[ { "key": "E7NCRW3K", "version": 31, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/E7NCRW3K", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/E7NCRW3K", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gilsinn et al.", "parsedDate": "2009", "numChildren": 0 }, "data": { "key": "E7NCRW3K", "version": 31, "itemType": "book", "title": "Delay Differential Equations: Recent Advances and New Directions", "creators": [ { "creatorType": "author", "firstName": "David E.", "lastName": "Gilsinn" }, { "creatorType": "author", "firstName": "Tamás", "lastName": "Kalmár-Nagy" }, { "creatorType": "author", "firstName": "Balakumar", "lastName": "Balachandran" } ], "abstractNote": "", "series": "", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2009", "publisher": "Springer US: Boston, MA", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "numPages": "", "ISBN": "9780387855943", "DOI": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Delay Differential Equations", "language": "eng", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Engineering -- Complexity", "type": 1 }, { "tag": "Engineering -- Computational Intelligence", "type": 1 }, { "tag": "Engineering -- Control , Robotics, Mechatronics", "type": 1 }, { "tag": "Engineering -- Ordinary Differential Equations", "type": 1 }, { "tag": "Engineering -- Systems Theory, Control", "type": 1 }, { "tag": "Engineering -- Vibration, Dynamical Systems, Control", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:49:32Z", "dateModified": "2014-03-21T16:49:32Z" } }, { "key": "SKX9PIN2", "version": 30, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/SKX9PIN2", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/SKX9PIN2", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Sahlholm and Henrik Johansson", "numChildren": 0 }, "data": { "key": "SKX9PIN2", "version": 30, "itemType": "journalArticle", "title": "Road grade estimation for look-ahead vehicle control using multiple measurement runs", "creators": [ { "creatorType": "author", "firstName": "Per", "lastName": "Sahlholm" }, { "creatorType": "author", "firstName": "Karl", "lastName": "Henrik Johansson" } ], "abstractNote": "Look-ahead cruise controllers and other advanced driver assistance systems for heavy duty vehicles require high precision digital topographic road maps. This paper presents a road grade estimation algorithm for creation of such maps based on Kalman filter fusion of vehicle sensor data and GPS positioning information. The algorithm uses data from multiple passes over the same road to improve previously stored road grade estimates. Measurement data from three test vehicles and six experiments have been used to evaluate the quality of the obtained road grade estimate compared to a known reference. The obtained final grade estimate compares favorably to one acquired from a specialized road grade measurement vehicle with a DGPS receiver and inertial measurement unit, with an average root mean square error of 0.17% grade.", "publicationTitle": "Control Engineering Practice", "publisher": "", "place": "", "date": "", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1016/j.conengprac.2009.09.007", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "0967-0661", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "eng", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Automotive System Identification And Modeling", "type": 1 }, { "tag": "General Automobile/road-environment Strategies", "type": 1 }, { "tag": "Kalman Filters", "type": 1 }, { "tag": "Sensor Fusion", "type": 1 }, { "tag": "global positioning systems", "type": 1 }, { "tag": "road traffic", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:37:51Z", "dateModified": "2014-03-21T16:37:51Z" } }, { "key": "ECS9CAKW", "version": 29, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/ECS9CAKW", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/ECS9CAKW", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gong et al.", "parsedDate": "2007-09", "numChildren": 0 }, "data": { "key": "ECS9CAKW", "version": 29, "itemType": "conferencePaper", "title": "Optimal power management of plug-in HEV with intelligent transportation system", "creators": [ { "creatorType": "author", "firstName": "Qiuming", "lastName": "Gong" }, { "creatorType": "author", "firstName": "Yaoyu", "lastName": "Li" }, { "creatorType": "author", "firstName": "Zhong-Ren", "lastName": "Peng" } ], "abstractNote": "Hybrid electric vehicles (HEV) have demonstrated their capability of improving the fuel economy and emission. The plug-in HEV (PHEV), utilizing more battery power, has become a more attractive upgrade of HEV. The charge-depletion mode is more appropriate for the power management of PHEV, i.e. the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the destination of the trip. In the past, the trip information has been considered as future information for vehicle operation and thus unavailable a priori. This situation can be changed by the current advancement of intelligent transportation systems (ITS) based on the use of on-board geographical information systems (GIS), global positioning systems (GPS) and advanced traffic flow modeling techniques. In this paper, a new approach of optimal power management of PHEV in the charge-depletion mode is proposed with driving cycle modeling based on the historic traffic information. A dynamic programming (DP) algorithm is applied to reinforce the charge-depletion control such that the SOC drops to a specific terminal value at the final time of the cycle. The vehicle model was based on a hybrid SUV. Only fuel consumption is considered for the current stage of study. Simulation results showed significant improvement in fuel economy compared with rule-based power management. Furthermore, simulations on several driving cycles using the proposed method showed much better consistency in fuel economy compared to the rule-based control.", "proceedingsTitle": "2007 IEEE/ASME international conference on Advanced intelligent mechatronics", "conferenceName": "2007 IEEE/ASME international conference on Advanced intelligent mechatronics", "publisher": "", "place": "", "date": "Sept 2007", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-6", "series": "", "seriesNumber": "", "DOI": "10.1109/AIM.2007.4412579", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Batteries", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "GIS", "type": 1 }, { "tag": "GPS", "type": 1 }, { "tag": "Geographic Information Systems", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Management information systems", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Plug-in Hybrid Electric Vehicles", "type": 1 }, { "tag": "Power Management", "type": 1 }, { "tag": "Power system management", "type": 1 }, { "tag": "Power system modeling", "type": 1 }, { "tag": "battery power", "type": 1 }, { "tag": "charge state", "type": 1 }, { "tag": "charge-depletion control", "type": 1 }, { "tag": "driving cycle modeling", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "dynamic programming algorithm", "type": 1 }, { "tag": "emission", "type": 1 }, { "tag": "energy management systems", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "global positioning systems", "type": 1 }, { "tag": "historic traffic information", "type": 1 }, { "tag": "hybrid SUV", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "intelligent transportation system", "type": 1 }, { "tag": "on-board geographical information systems", "type": 1 }, { "tag": "optimal power management", "type": 1 }, { "tag": "rule-based power management", "type": 1 }, { "tag": "traffic control", "type": 1 }, { "tag": "traffic engineering computing", "type": 1 }, { "tag": "traffic flow modeling", "type": 1 }, { "tag": "trip information", "type": 1 }, { "tag": "vehicle operation", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:31:12Z", "dateModified": "2014-03-21T16:31:12Z" } }, { "key": "4A3PFHWH", "version": 28, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/4A3PFHWH", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/4A3PFHWH", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Da-chuan", "parsedDate": "2010-10", "numChildren": 0 }, "data": { "key": "4A3PFHWH", "version": 28, "itemType": "conferencePaper", "title": "Algorithm of road information acquirement based on GPS and electronic map", "creators": [ { "creatorType": "author", "firstName": "Wei", "lastName": "Da-chuan" } ], "abstractNote": "In order to real-timely obtain road environmental information of vehicle's current location in its moving process, and to make its stalls transform adapt to the current road conditions, an algorithm was proposed, which is about how to acquire road information based on GPS and electronic map. Firstly, use GPS positioning technology to obtain information of the current position and direction of vehicles, and verify the extracted information. Then, combine with information about the correlative road parameters of electronic map to obtain the road parameters of the vehicle's current location and the front section along