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Optimization of electromagnetic vibration for integrated electric drive systems based on electric vehicle driving cycle considering energy consumption

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  • Sun, Zhicheng
  • Hu, Jianjun
  • Yao, Zutang
  • Xue, Shouzhi

Abstract

To reduce the vibration of the integrated electric drive system (IEDS) in actual operation condition and enhance vehicle comfort, the method is proposed to characterize the working characteristics of the IEDS in the electric vehicle driving cycle (EVDC) that can reflect the daily travel conditions of electric vehicles by using representative points. Then, based on the representative points, the multi-objective optimization method was proposed to optimize the electromagnetic force harmonics and motor loss of the electric drive system under complex operating conditions. This method utilizes particle swarm optimization algorithm to obtain the Pareto solution set of the optimization objectives, and uses weighted sum method (WSM) to determine the best-balanced solution. The optimization results show that the multi-objective optimization method proposed in this paper reduces the electromagnetic harmonic as the optimization objective by more than 13 %. Additionally, it expands the high-efficiency region of the IEDS, reducing the energy consumption of the vehicle by 4.7 % in the EVDC, thereby decreasing vehicle energy consumption and improving vehicle comfort.

Suggested Citation

  • Sun, Zhicheng & Hu, Jianjun & Yao, Zutang & Xue, Shouzhi, 2024. "Optimization of electromagnetic vibration for integrated electric drive systems based on electric vehicle driving cycle considering energy consumption," Energy, Elsevier, vol. 313(C).
  • Handle: RePEc:eee:energy:v:313:y:2024:i:c:s0360544224037964
    DOI: 10.1016/j.energy.2024.134018
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    References listed on IDEAS

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    1. Wei, Dong & He, Hongwen & Cao, Jianfei, 2020. "Hybrid electric vehicle electric motors for optimum energy efficiency: A computationally efficient design," Energy, Elsevier, vol. 203(C).
    2. Yang, Yang & He, Qiang & Fu, Chunyun & Liao, Shuiping & Tan, Peng, 2020. "Efficiency improvement of permanent magnet synchronous motor for electric vehicles," Energy, Elsevier, vol. 213(C).
    3. Li Zhao & Kun Li & Wu Zhao & Han-Chen Ke & Zhen Wang, 2022. "A Sticky Sampling and Markov State Transition Matrix Based Driving Cycle Construction Method for EV," Energies, MDPI, vol. 15(3), pages 1-19, January.
    4. Ye, Yiming & Wang, Hanchen & Xu, Bin & Zhang, Jiangfeng, 2023. "An imitation learning-based energy management strategy for electric vehicles considering battery aging," Energy, Elsevier, vol. 283(C).
    5. Liu, Qin & Zhang, Wencan & Zhang, Zhongbo & Qin, Qichao, 2022. "A drive system global control strategy for electric vehicle based on optimized acceleration curve," Energy, Elsevier, vol. 248(C).
    6. Zhang, Yahui & Wang, Zimeng & Tian, Yang & Wang, Zhong & Kang, Mingxin & Xie, Fangxi & Wen, Guilin, 2024. "Pre-optimization-assisted deep reinforcement learning-based energy management strategy for a series–parallel hybrid electric truck," Energy, Elsevier, vol. 302(C).
    7. Hu, Jianjun & Guo, Qi & Sun, Zhicheng & Yang, Dianzhao, 2023. "Study on low-frequency torsional vibration suppression of integrated electric drive system considering nonlinear factors," Energy, Elsevier, vol. 284(C).
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    1. Liu, Feng & Wang, Xiuhe & Sun, Lingling & Wei, Hongye & Li, Changbin & Ren, Jie, 2025. "Improved 3D hybrid thermal model for global temperature distribution prediction of interior permanent magnet synchronous motor," Energy, Elsevier, vol. 315(C).

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