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Wound field synchronous motor with hybrid circuit for neighborhood electric vehicle traction improving fuel economy

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  • Cha, Kyoung-Soo
  • Kim, Dong-Min
  • Jung, Young-Hoon
  • Lim, Myung-Seop

Abstract

Increasing the low mileage associated with electric vehicles is a major requirement. Improving the efficiency of the traction motor is one solution to solve the mileage problem. In this study, we propose a method to improve the efficiency of a wound field synchronous motor (as the traction motor) in case of neighborhood electric vehicles. The wound field synchronous motor is a salient pole machine that generates a negative reluctance torque when operating in the second quadrant, reducing its efficiency. However, second quadrant operation is inevitable due to voltage limitation in the high-speed range. Here, we propose a hybrid circuit comprising U, V, W windings and X, Y, Z windings. The high-speed efficiency of the wound field synchronous motor is improved by changing the connection between the windings. Further, a neighborhood electric vehicle with a wound field synchronous motor was simulated using an advanced vehicle simulator (ADVISOR) to verify the proposal. The hybrid circuit increased the fuel economy of the electric vehicle by up to 3.8%. Finally, a validation experiment was conducted using a fabricated motor prototype.

Suggested Citation

  • Cha, Kyoung-Soo & Kim, Dong-Min & Jung, Young-Hoon & Lim, Myung-Seop, 2020. "Wound field synchronous motor with hybrid circuit for neighborhood electric vehicle traction improving fuel economy," Applied Energy, Elsevier, vol. 263(C).
  • Handle: RePEc:eee:appene:v:263:y:2020:i:c:s0306261920301306
    DOI: 10.1016/j.apenergy.2020.114618
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    References listed on IDEAS

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    1. Riba, Jordi-Roger & López-Torres, Carlos & Romeral, Luís & Garcia, Antoni, 2016. "Rare-earth-free propulsion motors for electric vehicles: A technology review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 367-379.
    2. Taljegard, M. & Göransson, L. & Odenberger, M. & Johnsson, F., 2019. "Impacts of electric vehicles on the electricity generation portfolio – A Scandinavian-German case study," Applied Energy, Elsevier, vol. 235(C), pages 1637-1650.
    3. Hou, Jun & Song, Ziyou, 2020. "A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity," Applied Energy, Elsevier, vol. 257(C).
    4. Klein, M. & Tong, S. & Park, J.W., 2016. "In-plane nonuniform temperature effects on the performance of a large-format lithium-ion pouch cell," Applied Energy, Elsevier, vol. 165(C), pages 639-647.
    5. Wang, Sinan & Chen, Kangda & Zhao, Fuquan & Hao, Han, 2019. "Technology pathways for complying with Corporate Average Fuel Consumption regulations up to 2030: A case study of China," Applied Energy, Elsevier, vol. 241(C), pages 257-277.
    6. Zhao, Mingjie & Shi, Junhui & Lin, Cheng, 2019. "Optimization of integrated energy management for a dual-motor coaxial coupling propulsion electric city bus," Applied Energy, Elsevier, vol. 243(C), pages 21-34.
    7. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
    8. 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.
    9. 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.
    10. Qu, Xiaobo & Yu, Yang & Zhou, Mofan & Lin, Chin-Teng & Wang, Xiangyu, 2020. "Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach," Applied Energy, Elsevier, vol. 257(C).
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    Cited by:

    1. Kwon, Kihan & Lee, Jung-Hwan & Lim, Sang-Kil, 2023. "Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis," Applied Energy, Elsevier, vol. 342(C).
    2. Eckert, Jony Javorski & Silva, Fabrício L. & da Silva, Samuel Filgueira & Bueno, André Valente & de Oliveira, Mona Lisa Moura & Silva, Ludmila C.A., 2022. "Optimal design and power management control of hybrid biofuel–electric powertrain," Applied Energy, Elsevier, vol. 325(C).
    3. Selvin Raj, Jaya Antony Perinba & Asirvatham, Lazarus Godson & Angeline, Appadurai Anitha & Manova, Stephen & Rakshith, Bairi Levi & Bose, Jefferson Raja & Mahian, Omid & Wongwises, Somchai, 2024. "Thermal management strategies and power ratings of electric vehicle motors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

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