driving direction. Simulation results showed that the algorithm can obtain road information accurately and completely, can real-timely display the road conditions and driving conditions of the vehicle's current location on electronic map, and can effectively alleviate the shift problems when traffic is complex.", "proceedingsTitle": "2010 3rd International Congress on Image and Signal Processing (CISP)", "conferenceName": "2010 3rd International Congress on Image and Signal Processing (CISP)", "publisher": "", "place": "", "date": "October 2010", "eventPlace": "", "volume": "9", "issue": "", "numberOfVolumes": "", "pages": "4174-4178", "series": "", "seriesNumber": "", "DOI": "10.1109/CISP.2010.5646704", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Data mining", "type": 1 }, { "tag": "Databases", "type": 1 }, { "tag": "GPS", "type": 1 }, { "tag": "GPS location technology", "type": 1 }, { "tag": "Global Positioning System", "type": 1 }, { "tag": "Real time systems", "type": 1 }, { "tag": "Roads", "type": 1 }, { "tag": "Satellites", "type": 1 }, { "tag": "Vehicles", "type": 1 }, { "tag": "cartography", "type": 1 }, { "tag": "current road conditions", "type": 1 }, { "tag": "electronic map", "type": 1 }, { "tag": "information extraction", "type": 1 }, { "tag": "information retrieval", "type": 1 }, { "tag": "road information acquirement", "type": 1 }, { "tag": "road vehicles", "type": 1 }, { "tag": "traffic information systems", "type": 1 }, { "tag": "vehicle location", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:30:23Z", "dateModified": "2014-03-21T16:30:23Z" } }, { "key": "BFAII5XE", "version": 27, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/BFAII5XE", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/BFAII5XE", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gong et al.", "parsedDate": "2008-09", "numChildren": 0 }, "data": { "key": "BFAII5XE", "version": 27, "itemType": "conferencePaper", "title": "Computationally efficient optimal power management for plug-in hybrid electric vehicles based on spatial-domain two-scale dynamic programming", "creators": [ { "creatorType": "author", "firstName": "Qiuming", "lastName": "Gong" }, { "creatorType": "author", "firstName": "Yaoyu", "lastName": "Li" }, { "creatorType": "author", "firstName": "Zhong-Ren", "lastName": "Peng" } ], "abstractNote": "The plug-in hybrid electric vehicles (PHEV), utilizing more battery power, has become a next-generation HEV with great promise of higher fuel economy. Global optimization charge-depletion power management would be desirable. This has so far been hampered due to the a priori nature of the trip information and the almost prohibitive computational cost of global optimization techniques such as dynamic programming (DP). We have recently developed a two-scale dynamic programming approach as a nearly globally optimized charge-depletion strategy for the PHEV power management, through the combination with the intelligent transportation systems (ITS). The trip models are obtained via GPS, GIS, real-time and historical traffic flow data and advanced traffic flow modeling. A computationally efficient algorithm is proposed in this paper to enhance the previously developed two-scale DP framework so that the computational efficiency meets the need of on-board implementation. The electric-vehicle mode is reinforced for predicted traffic stops. For the remainder of the trip, the route is divided into a number of segments of certain length. For each segment, the fuel consumption and SOC change are calculated in advance according to different level of power splitting ratio, speed and acceleration/deceleration. The optimization can then be solved in spatial domain, with much less dimension than that in time domain. Simulation study showed significant reduction of computational time with minor loss of fuel economy performance.", "proceedingsTitle": "IEEE International Conference on Vehicular Electronics and Safety, 2008. ICVES 2008", "conferenceName": "IEEE International Conference on Vehicular Electronics and Safety, 2008. ICVES 2008", "publisher": "", "place": "", "date": "Sept 2008", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "90-95", "series": "", "seriesNumber": "", "DOI": "10.1109/ICVES.2008.4640882", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Batteries", "type": 1 }, { "tag": "Battery powered vehicles", "type": 1 }, { "tag": "Computational efficiency", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "Fuel Consumption", "type": 1 }, { "tag": "GIS", "type": 1 }, { "tag": "GPS", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Plug-in hybrid electric vehicle", "type": 1 }, { "tag": "Power system management", "type": 1 }, { "tag": "Power system modeling", "type": 1 }, { "tag": "acceleration-deceleration", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "global optimization charge-depletion power management", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "power splitting ratio", "type": 1 }, { "tag": "spatial-domain two-scale dynamic programming", "type": 1 }, { "tag": "traffic control", "type": 1 }, { "tag": "traffic flow modeling", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:28:46Z", "dateModified": "2014-03-21T16:28:46Z" } }, { "key": "5PC2DX4C", "version": 26, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/5PC2DX4C", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/5PC2DX4C", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Desai and Williamson", "parsedDate": "2009-10", "numChildren": 0 }, "data": { "key": "5PC2DX4C", "version": 26, "itemType": "conferencePaper", "title": "Comparative study of hybrid electric vehicle control strategies for improved drivetrain efficiency analysis", "creators": [ { "creatorType": "author", "firstName": "C.", "lastName": "Desai" }, { "creatorType": "author", "firstName": "S.S.", "lastName": "Williamson" } ], "abstractNote": "Stimulated by the urgent need for clean energy generation, improvised energy management strategies/control strategies for hybrid electric vehicles, plug-in hybrid electric vehicles, and all-electric vehicles are attracting much research interest. This paper presents the classification and study of various control strategies used in hybrid electric vehicles. Comparison of different control strategies with their advantages and disadvantages are also summarized, which provide novel directions for further developments.", "proceedingsTitle": "2009 IEEE Electrical Power Energy Conference (EPEC)", "conferenceName": "2009 IEEE Electrical Power Energy Conference (EPEC)", "publisher": "", "place": "", "date": "October 2009", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-6", "series": "", "seriesNumber": "", "DOI": "10.1109/EPEC.2009.5420888", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Batteries", "type": 1 }, { "tag": "Control strategy", "type": 1 }, { "tag": "Electric motors", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "Ice", "type": 1 }, { "tag": "Mechanical power transmission", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Plug-in Hybrid Electric Vehicles", "type": 1 }, { "tag": "Power demand", "type": 1 }, { "tag": "Power electronics", "type": 1 }, { "tag": "all-electric vehicles", "type": 1 }, { "tag": "clean energy generation", "type": 1 }, { "tag": "electric drives", "type": 1 }, { "tag": "electric vehicles", "type": 1 }, { "tag": "energy management systems", "type": 1 }, { "tag": "energy storage", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "fuzzy logic", "type": 1 }, { "tag": "global optimization", "type": 1 }, { "tag": "hybrid electric vehicle control strategies", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "improved drive train efficiency analysis", "type": 1 }, { "tag": "improvised energy management strategies", "type": 1 }, { "tag": "power transmission (mechanical)", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:27:33Z", "dateModified": "2014-03-21T16:27:33Z" } }, { "key": "AF66VRJ8", "version": 25, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/AF66VRJ8", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/AF66VRJ8", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gong et al.", "parsedDate": "2009-06", "numChildren": 0 }, "data": { "key": "AF66VRJ8", "version": 25, "itemType": "conferencePaper", "title": "Power management of plug-in hybrid electric vehicles using neural network based trip modeling", "creators": [ { "creatorType": "author", "firstName": "Qiuming", "lastName": "Gong" }, { "creatorType": "author", "firstName": "Yaoyu", "lastName": "Li" }, { "creatorType": "author", "firstName": "Zhongren", "lastName": "Peng" } ], "abstractNote": "The plug-in hybrid electric vehicles (PHEV), utilizing more battery power, has become a next-generation HEV with great promise of higher fuel economy. Global optimization charge-depletion power management would be desirable. This has so far been hampered due to the a priori nature of the trip information and the almost prohibitive computational cost of global optimization techniques such as dynamic programming (DP). Combined