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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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    12. Yin Hua & Min Xu & Mian Li & Chengbin Ma & Chen Zhao, 2015. "Estimation of State of Charge for Two Types of Lithium-Ion Batteries by Nonlinear Predictive Filter for Electric Vehicles," Energies, MDPI, vol. 8(5), pages 1-22, April.
    13. Di Santo, Katia Gregio & Kanashiro, Eduardo & Di Santo, Silvio Giuseppe & Saidel, Marco Antonio, 2015. "A review on smart grids and experiences in Brazil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1072-1082.
    14. Hu, Xiao & Wang, Ping & Hu, Yunfeng & Chen, Hong, 2020. "A stability-guaranteed and energy-conserving torque distribution strategy for electric vehicles under extreme conditions," Applied Energy, Elsevier, vol. 259(C).
    15. 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.
    16. 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.
    17. 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).
    18. Farzaneh, Alireza & Farjah, Ebrahim, 2018. "Analysis of Road Curvature’s Effects on Electric Motorcycle Energy Consumption," Energy, Elsevier, vol. 151(C), pages 160-166.
    19. Wu, Fuliang & Bektaş, Tolga & Dong, Ming & Ye, Hongbo & Zhang, Dali, 2021. "Optimal driving for vehicle fuel economy under traffic speed uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 175-206.

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