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Improvement of Battery Life and Energy Economy for Electric Vehicles with Two-Speed Transmission

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  • Ying Lyu

    (State Key Laboratory of Automotive Simulation and Control, College of Automotive Engineering, Jilin University, Changchun 130025, China
    State Key Laboratory of Comprehensive Technology on Automobile Vibration and Noise & Safety Control, Changchun 130000, China)

  • Xuenan Sun

    (School of Mathematics and Statistics, Northeast Normal University, Changchun 130024, China)

  • Hong Chu

    (State Key Laboratory of Automotive Simulation and Control, College of Automotive Engineering, Jilin University, Changchun 130025, China)

  • Bingzhao Gao

    (State Key Laboratory of Automotive Simulation and Control, College of Automotive Engineering, Jilin University, Changchun 130025, China)

Abstract

With the current energy environment background and development of the electrification of the automotive industry, a comprehensive economic indicator, in which the battery aging is further considered on the basis of conventional energy consumption, is proposed to research the energy optimization problem of two-speed electric vehicles. Firstly, a battery life model that adapts to vehicles under high dynamic conditions is introduced. Then, the speed optimal control problem of the two-speed electric vehicles in the acceleration–cruise–deceleration process is established and solved. Finally, the simulation results of two different performance indicators are contrasted and the performance improvement of the two-speed gearbox to the electric vehicles is analyzed. The simulation results under various working scenarios and driving cycles demonstrate that, compared with the conventional economic indicator considering the energy consumption only, the proposed economic indicator can significantly improve the battery life. In addition, it can also be seen that, compared with the one-speed electric vehicles, the application of a two-speed gearbox provides better performance from the aspects of battery aging saving and energy consumption.

Suggested Citation

  • Ying Lyu & Xuenan Sun & Hong Chu & Bingzhao Gao, 2020. "Improvement of Battery Life and Energy Economy for Electric Vehicles with Two-Speed Transmission," Energies, MDPI, vol. 13(13), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3409-:d:379450
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    References listed on IDEAS

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    1. Zubi, Ghassan & Dufo-López, Rodolfo & Carvalho, Monica & Pasaoglu, Guzay, 2018. "The lithium-ion battery: State of the art and future perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 292-308.
    2. Björnsson, Lars-Henrik & Karlsson, Sten, 2016. "The potential for brake energy regeneration under Swedish conditions," Applied Energy, Elsevier, vol. 168(C), pages 75-84.
    3. Huiyuan Xiong & Xionglai Zhu & Ronghui Zhang, 2018. "Energy Recovery Strategy Numerical Simulation for Dual Axle Drive Pure Electric Vehicle Based on Motor Loss Model and Big Data Calculation," Complexity, Hindawi, vol. 2018, pages 1-14, August.
    4. Khayyam, Hamid & Bab-Hadiashar, Alireza, 2014. "Adaptive intelligent energy management system of plug-in hybrid electric vehicle," Energy, Elsevier, vol. 69(C), pages 319-335.
    5. Omar, Noshin & Monem, Mohamed Abdel & Firouz, Yousef & Salminen, Justin & Smekens, Jelle & Hegazy, Omar & Gaulous, Hamid & Mulder, Grietus & Van den Bossche, Peter & Coosemans, Thierry & Van Mierlo, J, 2014. "Lithium iron phosphate based battery – Assessment of the aging parameters and development of cycle life model," Applied Energy, Elsevier, vol. 113(C), pages 1575-1585.
    6. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    Full references (including those not matched with items on IDEAS)

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