with the intelligent transportation systems (ITS), our previous work developed a two-scale dynamic programming approach as a nearly globally optimized charge-depletion strategy for PHEV power management. Trip model is obtained via GPS, GIS, real-time and historical traffic flow data and advanced traffic flow modeling. The gas-kinetic based model was used for the trip modeling in our previous study. The complicated partial deferential equation based model with several parameters needs to be calibrated had for implementation. In this paper, a neural network based trip model was developed for the highway portion, using the given data from WisTransPortal. The real test data was used for the training and validation of the network. The simulation results show that the obtained trip model using neural network can greatly improve the trip modeling accuracy, and thus improve the fuel economy. The potential of the advantages were indicated by the fuel economy comparison.", "proceedingsTitle": "American Control Conference, 2009. ACC '09.", "conferenceName": "American Control Conference, 2009. ACC '09.", "publisher": "", "place": "", "date": "June 2009", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "4601-4606", "series": "", "seriesNumber": "", "DOI": "10.1109/ACC.2009.5160623", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Battery powered vehicles", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Neural networks", "type": 1 }, { "tag": "Plug-in hybrid electric vehicle", "type": 1 }, { "tag": "Power system management", "type": 1 }, { "tag": "Power system modeling", "type": 1 }, { "tag": "Telecommunication traffic", "type": 1 }, { "tag": "WisTransPortal", "type": 1 }, { "tag": "advanced traffic flow modeling", "type": 1 }, { "tag": "automated highways", "type": 1 }, { "tag": "charge-depletion power management", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "electrical engineering computing", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "gas-kinetic based model", "type": 1 }, { "tag": "global optimization techniques", "type": 1 }, { "tag": "historical traffic flow data", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "neural nets", "type": 1 }, { "tag": "neural network based trip modeling", "type": 1 }, { "tag": "partial deferential equation based model", "type": 1 }, { "tag": "partial differential equations", "type": 1 }, { "tag": "traffic control", "type": 1 }, { "tag": "two-scale dynamic programming approach", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:26:20Z", "dateModified": "2014-03-21T16:26:20Z" } }, { "key": "KN38EUDQ", "version": 24, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/KN38EUDQ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/KN38EUDQ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Katsargyri et al.", "parsedDate": "2009-07", "numChildren": 0 }, "data": { "key": "KN38EUDQ", "version": 24, "itemType": "conferencePaper", "title": "Path dependent receding horizon control policies for Hybrid Electric Vehicles", "creators": [ { "creatorType": "author", "firstName": "G.-E.", "lastName": "Katsargyri" }, { "creatorType": "author", "firstName": "I.", "lastName": "Kolmanovsky" }, { "creatorType": "author", "firstName": "J.", "lastName": "Michelini" }, { "creatorType": "author", "firstName": "Ming", "lastName": "Kuang" }, { "creatorType": "author", "firstName": "A.", "lastName": "Phillips" }, { "creatorType": "author", "firstName": "M.", "lastName": "Rinehart" }, { "creatorType": "author", "firstName": "Munther", "lastName": "Dahleh" } ], "abstractNote": "Future hybrid electric vehicles (HEVs) may use path-dependent operating policies to improve fuel economy. In our previous work, we developed a dynamic programming (DP) algorithm for prescribing the battery state of charge (SoC) set-point, which in combination with a novel approach of route decomposition, has been shown to reduce fuel consumption over selected routes. In this paper, we propose and illustrate a receding horizon control (RHC) strategy for the on-board optimization of the fuel consumption. As compared to the DP approach, the computational requirements of the RHC strategy are lower. In addition, the RHC strategy is capable of correcting for differences between characteristics of a predicted route and a route actually traveled. Our numerical results indicate that the fuel economy potential of the RHC solution can approach that of the DP solution.", "proceedingsTitle": "2009 IEEE Control Applications, (CCA) Intelligent Control, (ISIC)", "conferenceName": "2009 IEEE Control Applications, (CCA) Intelligent Control, (ISIC)", "publisher": "", "place": "", "date": "July 2009", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "607-612", "series": "", "seriesNumber": "", "DOI": "10.1109/CCA.2009.5280977", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Batteries", "type": 1 }, { "tag": "Control systems", "type": 1 }, { "tag": "Fuel Consumption", "type": 1 }, { "tag": "Heuristic algorithms", "type": 1 }, { "tag": "Navigation", "type": 1 }, { "tag": "Pattern recognition", "type": 1 }, { "tag": "Recurrent neural networks", "type": 1 }, { "tag": "Roads", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "fuel cell vehicles", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "on-board optimization", "type": 1 }, { "tag": "path dependent receding horizon control policy", "type": 1 }, { "tag": "road vehicles", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:13:03Z", "dateModified": "2014-03-21T16:13:03Z" } }, { "key": "3Q4C9T8X", "version": 23, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/3Q4C9T8X", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/3Q4C9T8X", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gong et al.", "parsedDate": "2007-09", "numChildren": 0 }, "data": { "key": "3Q4C9T8X", "version": 23, "itemType": "conferencePaper", "title": "Trip Based Power Management of Plug-in Hybrid Electric Vehicle with Two-Scale Dynamic Programming", "creators": [ { "creatorType": "author", "firstName": "Qiuming", "lastName": "Gong" }, { "creatorType": "author", "firstName": "Yaoyu", "lastName": "Li" }, { "creatorType": "author", "firstName": "Zhong-Ren", "lastName": "Peng" } ], "abstractNote": "The plug-in HEV (PHEV), utilizing more battery power, has become the next-generation HEV with great promise of higher fuel economy. The charge-depletion mode is more appropriate for the power management of PHEV, i.e. the state of charge (SOC) is expected to drop to a low threshold when the vehicle reaches the destination of the trip. Globally optimized charge-depletion power management would be desirable. However, this has so far been hampered due to the a priori nature of the trip information and the prohibitive computational cost of global optimization techniques such as dynamic programming (DP). This situation can be changed by the current advancement of intelligent transportation systems (ITS) based on the use of on-board GPS, GIS, real-time and historical traffic flow data and advanced traffic flow modeling techniques. In this paper, charge-depletion control of PHEV is nearly globally optimized with a two-scale dynamic programming approach based on trip modeling with real-time and historical traffic data. For DP based charge-depletion control of PHEV, the SOC is desired to drop to a specific terminal value at the end of the trip. By specifying the origin and destination of a trip, the trip model, i.e. the driving cycle, is first obtained with the average of the historic traffic data, and the globally optimized SOC profile can be obtained by solving the overall or the macro-scale DP problem. The actual power management can be adapted during real-time vehicle operation with a micro-scale DP framework. The whole trip is divided into a number of segments, and for each segment, a smaller DP will be solved using the on-line traffic data transmitted to the vehicle from the traffic flow sensors within the segment. The SOC obtained in the macro-scale DP solution at the terminal location is reinforced to be the final value. Simulation study has been performed on a hybrid SUV model from ADVISOR, and a defined trip in the greater Milwaukee area. The simulation results demo- nstrated significant improvement in fuel economy using DP based charge-depletion control compared to rule based control, and also the benefit of adaptation using the two-scale DP method.", "proceedingsTitle": "IEEE Vehicle Power and Propulsion Conference, 2007. VPPC 2007", "conferenceName": "IEEE Vehicle Power and Propulsion Conference, 2007. VPPC 2007", "publisher": "", "place": "", "date": "Sept 2007", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "12-19", "series": "", "seriesNumber": "", "DOI": "10.1109/VPPC.2007.4544089", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "ADVISOR", "type": 1 }, { "tag": "Batteries", "type": 1 }, { "tag": "Computational efficiency", "type": 1 }, { "tag": "Computational intelligence", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "GIS", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Plug-in