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Minimum loss modulation method for various power factor angles

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  • Sun, Peng
  • Song, Qiang
  • Wang, Wei

Abstract

In recent years, the energy crisis has prompted widespread attention to electric vehicles (EVs). As a core component of electric drive system in EV, motor controller has a significant impact on vehicle energy consumption. In such situation, this paper proposes a minimum loss modulation method for all power factors and reduces current THD by dead-band compensation. Firstly, the mechanism model of the controller is established for loss calculation, and the relationship between the clamping region and the current peak is analyzed based on the traditional modulation methods. Secondly, a discontinuous pulse width modulation considering power factor angle method (CPFA-DPWM) is proposed to ensure that clamping region always falls at the peak current at all power factors. Furthermore, the adoption of current vector method instead of direct sampling for current polarity determination effectively reduces judgment error and avoids false dead-band compensation. The effectiveness of the proposed method is verified by simulation and thermal measurement experiment. Under China Light-duty Vehicle Test Cycle (CLTC), the controller loss of CPFA-DPWM is reduced by 18.61 % compared to SVPWM.

Suggested Citation

  • Sun, Peng & Song, Qiang & Wang, Wei, 2024. "Minimum loss modulation method for various power factor angles," Energy, Elsevier, vol. 310(C).
    • Handle: RePEc:eee:energy:v:310:y:2024:i:c:s036054422403069x
    DOI: 10.1016/j.energy.2024.133293
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    References listed on IDEAS

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    1. 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).
    2. Hu, Jianjun & Deng, Chenghao & Yang, Dianzhao & Yang, Ying & Jia, Meixia, 2022. "Optimal energy consumption and torque fluctuation control of integrated electric drive system based on mechanical-electromagnetic-thermal coupling characteristics," Energy, Elsevier, vol. 247(C).
    3. 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).
    4. He, Hongwen & Han, Mo & Liu, Wei & Cao, Jianfei & Shi, Man & Zhou, Nana, 2022. "MPC-based longitudinal control strategy considering energy consumption for a dual-motor electric vehicle," Energy, Elsevier, vol. 253(C).
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