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Optimal battery thermal management for electric vehicles with battery degradation minimization

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  • Wu, Yue
  • Huang, Zhiwu
  • Li, Dongjun
  • Li, Heng
  • Peng, Jun
  • Stroe, Daniel
  • Song, Ziyou

Abstract

The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules ”fast cooling, slow cooling, and temperature-maintaining” from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided.

Suggested Citation

  • Wu, Yue & Huang, Zhiwu & Li, Dongjun & Li, Heng & Peng, Jun & Stroe, Daniel & Song, Ziyou, 2024. "Optimal battery thermal management for electric vehicles with battery degradation minimization," Applied Energy, Elsevier, vol. 353(PA).
    • Handle: RePEc:eee:appene:v:353:y:2024:i:pa:s030626192301454x
    DOI: 10.1016/j.apenergy.2023.122090
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    References listed on IDEAS

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    1. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Hou, Jun & Zhang, Xiaowu & Ouyang, Minggao, 2015. "The optimization of a hybrid energy storage system at subzero temperatures: Energy management strategy design and battery heating requirement analysis," Applied Energy, Elsevier, vol. 159(C), pages 576-588.
    2. 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.
    3. Mali, Vima & Saxena, Rajat & Kumar, Kundan & Kalam, Abul & Tripathi, Brijesh, 2021. "Review on battery thermal management systems for energy-efficient electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. Dai, Haifeng & Jiang, Bo & Hu, Xiaosong & Lin, Xianke & Wei, Xuezhe & Pecht, Michael, 2021. "Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Han, Xuebing & Ouyang, Minggao, 2015. "Optimization for a hybrid energy storage system in electric vehicles using dynamic programing approach," Applied Energy, Elsevier, vol. 139(C), pages 151-162.
    6. Song, Ziyou & Zhang, Xiaobin & Li, Jianqiu & Hofmann, Heath & Ouyang, Minggao & Du, Jiuyu, 2018. "Component sizing optimization of plug-in hybrid electric vehicles with the hybrid energy storage system," Energy, Elsevier, vol. 144(C), pages 393-403.
    7. Zhao, Yihang & Dan, Dan & Zheng, Siyu & Wei, Mingshan & Xie, Yi, 2023. "A two-stage eco-cooling control strategy for electric vehicle thermal management system considering multi-source information fusion," Energy, Elsevier, vol. 267(C).
    8. Akinlabi, A.A. Hakeem & Solyali, Davut, 2020. "Configuration, design, and optimization of air-cooled battery thermal management system for electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).
    9. Wu, Yue & Huang, Zhiwu & Hofmann, Heath & Liu, Yongjie & Huang, Jiahao & Hu, Xiaosong & Peng, Jun & Song, Ziyou, 2022. "Hierarchical predictive control for electric vehicles with hybrid energy storage system under vehicle-following scenarios," Energy, Elsevier, vol. 251(C).
    10. Song, Ziyou & Yang, Niankai & Lin, Xinfan & Pinto Delgado, Fanny & Hofmann, Heath & Sun, Jing, 2022. "Progression of cell-to-cell variation within battery modules under different cooling structures," Applied Energy, Elsevier, vol. 312(C).
    11. Liu, Yongjie & Huang, Zhiwu & Wu, Yue & Yan, Lisen & Jiang, Fu & Peng, Jun, 2022. "An online hybrid estimation method for core temperature of Lithium-ion battery with model noise compensation," Applied Energy, Elsevier, vol. 327(C).
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    1. Luo, Pan & Gao, Kai & Hu, Lin & Chen, Bin & Zhang, Yuanjian, 2024. "Adaptive hybrid cooling strategy to mitigate battery thermal runaway considering natural convection in phase change material," Applied Energy, Elsevier, vol. 361(C).

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