Hybrid Electric Vehicles", "type": 1 }, { "tag": "Plug-in hybrid electric vehicle", "type": 1 }, { "tag": "Power Management", "type": 1 }, { "tag": "Power system management", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "electric vehicles", "type": 1 }, { "tag": "fuel economy", "type": 1 }, { "tag": "globally optimized charge-depletion power management", "type": 1 }, { "tag": "hybrid SUV model", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "intelligent transportation system", "type": 1 }, { "tag": "onboard GPS", "type": 1 }, { "tag": "traffic control", "type": 1 }, { "tag": "traffic flow data", "type": 1 }, { "tag": "traffic flow modeling techniques", "type": 1 }, { "tag": "traffic flow sensors", "type": 1 }, { "tag": "trip based power management", "type": 1 }, { "tag": "two-scale dynamic programming", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:12:40Z", "dateModified": "2014-03-21T16:12:40Z" } }, { "key": "7MDPF9SC", "version": 22, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/7MDPF9SC", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/7MDPF9SC", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Katsargyri et al.", "parsedDate": "2009-06", "numChildren": 0 }, "data": { "key": "7MDPF9SC", "version": 22, "itemType": "conferencePaper", "title": "Optimally controlling Hybrid Electric Vehicles using path forecasting", "creators": [ { "creatorType": "author", "firstName": "G.-E.", "lastName": "Katsargyri" }, { "creatorType": "author", "firstName": "I.V.", "lastName": "Kolmanovsky" }, { "creatorType": "author", "firstName": "J.", "lastName": "Michelini" }, { "creatorType": "author", "firstName": "M.L.", "lastName": "Kuang" }, { "creatorType": "author", "firstName": "A.M.", "lastName": "Phillips" }, { "creatorType": "author", "firstName": "M.", "lastName": "Rinehart" }, { "creatorType": "author", "firstName": "M.A.", "lastName": "Dahleh" } ], "abstractNote": "The paper examines path-dependent control of Hybrid Electric Vehicles (HEVs). In this approach we seek to improve HEV fuel economy by optimizing charging and discharging of the vehicle battery depending on the forecasted vehicle route. The route is decomposed into a series connection of route segments with (partially) known properties. The dynamic programming is used as a tool to quantify the benefits offered by route information availability.", "proceedingsTitle": "American Control Conference, 2009. ACC '09.", "conferenceName": "American Control Conference, 2009. ACC '09.", "publisher": "", "place": "", "date": "June 2009", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "4613-4617", "series": "", "seriesNumber": "", "DOI": "10.1109/ACC.2009.5160504", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Battery powered vehicles", "type": 1 }, { "tag": "Control systems", "type": 1 }, { "tag": "Electric motors", "type": 1 }, { "tag": "Engines", "type": 1 }, { "tag": "Fuels", "type": 1 }, { "tag": "Generators", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Vehicle dynamics", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "path forecasting", "type": 1 }, { "tag": "route information availability", "type": 1 }, { "tag": "vehicle battery", "type": 1 }, { "tag": "vehicle route forecasting", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:11:56Z", "dateModified": "2014-03-21T16:11:56Z" } }, { "key": "HJJEW4CP", "version": 21, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/HJJEW4CP", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/HJJEW4CP", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Zhang and Vahid", "parsedDate": "2010-06", "numChildren": 0 }, "data": { "key": "HJJEW4CP", "version": 21, "itemType": "conferencePaper", "title": "Real-time optimal control of plug-in hybrid vehicles with trip preview", "creators": [ { "creatorType": "author", "firstName": "Chen", "lastName": "Zhang" }, { "creatorType": "author", "firstName": "A.", "lastName": "Vahid" } ], "abstractNote": "The global optimal solutions of energy management of hybrid electric vehicles depend on future driving conditions. This paper investigates a potential real-time methodology to integrate long-horizon preview information for plug-in hybrid vehicles. Equivalent Fuel Consumption Minimization Strategy (ECMS) is deployed as an instantaneous real-time minimization strategy with parameters adjusted by estimated future driving conditions and obtained either from Dynamic Programming (DP) or from a global ECMS. The preview information is decomposed into future road terrain stored as in-vehicle 3D maps and future velocity estimated from streaming or historic traffic data. We show that with estimated future information, substantial reduction in fuel use, up to 13% is possible compared with a rule-based control strategy without any preview. Further improvement of fuel consumption on the order of 1% could be achieved with exact future information.", "proceedingsTitle": "American Control Conference (ACC), 2010", "conferenceName": "American Control Conference (ACC), 2010", "publisher": "", "place": "", "date": "June 2010", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "6917-6922", "series": "", "seriesNumber": "", "DOI": "", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Battery management systems", "type": 1 }, { "tag": "Brushless DC motors", "type": 1 }, { "tag": "Combustion", "type": 1 }, { "tag": "Energy management", "type": 1 }, { "tag": "Engines", "type": 1 }, { "tag": "Fuels", "type": 1 }, { "tag": "Hybrid electric vehicle", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Power demand", "type": 1 }, { "tag": "Roads", "type": 1 }, { "tag": "dynamic programming", "type": 1 }, { "tag": "energy management systems", "type": 1 }, { "tag": "equivalent fuel consumption minimization strategy", "type": 1 }, { "tag": "hybrid electric vehicles", "type": 1 }, { "tag": "long-horizon preview information", "type": 1 }, { "tag": "plug-in hybrid vehicle", "type": 1 }, { "tag": "real-time optimal control", "type": 1 }, { "tag": "road terrain", "type": 1 }, { "tag": "rule-based control", "type": 1 }, { "tag": "traffic data streaming", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:10:50Z", "dateModified": "2014-03-21T16:10:50Z" } }, { "key": "9FTFWW7T", "version": 20, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/9FTFWW7T", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/9FTFWW7T", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Kermani et al.", "parsedDate": "2012-04", "numChildren": 0 }, "data": { "key": "9FTFWW7T", "version": 20, "itemType": "journalArticle", "title": "Predictive energy management for hybrid vehicle", "creators": [ { "creatorType": "author", "firstName": "S.", "lastName": "Kermani" }, { "creatorType": "author", "firstName": "S.", "lastName": "Delprat" }, { "creatorType": "author", "firstName": "T. M.", "lastName": "Guerra" }, { "creatorType": "author", "firstName": "R.", "lastName": "Trigui" }, { "creatorType": "author", "firstName": "B.", "lastName": "Jeanneret" } ], "abstractNote": "Hybrid vehicle control strategies are algorithms devoted to the energy management. At each sampling time they choose the powertrain operating point in order to minimize a criterion, usually the fuel consumption. In simulation, an optimization algorithm can be derived from the minimum principle. For real time control, a Model Predictive Control scheme can be used but it requires the prediction of the future driving conditions. Their time ordered prediction is very difficult. Moreover, if the optimal costate is constant, only the prediction of their distribution is sufficient and allows deriving a real time control strategy. Experimental results are provided to illustrate the benefits of this approach.", "publicationTitle": "Control Engineering Practice", "publisher": "", "place": "", "date": "April 2012", "volume": "20", "issue": "4", "section": "", "partNumber": "", "partTitle": "", "pages": "408-420", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Control Engineering Practice", "DOI": "10.1016/j.conengprac.2011.12.001", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0967066111002498", "accessDate": "2014-03-21T16:08:25Z", "PMID": "", "PMCID": "", "ISSN": "0967-0661", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Energy management", "type": 1 }, { "tag": "Hybrid electric vehicle", "type": 1 }, { "tag": "Minimum principle", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Real time control", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:08:25Z", "dateModified": "2014-03-21T16:08:25Z" } }, { "key": "96QIRU7G", "version": 19, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/96QIRU7G", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/96QIRU7G", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Sorrentino et al.", "parsedDate": "2013-01-01", "numChildren": 0 }, "data": { "key": "96QIRU7G", "version": 19, "itemType": "journalArticle", "title": "An integrated mathematical tool aimed at developing highly performing and cost-effective fuel cell hybrid vehicles", "creators": [ { "creatorType": "author", "firstName": "Marco", "lastName": "Sorrentino" }, { "creatorType": "author", "firstName": "Cesare", "lastName": "Pianese" }, { "creatorType": "author", "firstName": "Mario", "lastName": "Maiorino" } ], "abstractNote": "An integrated mathematical tool is presented to simultaneously design powertrain and control strategies for PEM fuel cell hybrid vehicles. Such an activity is motivated by the positive impact of car electrification on transportation related GHG emissions, and by the potential of hydrogen as an intensive energy carrier to avoid heavy battery packs, as required for pure electric cars. Moreover, the availability of reliable and comprehensive mathematical tools is recognized as a key to develop cost effective and highly performing innovative powertrains.