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Comprehensive comparison between silicon carbide MOSFETs and silicon IGBTs based traction systems for electric vehicles

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  • Ding, Xiaofeng
  • Du, Min
  • Zhou, Tong
  • Guo, Hong
  • Zhang, Chengming

Abstract

In this paper, the performance of both silicon carbide (SiC) MOSFETs and silicon (Si) IGBTs based electric vehicle (EV) traction systems are investigated and compared comprehensively, particularly from the efficiency point of view. Both conduction loss and switching loss of SiC-MOSFETs are analyzed and modeled taking temperature effect into account. Such approach yields a more accurate prediction of SiC losses. The temperature distribution of SiC-Inverter is described by ANSYS finite element analysis (FEA), and compared with Si counterparts. According to the lower losses and higher thermal conductivity, SiC exhibits much lower temperature than Si under the same power rating and cooling condition. Subsequently, this paper goes further by conducting an investigation of the effect of SiC-Inverter on the motor efficiency. Experimental results show that the SiC-based inverter-motor traction system has observably higher efficiency of overall system compared to the Si-based traction system, and first explore that the motor has extremely high efficiency under low speed and light load when it is driven by a SiC-MOSFETs based inverter due to the higher switching speed of SiC MOSFETs. Meanwhile, the experimental results also confirm the losses models of SiC MOSFETs.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:626-634
    DOI: 10.1016/j.apenergy.2016.05.059
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    References listed on IDEAS

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    1. Sujitjorn, S. & Areerak, K. -L., 2004. "Numerical approach to loss minimization in an induction motor," Applied Energy, Elsevier, vol. 79(1), pages 87-96, September.
    2. Xiong, Rui & Sun, Fengchun & Chen, Zheng & He, Hongwen, 2014. "A data-driven multi-scale extended Kalman filtering based parameter and state estimation approach of lithium-ion olymer battery in electric vehicles," Applied Energy, Elsevier, vol. 113(C), pages 463-476.
    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. Soylu, Seref, 2014. "The effects of urban driving conditions on the operating characteristics of conventional and hybrid electric city buses," Applied Energy, Elsevier, vol. 135(C), pages 472-482.
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    Cited by:

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    3. Edemar O. Prado & Pedro C. Bolsi & Hamiltom C. Sartori & José R. Pinheiro, 2022. "An Overview about Si, Superjunction, SiC and GaN Power MOSFET Technologies in Power Electronics Applications," Energies, MDPI, vol. 15(14), pages 1-17, July.
    4. Guo, Qingbo & Zhang, Chengming & Li, Liyi & Gerada, David & Zhang, Jiangpeng & Wang, Mingyi, 2017. "Design and implementation of a loss optimization control for electric vehicle in-wheel permanent-magnet synchronous motor direct drive system," Applied Energy, Elsevier, vol. 204(C), pages 1317-1332.
    5. 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.
    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.
    7. Boud Verbrugge & Haaris Rasool & Mohammed Mahedi Hasan & Sajib Chakraborty & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2022. "Reliability Assessment of SiC-Based Depot Charging Infrastructure with Smart and Bidirectional (V2X) Charging Strategies for Electric Buses," Energies, MDPI, vol. 16(1), pages 1-15, December.
    8. Han, Feng & Guo, Hong & Ding, Xiaofeng, 2021. "Design and optimization of a liquid cooled heat sink for a motor inverter in electric vehicles," Applied Energy, Elsevier, vol. 291(C).
    9. Ding, Xiaofeng & Lu, Peng & Shan, Zhenyu, 2021. "A high-accuracy switching loss model of SiC MOSFETs in a motor drive for electric vehicles," Applied Energy, Elsevier, vol. 291(C).
    10. Guo Hong & Tian Wei & Xiaofeng Ding & Chongwei Duan, 2018. "Multi-Objective Optimal Design of Electro-Hydrostatic Actuator Driving Motors for Low Temperature Rise and High Power Weight Ratio," Energies, MDPI, vol. 11(5), pages 1-21, May.
    11. Xiaofeng Ding & Min Du & Jiawei Cheng & Feida Chen & Suping Ren & Hong Guo, 2017. "Impact of Silicon Carbide Devices on the Dynamic Performance of Permanent Magnet Synchronous Motor Drive Systems for Electric Vehicles," Energies, MDPI, vol. 10(3), pages 1-19, March.
    12. Wang, Hanqing & Gaillard, Arnaud & Hissel, Daniel, 2019. "A review of DC/DC converter-based electrochemical impedance spectroscopy for fuel cell electric vehicles," Renewable Energy, Elsevier, vol. 141(C), pages 124-138.

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