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A new strategy of efficiency enhancement for traction systems in electric vehicles

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  • Ding, Xiaofeng
  • Guo, Hong
  • Xiong, Rui
  • Chen, Feida
  • Zhang, Donghuai
  • Gerada, Chris

Abstract

The inverter-motor drive system is the main traction force in electric vehicles (EVs). The overall efficiency of inverter-motor will directly determine the energy consumption of EVs. In this paper, aiming at improving the overall efficiency of inverter-motor, a novel methodology is proposed. Firstly, the iron loss, copper loss and stray loss of motor, as well as the devices’ conduction loss and switching loss in inverter are modeled. Afterwards, based on previous loss model strategy and gold section search strategy, a novel hybrid efficiency-optimization control strategy is proposed. The proposed method combines each benefit in loss-model and gold section search, and can realize high efficiency operation of the inverter-motor system in large power range. Additionally, the proposed method manifests faster search speed and better accuracy compared to conventional methods. Experiment results validated the effectiveness of the proposed hybrid control strategy. Meanwhile, the impact of the efficiency improvement on the driving cycle is further investigated through Advanced Vehicle Simulator (ADVISOR) simulations.

Suggested Citation

  • Ding, Xiaofeng & Guo, Hong & Xiong, Rui & Chen, Feida & Zhang, Donghuai & Gerada, Chris, 2017. "A new strategy of efficiency enhancement for traction systems in electric vehicles," Applied Energy, Elsevier, vol. 205(C), pages 880-891.
    • Handle: RePEc:eee:appene:v:205:y:2017:i:c:p:880-891
    DOI: 10.1016/j.apenergy.2017.08.051
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    References listed on IDEAS

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    1. Wang, Chun & Xiong, Rui & He, Hongwen & Ding, Xiaofeng & Shen, Weixiang, 2016. "Efficiency analysis of a bidirectional DC/DC converter in a hybrid energy storage system for plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 183(C), pages 612-622.
    2. Ding, Xiaofeng & Du, Min & Zhou, Tong & Guo, Hong & Zhang, Chengming, 2017. "Comprehensive comparison between silicon carbide MOSFETs and silicon IGBTs based traction systems for electric vehicles," Applied Energy, Elsevier, vol. 194(C), pages 626-634.
    3. Li, Yunhua & Liu, Mingsheng & Lau, Josephine & Zhang, Bei, 2015. "A novel method to determine the motor efficiency under variable speed operations and partial load conditions," Applied Energy, Elsevier, vol. 144(C), pages 234-240.
    4. Sun, Fengchun & Xiong, Rui & He, Hongwen, 2016. "A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique," Applied Energy, Elsevier, vol. 162(C), pages 1399-1409.
    5. Xiong, Rui & Yu, Quanqing & Wang, Le Yi & Lin, Cheng, 2017. "A novel method to obtain the open circuit voltage for the state of charge of lithium ion batteries in electric vehicles by using H infinity filter," Applied Energy, Elsevier, vol. 207(C), pages 346-353.
    6. Ding, Xiaofeng & Chen, Feida & Du, Min & Guo, Hong & Ren, Suping, 2017. "Effects of silicon carbide MOSFETs on the efficiency and power quality of a microgrid-connected inverter," Applied Energy, Elsevier, vol. 201(C), pages 270-283.
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    Cited by:

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    6. Trancho, E. & Ibarra, E. & Arias, A. & Kortabarria, I. & Prieto, P. & Martínez de Alegría, I. & Andreu, J. & López, I., 2018. "Sensorless control strategy for light-duty EVs and efficiency loss evaluation of high frequency injection under standardized urban driving cycles," Applied Energy, Elsevier, vol. 224(C), pages 647-658.
    7. Hung, Nguyen Ba & Sung, Jaewon & Lim, Ocktaeck, 2018. "A simulation and experimental study of operating performance of an electric bicycle integrated with a semi-automatic transmission," Applied Energy, Elsevier, vol. 221(C), pages 319-333.
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