\nA database of hybridizing devices' costs and weights is developed and exploited in conjunction with a weight model to size the powertrain as a function of degree of hybridization. In parallel, a versatile heuristic control strategy is proposed to easily adapt control rules to different powertrains. Then, both the weight model and the heuristic control strategy are embedded into an optimization procedure to determine the most convenient PEM fuel cell hybrid vehicle configuration.\nThe methodology is tested for a fuel cell hybrid shuttle, whose hydrogen feeding is guaranteed by a photovoltaic on-site generation system. Such a case study not only is suitable to assess the proposed optimization procedure, but also serves at indicating the most promising short-term applications of fuel cell hybrid vehicles.", "publicationTitle": "Journal of Power Sources", "publisher": "", "place": "", "date": "January 1, 2013", "volume": "221", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "308-317", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Journal of Power Sources", "DOI": "10.1016/j.jpowsour.2012.08.001", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0378775312012591", "accessDate": "2014-03-21T16:04:54Z", "PMID": "", "PMCID": "", "ISSN": "0378-7753", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Control", "type": 1 }, { "tag": "Design", "type": 1 }, { "tag": "Fuel cell hybrid vehicle", "type": 1 }, { "tag": "Modeling", "type": 1 }, { "tag": "PEM", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:04:54Z", "dateModified": "2014-03-21T16:04:54Z" } }, { "key": "I4MF2PPV", "version": 18, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/I4MF2PPV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/I4MF2PPV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Carslaw et al.", "parsedDate": "2010-07", "numChildren": 0 }, "data": { "key": "I4MF2PPV", "version": 18, "itemType": "journalArticle", "title": "Comprehensive analysis of the carbon impacts of vehicle intelligent speed control", "creators": [ { "creatorType": "author", "firstName": "David C.", "lastName": "Carslaw" }, { "creatorType": "author", "firstName": "Paul S.", "lastName": "Goodman" }, { "creatorType": "author", "firstName": "Frank C. H.", "lastName": "Lai" }, { "creatorType": "author", "firstName": "Oliver M. J.", "lastName": "Carsten" } ], "abstractNote": "In recent years sophisticated technologies have been developed to control vehicle speed based on the type of road the vehicle is driven on using Global Positioning Systems and in-car technology that can alter the speed of the vehicle. While reducing the speed of road vehicles is primarily of interest from a safety perspective, vehicle speed is also an important determinant of vehicle emissions and thus these technologies can be expected to have impacts on a range of exhaust emissions. This work analyses the results from a very large, comprehensive field trial that used 20 instrumented vehicles with and without speed control driven almost 500,000 km measuring vehicle speed at 10 Hz. We develop individual vehicle modal emissions models for CO2 for 30 Euro III and Euro IV cars at a 1-Hz time resolution. Generalized Additive Models were used to describe how emissions from individual vehicles vary depending on their driving conditions, taking account of variable interactions and time-lag effects. We quantify the impact that vehicle speed control has on-vehicle emissions of CO2 by road type, fuel type and driver behaviour. Savings in CO2 of ≈6% were found on average for motorway-type roads when mandatory speed control was used compared with base case conditions. For most other types of road, speed control has very little effect on emissions of CO2 and in some cases can result in increased emissions for low-speed limit urban roads. We also find that there is on average a 20% difference in CO2 emission between the lowest and highest emitting driver, which highlights the importance of driver behaviour in general as a means of reducing emissions of CO2.", "publicationTitle": "Atmospheric Environment", "publisher": "", "place": "", "date": "July 2010", "volume": "44", "issue": "23", "section": "", "partNumber": "", "partTitle": "", "pages": "2674-2680", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Atmospheric Environment", "DOI": "10.1016/j.atmosenv.2010.04.046", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1352231010003535", "accessDate": "2014-03-21T16:04:35Z", "PMID": "", "PMCID": "", "ISSN": "1352-2310", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Emission inventory", "type": 1 }, { "tag": "Fuel Consumption", "type": 1 }, { "tag": "Intelligent speed adaptation", "type": 1 }, { "tag": "Vehicle emissions", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:04:35Z", "dateModified": "2014-03-21T16:04:35Z" } }, { "key": "3XW92HD3", "version": 17, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/3XW92HD3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/3XW92HD3", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Shams-Zahraei et al.", "parsedDate": "2012-10-15", "numChildren": 0 }, "data": { "key": "3XW92HD3", "version": 17, "itemType": "journalArticle", "title": "Integrated thermal and energy management of plug-in hybrid electric vehicles", "creators": [ { "creatorType": "author", "firstName": "Mojtaba", "lastName": "Shams-Zahraei" }, { "creatorType": "author", "firstName": "Abbas Z.", "lastName": "Kouzani" }, { "creatorType": "author", "firstName": "Steffen", "lastName": "Kutter" }, { "creatorType": "author", "firstName": "Bernard", "lastName": "Bäker" } ], "abstractNote": "In plug-in hybrid electric vehicles (PHEVs), the engine temperature declines due to reduced engine load and extended engine off period. It is proven that the engine efficiency and emissions depend on the engine temperature. Also, temperature influences the vehicle air-conditioner and the cabin heater loads. Particularly, while the engine is cold, the power demand of the cabin heater needs to be provided by the batteries instead of the waste heat of engine coolant. The existing energy management strategies (EMS) of PHEVs focus on the improvement of fuel efficiency based on hot engine characteristics neglecting the effect of temperature on the engine performance and the vehicle power demand. This paper presents a new EMS incorporating an engine thermal management method which derives the global optimal battery charge depletion trajectories. A dynamic programming-based algorithm is developed to enforce the charge depletion boundaries, while optimizing a fuel consumption cost function by controlling the engine power. The optimal control problem formulates the cost function based on two state variables: battery charge and engine internal temperature. Simulation results demonstrate that temperature and the cabin heater/air-conditioner power demand can significantly influence the optimal solution for the EMS, and accordingly fuel efficiency and emissions of PHEVs.", "publicationTitle": "Journal of Power Sources", "publisher": "", "place": "", "date": "October 15, 2012", "volume": "216", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "237-248", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Journal of Power Sources", "DOI": "10.1016/j.jpowsour.2012.05.055", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S037877531200924X", "accessDate": "2014-03-21T16:01:55Z", "PMID": "", "PMCID": "", "ISSN": "0378-7753", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Dynamic programing", "type": 1 }, { "tag": "Energy management strategy", "type": 1 }, { "tag": "Optimal control", "type": 1 }, { "tag": "Plug-in hybrid electric vehicle", "type": 1 }, { "tag": "Temperature", "type": 1 }, { "tag": "Thermal management", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T16:01:55Z", "dateModified": "2014-03-21T16:01:55Z" } }, { "key": "3SSK2BP5", "version": 16, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/3SSK2BP5", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/3SSK2BP5", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Utamaphethai and Ghosh", "parsedDate": "1998-03", "numChildren": 0 }, "data": { "key": "3SSK2BP5", "version": 16, "itemType": "journalArticle", "title": "Dicaf: a distributed architecture for intelligent transportation", "creators": [ { "creatorType": "author", "firstName": "N.", "lastName": "Utamaphethai" }, { "creatorType": "author", "firstName": "S.", "lastName": "Ghosh" } ], "abstractNote": "The solution to increasing traffic congestion is not to simply build new roads. Instead, researchers hope to use technology to make more efficient use of the highway network that already exists. Key efforts to date have fallen into two categories. One set of studies has looked at the use of a centralized traffic management center that collects traffic congestion information at a single point and relays it to on-board computers in vehicles or directly to the drivers. Another set of studies has looked at systems that would prescribe the routes for vehicles. The authors describe their Dicaf (distributed scalable architecture for IVHS using a continuous-function congestion measure) system, which envisions a network of distributed, independent traffic management centers that provide congestion and other information to on-board navigation systems in the automobiles themselves. The navigation system uses that information to help drivers avoid slower traffic and thus find the fastest route home or anywhere", "publicationTitle": "Computer", "publisher": "", "place": "", "date": "March 1998", "volume": "31", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "78-84", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/2.660193", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "0018-9162", "archive": "", "archiveLocation": "", "shortTitle": "Dicaf", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Computer architecture", "type": 1 }, { "tag": "Computer network management", "type": 1 }, { "tag": "Dicaf", "type": 1 }, { "tag": "IVHS", "type": 1 }, { "tag": "Intelligent transportation systems", "type": 1 }, { "tag": "Navigation", "type": 1 }, { "tag": "Relays", "type": 1 }, { "tag": "Road transportation", "type": 1 }, { "tag": "Telecommunication traffic", "type": 1 }, { "tag": "Vehicle driving", "type": 1 }, { "tag": "Vehicles", "type": 1 }, { "tag": "automated highways", "type": 1 }, { "tag": "automobiles", "type": 1 }, { "tag": "centralized traffic management center", "type": 1 }, { "tag": "continuous-function congestion measure", "type": 1 }, { "tag": "distributed processing", "type": 1 }, { "tag": "distributed scalable architecture", "type": 1 }, { "tag": "intelligent transportation", "type": 1 }, { "tag": "on-board computers", "type": 1 }, { "tag": "on-board navigation systems", "type": 1 }, { "tag": "road traffic", "type": 1 }, { "tag": "road traffic congestion", "type": 1 }, { "tag": "road vehicles", "type": 1 }, { "tag": "traffic information systems", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-21T15:59:21Z", "dateModified": "2014-03-21T15:59:21Z" } }, { "key": "FFRFVZM7", "version": 15, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/FFRFVZM7", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/FFRFVZM7", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Reich", "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "FFRFVZM7", "version": 15, "itemType": "journalArticle", "title": "Transportation Efficiency", "creators": [ { "creatorType": "author", "firstName": "Aliciaa", "lastName": "Reich" } ], "abstractNote": "ABSTRACT The transportation sector consumes 70% of the petroleum that the U.S. uses for fuel, which leads one to study transportation to identify significant opportunities to save energy. Every 1-cent increase in the price of a gallon of gas costs the U.S. Postal Service (USPS) $8 million per year for their 200,000-vehicle fleet. To reduce American dependence on fossil fuels, the carbon footprint left by vehicular fleets should be evaluated. This article reports on the current state of fuel efficiency and fleet efficiency in the U.S., including government, municipal, and large commercial sectors. It also discusses opportunities in behavior modification to improve fleet efficiency. Case studies are presented showing evidence of best practices currently implemented. By studying transportation fleets and educating fleet managers about viable alternatives to improve fleet efficiency, we can save significant amounts of fuel and reduce our carbon footprint. This analysis demonstrates that transportation efficiency is economically feasible for a wide variety of public and private entities and is beneficial to the environment.", "publicationTitle": "Strategic Planning for Energy and the Environment", "publisher": "", "place": "", "date": "2012", "volume": "32", "issue": "2", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1080/10485236.2012.10554233", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1048-5236", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:43:03Z", "dateModified": "2014-03-20T22:43:03Z" } }, { "key": "22B6BMIX", "version": 14, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/22B6BMIX", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/22B6BMIX", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Magliocchetti et al.", "parsedDate": "2011", "numChildren": 0 }, "data": { "key": "22B6BMIX", "version": 14, "itemType": "journalArticle", "title": "A Personal Mobility Assistant based on Ambient Intelligence to Promote Sustainable Travel Choices", "creators": [ { "creatorType": "author", "firstName": "Daniele", "lastName": "Magliocchetti" }, { "creatorType": "author", "firstName": "Martin", "lastName": "Gielow" }, { "creatorType": "author", "firstName": "Federico", "lastName": "De Vigili" }, { "creatorType": "author", "firstName": "Giuseppe", "lastName": "Conti" }, { "creatorType": "author", "firstName": "Raffaele", "lastName": "De Amicis" } ], "abstractNote": "An increasing amount of attention is being paid by local public administrations, national and federal governments as well as by international institutions, such as the European Commission, to improve personal mobility within urban environments through the use of public transports. Improving mobility of people through increased use of public transportation has a number of advantages since it is strategic to reduce energy consumption, to lower emissions and pollution levels, to improve public safety, and to dramatically reduce congestions and road traffic. Reducing private transportation clearly bring significant benefits not only to citizens’ quality of life and public health but it also results in a more efficient urban system as a whole, with consequent substantial economic benefits at the wider societal level. Based on this assumption, this paper presents a so-called personal mobility assistant, i.e. a software for smartphones and tablets which promotes use of public transport by helping user identify the best travel option across a multi-modal transport network, through a user-friendly interface that intelligently adjusts to user preferences and to contextual information.", "publicationTitle": "Procedia Computer Science", "publisher": "", "place": "", "date": "2011", "volume": "5", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "892-899", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Procedia Computer Science", "DOI": "10.1016/j.procs.2011.07.124", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S1877050911004492", "accessDate": "2014-03-20T22:42:36Z", "PMID": "", "PMCID": "", "ISSN": "1877-0509", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "intelligent transportation system", "type": 1 }, { "tag": "mobile computing", "type": 1 }, { "tag": "personal mobility assistant", "type": 1 }, { "tag": "user-friendly mobile HCI", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:42:36Z", "dateModified": "2014-03-20T22:42:36Z" } }, { "key": "CPVTJ86P", "version": 13, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/CPVTJ86P", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/CPVTJ86P", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Schwieger et al.", "parsedDate": "2007", "numChildren": 0 }, "data": { "key": "CPVTJ86P", "version": 13, "itemType": "journalArticle", "title": "Mobile phone positioning for traffic state acquisition", "creators": [ { "creatorType": "author", "firstName": "Volker", "lastName": "Schwieger" }, { "creatorType": "author", "firstName": "Katrin", "lastName": "Ramm" }, { "creatorType": "author", "firstName": "Renate", "lastName": "Czommer" }, { "creatorType": "author", "firstName": "Wolfgang", "lastName": "Möhlenbrink" } ], "abstractNote": "Up to now different methods for the determination of positions and velocities of road users such as e.g. floating car data (FCD) or local loop data are used for traffic state acquisition and forecast. This paper deals with the determination of trajectories of road users applying information which are available within the GSM network. The signal strength and timing advance values are the measurements introduced into different least-square algorithms to determine positions. One alternative estimates the positions by distance measurements and further static information of the GSM network, the second alternative matches measured signal strengths on a given signal strength map. Both