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Optimal energy management strategy for battery powered electric vehicles

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  • Xi, Jiaqi
  • Li, Mian
  • Xu, Min

Abstract

Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios.

Suggested Citation

  • Xi, Jiaqi & Li, Mian & Xu, Min, 2014. "Optimal energy management strategy for battery powered electric vehicles," Applied Energy, Elsevier, vol. 134(C), pages 332-341.
    • Handle: RePEc:eee:appene:v:134:y:2014:i:c:p:332-341
    DOI: 10.1016/j.apenergy.2014.08.033
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    13. Nikita V. Martyushev & Boris V. Malozyomov & Ilham H. Khalikov & Viktor Alekseevich Kukartsev & Vladislav Viktorovich Kukartsev & Vadim Sergeevich Tynchenko & Yadviga Aleksandrovna Tynchenko & Mengxu , 2023. "Review of Methods for Improving the Energy Efficiency of Electrified Ground Transport by Optimizing Battery Consumption," Energies, MDPI, vol. 16(2), pages 1-39, January.
    14. Burgos Payán, Manuel & Roldan Fernandez, Juan Manuel & Maza Ortega, Jose Maria & Riquelme Santos, Jesus Manuel, 2019. "Techno-economic optimal power rating of induction motors," Applied Energy, Elsevier, vol. 240(C), pages 1031-1048.
    15. Wang, L.W. & Jiang, L. & Gao, J. & Gao, P. & Wang, R.Z., 2017. "Analysis of resorption working pairs for air conditioners of electric vehicles," Applied Energy, Elsevier, vol. 207(C), pages 594-603.
    16. Apitzsch, Tilman & Klöffer, Christian & Jochem, Patrick & Doppelbauer, Martin & Fichtner, Wolf, 2016. "Metaheuristics for online drive train efficiency optimization in electric vehicles," Working Paper Series in Production and Energy 17, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).
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