TCO Improvement of Commercial Electric Vehicles using Battery Sizing and Intelligent Charge Method

被引:0
|
作者
Babin, Anthony [1 ,2 ]
Boscher, David [1 ]
Hamdoun, Zouheir [1 ]
Rizoug, Nassim [2 ]
Mesbahi, Tedjani [2 ]
Larouci, Cherif [2 ]
机构
[1] GRUAU LAVAL, Dept Innovat & Res, St Berthevin, France
[2] ESTACA, ESTACALAB, Laval, PQ, Canada
关键词
Ageing; battery; battery sizing; commercial electric vehicle; intelligent charge; LEP; mission profile; modeling; scheduled charge; TCO;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to democratize electric vehicles, automakers have to give a solution to reduce the total cost of ownership and bring it better than thermal vehicles one. This paper presents results of works on costs improvement of a 3.5t light-duty commercial electric vehicle. TCO (Total Cost of Ownership) were separated into investment costs and operating costs. The batteries of an electric vehicle were the most expensive element of the powertrain, which can represent until 45% of the vehicle price. What's more, contrary to the life of thermal vehicles, electric energy storage systems have a limited life around 5 years, highly dependent on conditions of use. Thus, study of batteries represents a capital step toward TCO improvement. Inspired by literature, battery aging model is proposed and identified by the calendar and cycling aging tests. A global multi-physical model of the battery, including ageing, were identified and incorporated inside the energetic vehicle model. Charging strategies were developed and adapted to operate according to the influence of the conditions of use. These models and strategies are integrated in a software tool. Taking into account the intended use of the vehicle, this tool, first, designates the most suitable battery, solution dimensions, and then, associates the charging strategy- to the requirements of use, in order to ensure the best battery life or the lowest TCO.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Battery technology could fast-charge electric vehicles
    O'Shea, Paul
    Electronic Products (Garden City, New York), 2009, 51 (09):
  • [32] A novel parameter and state-of-charge determining method of lithium ion battery for electric vehicles
    Li, Zhirun
    Xiong, Rui
    Mu, Hao
    He, Hongwen
    Wang, Chun
    APPLIED ENERGY, 2017, 207 : 363 - 371
  • [33] Sizing of hybrid PMSG-PV system for battery charging of electric vehicles
    Singaravel, M. M. Rajan
    Daniel, S. Arul
    FRONTIERS IN ENERGY, 2015, 9 (01) : 68 - 74
  • [34] Sizing of hybrid PMSG-PV system for battery charging of electric vehicles
    M. M. Rajan Singaravel
    S. Arul Daniel
    Frontiers in Energy, 2015, 9 : 68 - 74
  • [35] Sizing of hybrid PMSG-PV system for battery charging of electric vehicles
    M.M.RAJAN SINGARAVEL
    S.ARUL DANIEL
    Frontiers in Energy, 2015, 9 (01) : 68 - 74
  • [36] Stability Improvement in an On-Board Battery Charger for Electric Vehicles
    Jeong, Hae-Gwang
    Lee, Kyo-Beum
    2012 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2012, : 690 - 694
  • [37] Temperature Characteristics Improvement of Power Battery Module for Electric Vehicles
    Wang, Jian
    Wu, Zhengbin
    Deng, Xianquan
    Quan, Songhua
    Yang, Xiaoping
    2013 9TH IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2013, : 335 - 338
  • [38] Study on the combined influence of battery models and sizing strategy for hybrid and battery-based electric vehicles
    Pinto, Claudio
    Barreras, Jorge V.
    de Castro, Ricardo
    Araujo, Rui Esteves
    Schaltz, Erik
    ENERGY, 2017, 137 : 272 - 284
  • [39] Battery Pack Sizing Method - Case Study of an Electric Motorcycle
    LeBel, Felix-A.
    Pelletier, Louis
    Messier, Pascal
    Trovao, Joao Pedro
    2018 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC), 2018,
  • [40] Intelligent Battery-Aware Energy Management System for Electric Vehicles
    Mahmoud, Dina G.
    Elkhouly, Omar A.
    Azzazy, Muhammad
    Alkady, Gehad I.
    Adly, Ihab
    Daoud, Ramez M.
    Amer, Hassanein H.
    ElSayed, Hany
    Guirguis, Mark
    Abdelshafi, Mohamed Gamal
    2019 24TH IEEE INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), 2019, : 1635 - 1638