solutions are smoothed afterwards in parallel by a moving average filter and a Kalman filter algorithm. The resulting trajectories are matched on a digital road map using routing algorithms and map aiding procedures. These trajectories are called floating phone data (FPD). First intermediate results show an accuracy of approximately 200 to 300 m for the signal strength matching approach. For the time being correctness of the identified digital road elements is given for rural and suburban regions only. Further investigations have to be realised regarding the verification of these intermediate results as well as the extension of road identification to urban areas.", "publicationTitle": "Journal of Applied Geodesy", "publisher": "", "place": "", "date": "2007", "volume": "1", "issue": "3", "section": "", "partNumber": "", "partTitle": "", "pages": "125-135", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1515/jag.2007.015", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1862-9016", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Kalman Filter", "type": 1 }, { "tag": "Map Aiding", "type": 1 }, { "tag": "Mobile Phone Positioning", "type": 1 }, { "tag": "Moving Average Filter", "type": 1 }, { "tag": "Traffic State Acquisition", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:40:42Z", "dateModified": "2014-03-20T22:40:42Z" } }, { "key": "WRVWF9RZ", "version": 12, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/WRVWF9RZ", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/WRVWF9RZ", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Gajanand and Narendran", "parsedDate": "2013", "numChildren": 0 }, "data": { "key": "WRVWF9RZ", "version": 12, "itemType": "journalArticle", "title": "Green route planning to reduce the environmental impact of distribution", "creators": [ { "creatorType": "author", "firstName": "M. S.", "lastName": "Gajanand" }, { "creatorType": "author", "firstName": "T. T.", "lastName": "Narendran" } ], "abstractNote": "Distribution of goods involves massive deployment of vehicles whose emissions are a major concern for environmentalists. Factors such as speed, nature of the road, load carried and other vehicle parameters apart from the distance are known to affect the emissions as well as the consumption of fuel. Between the same pair of nodes, taking an alternative route with different lengths and velocities can result in reduced fuel consumption. Literature suggests that minimising the consumption of fuel results in reducing the emission of harmful gases and of particulate matter. We formulate a multiple-route-vehicle-routing problem to evaluate alternative routes between nodes and solve for minimising the fuel consumption. The results from trial data-sets provide insights into the impact of the solutions on the number of vehicles used, fuel consumed, distance travelled, travel time and cost. This paper provides a means of routing distribution vehicles so as to reduce their impact on the environment.", "publicationTitle": "International Journal of Logistics Research and Applications", "publisher": "", "place": "", "date": "2013", "volume": "16", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1080/13675567.2013.831400", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1367-5567", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Alternative Routes", "type": 1 }, { "tag": "Co Emissions", "type": 1 }, { "tag": "Environment", "type": 1 }, { "tag": "Fuel Consumption", "type": 1 }, { "tag": "Green Logistics", "type": 1 }, { "tag": "Vehicle Routing", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:31:04Z", "dateModified": "2014-03-20T22:31:04Z" } }, { "key": "CX27JGUT", "version": 11, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/CX27JGUT", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/CX27JGUT", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Spielhofer et al.", "parsedDate": "2005-09", "numChildren": 0 }, "data": { "key": "CX27JGUT", "version": 11, "itemType": "conferencePaper", "title": "Roncalli - position dependent in-vehicle real time information for road users - an overview", "creators": [ { "creatorType": "author", "firstName": "R.", "lastName": "Spielhofer" }, { "creatorType": "author", "firstName": "P.", "lastName": "Maurer" }, { "creatorType": "author", "firstName": "M.", "lastName": "Meissner" }, { "creatorType": "author", "firstName": "K.", "lastName": "Machata" }, { "creatorType": "author", "firstName": "N.", "lastName": "Widmann" } ], "abstractNote": "This paper describes the outcomes of the projects Roncalli and Roncall 12, two ITS projects that deal with road safety information for the driver and the trading of traffic data in general at a market place. A client-server architecture for delivering road safety information directly to the driver and the resulting services is described. Furthermore, the design of a market place for traffic data is outlined.", "proceedingsTitle": "2005 IEEE Intelligent Transportation Systems, 2005. Proceedings", "conferenceName": "2005 IEEE Intelligent Transportation Systems, 2005. Proceedings", "publisher": "", "place": "", "date": "Sept 2005", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1012-1016", "series": "", "seriesNumber": "", "DOI": "10.1109/ITSC.2005.1520189", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cellular phones", "type": 1 }, { "tag": "Databases", "type": 1 }, { "tag": "Global Positioning System", "type": 1 }, { "tag": "Ground penetrating radar", "type": 1 }, { "tag": "Network servers", "type": 1 }, { "tag": "Rain", "type": 1 }, { "tag": "Sensor phenomena and characterization", "type": 1 }, { "tag": "Sensor systems", "type": 1 }, { "tag": "Tiles", "type": 1 }, { "tag": "automated highways", "type": 1 }, { "tag": "client-server architecture", "type": 1 }, { "tag": "client-server systems", "type": 1 }, { "tag": "driver information systems", "type": 1 }, { "tag": "in-vehicle real time information", "type": 1 }, { "tag": "road safety", "type": 1 }, { "tag": "road safety information", "type": 1 }, { "tag": "road traffic", "type": 1 }, { "tag": "road users", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:27:56Z", "dateModified": "2014-03-20T22:27:56Z" } }, { "key": "VPWD4ETV", "version": 10, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/VPWD4ETV", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/VPWD4ETV", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Lioudakis et al.", "parsedDate": "2010-05", "numChildren": 0 }, "data": { "key": "VPWD4ETV", "version": 10, "itemType": "conferencePaper", "title": "An Intelligent Traffic Management System for the Eco-Optimization of Urban Traffic Flows", "creators": [ { "creatorType": "author", "firstName": "G. V.", "lastName": "Lioudakis" }, { "creatorType": "author", "firstName": "C. A.", "lastName": "Papagianni" }, { "creatorType": "author", "firstName": "D.I.", "lastName": "Kaklamani" }, { "creatorType": "author", "firstName": "I.S.", "lastName": "Venieris" }, { "creatorType": "author", "firstName": "A.H.", "lastName": "Salden" } ], "abstractNote": "Road traffic congestion constitutes a parameter that significantly affects quality of life in modern cities, while it has a direct impact on the environmental pollution. Optimizing the traffic flows would bring considerable and multi-aspect gains. In this light, this paper proposes an intelligent traffic management system for the provision of a dynamic, in real-time fleet navigation service at large scale. The framework collects all available contextual information generated \"on the road\" and uses a multi-layer, distributed, hierarchical middleware, for optimizing traffic flows in a cellular fashion. The framework enables also the provision of other value-added services, while it puts special care on the issue of protecting personal privacy.", "proceedingsTitle": "2010 IEEE International Conference on Communications Workshops (ICC)", "conferenceName": "2010 IEEE International Conference on Communications Workshops (ICC)", "publisher": "", "place": "", "date": "May 2010", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "1-5", "series": "", "seriesNumber": "", "DOI": "10.1109/ICCW.2010.5503897", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Cities and towns", "type": 1 }, { "tag": "Intelligent systems", "type": 1 }, { "tag": "Large-scale systems", "type": 1 }, { "tag": "Navigation", "type": 1 }, { "tag": "Pollution", "type": 1 }, { "tag": "Privacy", "type": 1 }, { "tag": "Protection", "type": 1 }, { "tag": "Real time systems", "type": 1 }, { "tag": "Roads", "type": 1 }, { "tag": "air pollution", "type": 1 }, { "tag": "automated highways", "type": 1 }, { "tag": "eco-optimization", "type": 1 }, { "tag": "environmental pollution", "type": 1 }, { "tag": "intelligent traffic management system", "type": 1 }, { "tag": "middleware", "type": 1 }, { "tag": "optimisation", "type": 1 }, { "tag": "road traffic", "type": 1 }, { "tag": "road traffic congestion", "type": 1 }, { "tag": "traffic flow optimization", "type": 1 }, { "tag": "urban traffic