2014 IEEE International Electric Vehicle Conference (IEVC)最新文献_第7页

Crowd sourced energy estimation in connected vehicles 联网车辆的众源能源估计

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056189

A. Jayakumar, Fabio Ingrosso, G. Rizzoni, Jason Meyer, Jeffrey Doering

{"title":"Crowd sourced energy estimation in connected vehicles","authors":"A. Jayakumar, Fabio Ingrosso, G. Rizzoni, Jason Meyer, Jeffrey Doering","doi":"10.1109/IEVC.2014.7056189","DOIUrl":"https://doi.org/10.1109/IEVC.2014.7056189","url":null,"abstract":"Accurately forecasting the energy consumption profile of a vehicle is a key requirement of many growing research areas such as horizon based energy management and eco-routing. However, the energy consumption rate of a vehicle depends on many factors making it very difficult to estimate. Many of these factors such as traffic light timing, traffic congestion and weather, change from day to day and trip to trip. While real time traffic information and traffic light timing schedules can be used to help predict the effect of the first two factors, the impact of weather cannot be as easily predicted based on a weather report. Depending on the topology of the route including other vehicles on the road, the local wind speed relative to a vehicle can differ greatly from a predicted bulk wind speed. The effect of precipitation is also difficult to predict because it depends on the amount falling and the amount accumulated on the road. In this paper it is first shown that energy consumption prediction errors due to un-modeled effects, including most notably weather, exhibit a high amount of trip-to-trip variation and a smaller amount of variation within a trip. Next, it is demonstrated that moderate wind speeds have an observable effect on energy consumption and this effect varies based on the direction of travel and wind direction. This analysis also illustrates the challenges in predicting the effect of wind speed and precipitation on energy consumption based on a weather forecast. Finally, a case is made for future research involving the use of current and recent data from a large population of vehicles to provide a more accurate energy consumption profile by reducing the prediction errors due to un-modeled effects.","PeriodicalId":223794,"journal":{"name":"2014 IEEE International Electric Vehicle Conference (IEVC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124879849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Assessment of the impact of Electric vehicles on iberian day-ahead electricity market 电动汽车对伊比利亚日前电力市场的影响评估

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056160

P. Olivella-Rosell, G. Bosch-Llufriu, R. Villafáfila-Robles, D. Heredero-Peris, Mario Kovačević, N. Leemput

引用次数: 1

Finding suitable locations for charging stations 寻找合适的充电站位置

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056134

Matthias Eisel, J. Schmidt, L. Kolbe

引用次数: 17

Integrating the electric grid and the commuter network through a “vehicle to grid” concept: a Complex Networks Theory approach 通过“车辆到电网”的概念整合电网和通勤网络:一种复杂网络理论方法

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056119

A. Chessa, G. Caldarelli, A. Damiano, Antonio Scala

引用次数: 1

A framework for the distributed management of charging operations 收费操作的分布式管理框架

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056131

M. P. Fanti, A. M. Mangini, G. Pedroncelli, W. Ukovich

引用次数: 4

Dead time generator for synchronous boost converters with GaN transistors GaN晶体管同步升压变换器的死区时间发生器

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056113

M. Macellari, F. Celani, L. Schirone

引用次数: 5

Neighborhood level network aware electric vehicle charging management with mixed control strategy 基于混合控制策略的邻域网络感知电动汽车充电管理

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056207

Di Wu, Haibo Zeng, B. Boulet

{"title":"Neighborhood level network aware electric vehicle charging management with mixed control strategy","authors":"Di Wu, Haibo Zeng, B. Boulet","doi":"10.1109/IEVC.2014.7056207","DOIUrl":"https://doi.org/10.1109/IEVC.2014.7056207","url":null,"abstract":"With the fast development of the electric vehicle (EV) technology and the pressing environment conditions. It is expected that EVs will grow rapidly in the near feature. However, the broad adoption of EVs will produce a high power demand on the power grid. Smart charging control of the EVs could help to relieve the possible negative influences on the power grid. Many researchers have investigated possible algorithms for EV charging control. Considering customers' willingness, this paper proposes a mixed charging control framework. The proposed control framework is aimed to minimize the charging cost and satisfy the customers' charging freedom requirements. A user satisfaction determining method is also proposed which can help to evaluate user satisfactions for different control algorithms. Within the proposed framework, both the benefits for the utility companies and the customers are considered. The optimization framework is evaluated with the data from a local utility company. Simulation results show the efficiency of the proposed framework. The framework can also be further used to evaluate the penetration for a certain neighborhood level network.","PeriodicalId":223794,"journal":{"name":"2014 IEEE International Electric Vehicle Conference (IEVC)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115662103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

Motor drive control of a full-electric vehicle using generalized predictive control algorithm 基于广义预测控制算法的全电动汽车电机驱动控制

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056151

A. Kiselev, A. Kuznietsov

引用次数: 5

Fault-tolerant control based on sliding mode for overactuated electric vehicles 基于滑模的过驱动电动汽车容错控制

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056137

A. Lopes, R. Araújo

引用次数: 5

Flexray versus Ethernet for vehicular networks Flexray与以太网的车载网络

2014 IEEE International Electric Vehicle Conference (IEVC) Pub Date : 2014-12-01 DOI: 10.1109/IEVC.2014.7056123

Ben Ncira Amel, Bouhouch Rim, Jaouani Houda, H. Salem, J. Khaled

引用次数: 2