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A novel approach for electric powertrain optimization considering vehicle power performance, energy consumption and ride comfort

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  • Lei, Fei
  • Bai, Yingchun
  • Zhu, Wenhao
  • Liu, Jinhong

Abstract

This paper discussed the approach for designing an electric powertrain in saving energy while maintaining vehicle power performance and ride comfort. Usually, energy consumption can be improved by motor efficiency optimization. As an innovative layout, electric vehicle with in-wheel motor may suffer additional vibration due to the increase of unsprung weight. Thus, vehicle ride comfort, together with power performance and energy consumption, are considered in the powertrain design. The work is done on two levels. First, requirements for power performance, energy consumption and ride comfort are generated on the vehicle level. Second, the generated requirements are applied onto the in-wheel motor system, which is described by the motor torque, efficiency and weight models. Torque outputs, motor efficiency and lightweight are the corresponding requirements on the subsystem level. Then multi-objective global optimization is carried out on the subsystem level. The Pareto front indicates that lightweight and high efficiency are two conflicting objectives that cannot be compromised on the subsystem level. A constrained energy approach is proposed to determining the final optimal on the vehicle level with the goal of improving vehicle performance and energy consumption. The final solution has a lightweight ratio of 93.5% and motor efficiency of 92%.

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  • Lei, Fei & Bai, Yingchun & Zhu, Wenhao & Liu, Jinhong, 2019. "A novel approach for electric powertrain optimization considering vehicle power performance, energy consumption and ride comfort," Energy, Elsevier, vol. 167(C), pages 1040-1050.
    • Handle: RePEc:eee:energy:v:167:y:2019:i:c:p:1040-1050
    DOI: 10.1016/j.energy.2018.11.052
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    References listed on IDEAS

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    1. Song, Ziyou & Hofmann, Heath & Li, Jianqiu & Han, Xuebing & Ouyang, Minggao, 2015. "Optimization for a hybrid energy storage system in electric vehicles using dynamic programing approach," Applied Energy, Elsevier, vol. 139(C), pages 151-162.
    2. 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.
    3. Zhang, Shuo & Xiong, Rui & Zhang, Chengning & Sun, Fengchun, 2016. "An optimal structure selection and parameter design approach for a dual-motor-driven system used in an electric bus," Energy, Elsevier, vol. 96(C), pages 437-448.
    4. Sakthivel, V.P. & Subramanian, S., 2011. "On-site efficiency evaluation of three-phase induction motor based on particle swarm optimization," Energy, Elsevier, vol. 36(3), pages 1713-1720.
    5. Xu, Liangfei & Mueller, Clemens David & Li, Jianqiu & Ouyang, Minggao & Hu, Zunyan, 2015. "Multi-objective component sizing based on optimal energy management strategy of fuel cell electric vehicles," Applied Energy, Elsevier, vol. 157(C), pages 664-674.
    6. Xu, Liangfei & Ouyang, Minggao & Li, Jianqiu & Yang, Fuyuan & Lu, Languang & Hua, Jianfeng, 2013. "Optimal sizing of plug-in fuel cell electric vehicles using models of vehicle performance and system cost," Applied Energy, Elsevier, vol. 103(C), pages 477-487.
    7. Lei, Fei & Gu, Ke & Du, Bin & Xie, Xiaoping, 2017. "Comprehensive global optimization of an implicit constrained multi-physics system for electric vehicles with in-wheel motors," Energy, Elsevier, vol. 139(C), pages 523-534.
    8. Rambaldi, Lorenzo & Bocci, Enrico & Orecchini, Fabio, 2011. "Preliminary experimental evaluation of a four wheel motors, batteries plus ultracapacitors and series hybrid powertrain," Applied Energy, Elsevier, vol. 88(2), pages 442-448, February.
    9. Hung, Yi-Hsuan & Wu, Chien-Hsun, 2015. "A combined optimal sizing and energy management approach for hybrid in-wheel motors of EVs," Applied Energy, Elsevier, vol. 139(C), pages 260-271.
    10. Lei, Fei & Du, Bin & Liu, Xin & Xie, Xiaoping & Chai, Tian, 2016. "Optimization of an implicit constrained multi-physics system for motor wheels of electric vehicle," Energy, Elsevier, vol. 113(C), pages 980-990.
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    9. Ma, Fangwu & Yang, Yu & Wang, Jiawei & Liu, Zhenze & Li, Jinhang & Nie, Jiahong & Shen, Yucheng & Wu, Liang, 2019. "Predictive energy-saving optimization based on nonlinear model predictive control for cooperative connected vehicles platoon with V2V communication," Energy, Elsevier, vol. 189(C).
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