flows", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T22:27:05Z", "dateModified": "2014-03-20T22:27:05Z" } }, { "key": "TVGHTIRK", "version": 9, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/TVGHTIRK", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/TVGHTIRK", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Nienhüser et al.", "parsedDate": "2012", "numChildren": 0 }, "data": { "key": "TVGHTIRK", "version": 9, "itemType": "journalArticle", "title": "Energy Efficient Driving and Operation Strategies Based on Situation Awareness and Reasoning", "creators": [ { "creatorType": "author", "firstName": "Dennis", "lastName": "Nienhüser" }, { "creatorType": "author", "firstName": "Tobias", "lastName": "Bär" }, { "creatorType": "author", "firstName": "Ralf", "lastName": "Kohlhaas" }, { "creatorType": "author", "firstName": "Thomas", "lastName": "Schamm" }, { "creatorType": "author", "firstName": "Jochen", "lastName": "Zimmermann" }, { "creatorType": "author", "firstName": "Thomas", "lastName": "Gumpp" }, { "creatorType": "author", "firstName": "Marcus", "lastName": "Strand" }, { "creatorType": "author", "firstName": "Oliver", "lastName": "Bringmann" }, { "creatorType": "author", "firstName": "Johann Marius", "lastName": "Zöllner" } ], "abstractNote": "A vehicle´s basic energy consumption is determined by its design, but the driving behavior is another important factor having a major influence on the overall consumption. In this work we show how information technology can be used to gain an understanding of the whole traffic situation and use it to derive energy optimal behavior. It can be used to optimize operation strategies and in cooperation with the driver helping him to maximize fuel saving by anticipatory driving. We summarize the research challenges that need to be solved to create energy efficiency assistance systems and present an overview of our solutions.", "publicationTitle": "it - Information Technology", "publisher": "", "place": "", "date": "2012", "volume": "54", "issue": "1", "section": "", "partNumber": "", "partTitle": "", "pages": "5-16", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1524/itit.2012.0658", "citationKey": "", "url": "", "accessDate": "", "PMID": "", "PMCID": "", "ISSN": "1611-2776", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "Primo", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Automotive", "type": 1 }, { "tag": "Driving Strategies", "type": 1 }, { "tag": "Environment Perception", "type": 1 }, { "tag": "Operation Strategies", "type": 1 }, { "tag": "Situation Interpretation", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T21:11:28Z", "dateModified": "2014-03-20T21:11:28Z" } }, { "key": "GUMUM76J", "version": 8, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/GUMUM76J", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/GUMUM76J", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Iacob et al.", "parsedDate": "2013-11-01", "numChildren": 0 }, "data": { "key": "GUMUM76J", "version": 8, "itemType": "journalArticle", "title": "Towards a reference architecture for fuel-based carbon management systems in the logistics industry", "creators": [ { "creatorType": "author", "firstName": "M. E.", "lastName": "Iacob" }, { "creatorType": "author", "firstName": "M. J. van", "lastName": "Sinderen" }, { "creatorType": "author", "firstName": "M.", "lastName": "Steenwijk" }, { "creatorType": "author", "firstName": "P.", "lastName": "Verkroost" } ], "abstractNote": "The current practice in the logistics industry is to calculate the carbon footprint of transportation activities based on the distance covered, using long-term fuel consumption averages per kilometer. However, fuel consumption may actually vary over time, because of differences in road characteristics, traffic situations, driving behavior, etc. Therefore, distance-based emission calculations are not accurate. Our approach is fuel-based and it calculates transport greenhouse gas emissions by obtaining the actual fuel consumption during trips via board computers installed in vehicles. Thus, we propose an architecture for a fuel-based Logistics Carbon Management System (LCMS) that monitors and collects real-time data about the fuel consumption during trips, and, consequently, calculates detailed and accurate carbon footprints of transportation services. Furthermore, this system is integrated with the logistics service provider’s business processes and with typical software applications (e.g., Transport Management Systems and Board Computers). We validate and implement the proposed architecture by means of a prototype.", "publicationTitle": "Information Systems Frontiers", "publisher": "", "place": "", "date": "2013/11/01", "volume": "15", "issue": "5", "section": "", "partNumber": "", "partTitle": "", "pages": "725-745", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Inf Syst Front", "DOI": "10.1007/s10796-013-9416-y", "citationKey": "", "url": "http://link.springer.com/article/10.1007/s10796-013-9416-y", "accessDate": "2014-03-20T21:07:16Z", "PMID": "", "PMCID": "", "ISSN": "1387-3326, 1572-9419", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "link.springer.com", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Architecture", "type": 1 }, { "tag": "Business Information Systems", "type": 1 }, { "tag": "Carbon footprinting", "type": 1 }, { "tag": "Logistics carbon management system", "type": 1 }, { "tag": "Logistics industry", "type": 1 }, { "tag": "Management of Computing and Information Systems", "type": 1 }, { "tag": "Operations Research/Decision Theory", "type": 1 }, { "tag": "Systems Theory, Control", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T21:07:16Z", "dateModified": "2014-03-20T21:07:16Z" } }, { "key": "F43ADUZ6", "version": 5, "library": { "type": "group", "id": 255374, "name": "Eco-routing and adaptive powertrain control in hybrid vehicles", "links": { "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/255374/items/F43ADUZ6", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/eco-routing_and_adaptive_powertrain_control_in_hybrid_vehicles/items/F43ADUZ6", "type": "text/html" } }, "meta": { "createdByUser": { "id": 1261598, "username": "Bibliobomb", "name": "Alex Hernandez", "links": { "alternate": { "href": "https://www.zotero.org/bibliobomb", "type": "text/html" } } }, "creatorSummary": "Vreeswijk et al.", "parsedDate": "2010-09", "numChildren": 0 }, "data": { "key": "F43ADUZ6", "version": 5, "itemType": "conferencePaper", "title": "Energy efficient traffic management and control - the eCoMove approach and expected benefits", "creators": [ { "creatorType": "author", "firstName": "J.D.", "lastName": "Vreeswijk" }, { "creatorType": "author", "firstName": "M. K M", "lastName": "Mahmod" }, { "creatorType": "author", "firstName": "B.", "lastName": "van Arem" } ], "abstractNote": "Transportation is an important contributor to environmental problems like declining air quality. Current traffic measures seek to optimize travel times, but fall short on the ideal of an ecologically friendly traffic system. The European research project eCoMove aims to reduce the overall fuel consumption in traffic by 20 percent by means of energy efficient driving behavior and energy efficient traffic management and control. This paper contributes to the understanding of the feasibility of this goal. Vehicle-to-vehicle and vehicle-to-infrastructure communication is a key element in the vision of eCoMove. In this paper the eCoMove concepts are presented by means of an in-depth look on the eco Adaptive Balancing and Control system. Preliminary studies on rerouting, green priority and speed advice at signalized intersections indicate signification environmental benefits.", "proceedingsTitle": "2010 13th International IEEE Conference on Intelligent Transportation Systems (ITSC)", "conferenceName": "2010 13th International IEEE Conference on Intelligent Transportation Systems (ITSC)", "publisher": "", "place": "", "date": "Sept 2010", "eventPlace": "", "volume": "", "issue": "", "numberOfVolumes": "", "pages": "955-961", "series": "", "seriesNumber": "", "DOI": "10.1109/ITSC.2010.5625122", "ISBN": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "IEEE Xplore", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "Acceleration", "type": 1 }, { "tag": "Biological system modeling", "type": 1 }, { "tag": "Driver circuits", "type": 1 }, { "tag": "Fuels", "type": 1 }, { "tag": "Green products", "type": 1 }, { "tag": "Vehicles", "type": 1 }, { "tag": "air pollution", "type": 1 }, { "tag": "declining air quality", "type": 1 }, { "tag": "eCoMove Approach", "type": 1 }, { "tag": "energy efficient traffic management", "type": 1 }, { "tag": "environmental problems", "type": 1 }, { "tag": "pollution control", "type": 1 }, { "tag": "road vehicles", "type": 1 }, { "tag": "traffic control", "type": 1 }, { "tag": "transportation", "type": 1 }, { "tag": "vehicle-to-infrastructure communication", "type": 1 }, { "tag": "vehicle-to-vehicle communication", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2014-03-20T20:57:30Z", "dateModified": "2014-03-20T20:57:30Z" } } ]