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Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles

Author

Listed:
  • Song, Ziyou
  • Li, Jianqiu
  • Han, Xuebing
  • Xu, Liangfei
  • Lu, Languang
  • Ouyang, Minggao
  • Hofmann, Heath

Abstract

This paper proposes a semi-active battery/supercapacitor (SC) hybrid energy storage system (HESS) for use in electric drive vehicles. A much smaller unidirectional dc/dc converter is adopted in the proposed HESS to integrate the SC and battery, thereby increasing the HESS efficiency and reducing the system cost. We have also included a quantitative battery capacity fade model, in addition to the theoretical HESS model proposed in this paper. For the proposed HESS, we have examined the sizing optimization of the HESS parameters for an electric city bus, including the parallel and series number of the battery cell and the SC module. Considering the constraint of requirement on minimal mileage, the optimization goal is to simultaneously minimize (i) the total cost of the HESS and (ii) the capacity loss of a LiFePO4 battery over a typical China Bus Driving Cycle. The simulation result shows that these two objectives are conflicting, and trades them off using a non-dominated sorting genetic algorithm II. Finally, the Pareto front including optimal HESS parameter groups has been obtained, which indicates that the battery capacity loss can be reduced rapidly when the SC cost increases within the range from 10 to 40 thousand RMB.

Suggested Citation

  • Song, Ziyou & Li, Jianqiu & Han, Xuebing & Xu, Liangfei & Lu, Languang & Ouyang, Minggao & Hofmann, Heath, 2014. "Multi-objective optimization of a semi-active battery/supercapacitor energy storage system for electric vehicles," Applied Energy, Elsevier, vol. 135(C), pages 212-224.
    • Handle: RePEc:eee:appene:v:135:y:2014:i:c:p:212-224
    DOI: 10.1016/j.apenergy.2014.06.087
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    References listed on IDEAS

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    1. Hung, Yi-Hsuan & Wu, Chien-Hsun, 2012. "An integrated optimization approach for a hybrid energy system in electric vehicles," Applied Energy, Elsevier, vol. 98(C), pages 479-490.
    2. Trovão, João P. & Pereirinha, Paulo G. & Jorge, Humberto M. & Antunes, Carlos Henggeler, 2013. "A multi-level energy management system for multi-source electric vehicles – An integrated rule-based meta-heuristic approach," Applied Energy, Elsevier, vol. 105(C), pages 304-318.
    3. He, Hongwen & Xiong, Rui & Zhao, Kai & Liu, Zhentong, 2013. "Energy management strategy research on a hybrid power system by hardware-in-loop experiments," Applied Energy, Elsevier, vol. 112(C), pages 1311-1317.
    4. Xu, Liangfei & Ouyang, Minggao & Li, Jianqiu & Yang, Fuyuan & Lu, Languang & Hua, Jianfeng, 2013. "Optimal sizing of plug-in fuel cell electric vehicles using models of vehicle performance and system cost," Applied Energy, Elsevier, vol. 103(C), pages 477-487.
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