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Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking

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  • Li, Liang
  • Li, Xujian
  • Wang, Xiangyu
  • Song, Jian
  • He, Kai
  • Li, Chenfeng

Abstract

Downshift during regenerative braking helps to improve the energy efficiency of electric vehicles. Two main problems are involved in the downshift process. One is the determination of optimal downshift point, and the other is the cooperative control of regenerative braking and hydraulic braking. In order to achieve a systemic solution to these problems, a hierarchical control strategy is brought forward for an electric vehicle with a two-speed automated mechanical transmission. For the upper controller, an off-line calculation and on-line look-up table method is adopted to obtain the optimal downshift point, and a series regenerative braking distribution strategy is designed. For the medium controller, a nonlinear sliding mode observer is designed to obtain the actual hydraulic brake torque. For the lower controller, cooperative control of regenerative braking and hydraulic braking is given to ensure brake safety during downshift process, and a resembling pulse width modulation method is proposed to regulated the hydraulic brake torque. Simulation results and hardware-in-loop test show that the proposed algorithm is effective in improving the energy efficiency of electric vehicles.

Suggested Citation

  • Li, Liang & Li, Xujian & Wang, Xiangyu & Song, Jian & He, Kai & Li, Chenfeng, 2016. "Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking," Applied Energy, Elsevier, vol. 176(C), pages 125-137.
    • Handle: RePEc:eee:appene:v:176:y:2016:i:c:p:125-137
    DOI: 10.1016/j.apenergy.2016.05.042
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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. 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. 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.
    4. Hu, Xiaosong & Johannesson, Lars & Murgovski, Nikolce & Egardt, Bo, 2015. "Longevity-conscious dimensioning and power management of the hybrid energy storage system in a fuel cell hybrid electric bus," Applied Energy, Elsevier, vol. 137(C), pages 913-924.
    5. Yang, Yalian & Hu, Xiaosong & Pei, Huanxin & Peng, Zhiyuan, 2016. "Comparison of power-split and parallel hybrid powertrain architectures with a single electric machine: Dynamic programming approach," Applied Energy, Elsevier, vol. 168(C), pages 683-690.
    6. Ruan, Jiageng & Walker, Paul & Zhang, Nong, 2016. "A comparative study energy consumption and costs of battery electric vehicle transmissions," Applied Energy, Elsevier, vol. 165(C), pages 119-134.
    7. Li, Liang & You, Sixiong & Yang, Chao & Yan, Bingjie & Song, Jian & Chen, Zheng, 2016. "Driving-behavior-aware stochastic model predictive control for plug-in hybrid electric buses," Applied Energy, Elsevier, vol. 162(C), pages 868-879.
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