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Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis

Author

Listed:
  • Boyi Xiao

    (College of Engineering, South China Agricultural University, Guangzhou 510640, China)

  • Huazhong Lu

    (College of Engineering, South China Agricultural University, Guangzhou 510640, China
    Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China)

  • Hailin Wang

    (College of Engineering, South China Agricultural University, Guangzhou 510640, China)

  • Jiageng Ruan

    (University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia)

  • Nong Zhang

    (University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia)

Abstract

A regenerative braking system and hydraulic braking system are used in conjunction in the majority of electric vehicles worldwide. We propose a new regenerative braking distribution strategy that is based on multi-input fuzzy control logic while considering the influences of the battery’s state of charge, the brake strength and the motor speed. To verify the braking performance and recovery economy, this strategy was applied to a battery electric vehicle model and compared with two other improved regenerative braking strategies. The performance simulation was performed using standard driving cycles (NEDC, LA92, and JP1015) and a real-world-based urban cycle in China. The tested braking strategies satisfied the general safety requirements of Europe (as specified in ECE-13H), and the emergency braking scenario and economic potential were tested. The simulation results demonstrated the differences in the braking force distribution performance of these three regenerative braking strategies, the feasibility of the braking methods for the proposed driving cycles and the energy economic potential of the three strategies.

Suggested Citation

  • Boyi Xiao & Huazhong Lu & Hailin Wang & Jiageng Ruan & Nong Zhang, 2017. "Enhanced Regenerative Braking Strategies for Electric Vehicles: Dynamic Performance and Potential Analysis," Energies, MDPI, vol. 10(11), pages 1-19, November.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1875-:d:118994
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    References listed on IDEAS

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    1. Ruan, Jiageng & Walker, Paul D. & Watterson, Peter A. & Zhang, Nong, 2016. "The dynamic performance and economic benefit of a blended braking system in a multi-speed battery electric vehicle," Applied Energy, Elsevier, vol. 183(C), pages 1240-1258.
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    Cited by:

    1. Qi, Chunyang & Song, Chuanxue & Xiao, Feng & Song, Shixin, 2022. "Generalization ability of hybrid electric vehicle energy management strategy based on reinforcement learning method," Energy, Elsevier, vol. 250(C).
    2. Changran He & Guoye Wang & Zhangpeng Gong & Zhichao Xing & Dongxin Xu, 2018. "A Control Algorithm for the Novel Regenerative–Mechanical Coupled Brake System with by-Wire Based on Multidisciplinary Design Optimization for an Electric Vehicle," Energies, MDPI, vol. 11(9), pages 1-18, September.
    3. Carlos Santos-Iglesia & Pablo Fernández-Arias & Álvaro Antón-Sancho & Diego Vergara, 2022. "Energy Consumption of the Urban Transport Fleet in UNESCO World Heritage Sites: A Case Study of Ávila (Spain)," Sustainability, MDPI, vol. 14(9), pages 1-19, May.
    4. Carmen Raga & Andres Barrado & Henry Miniguano & Antonio Lazaro & Isabel Quesada & Alberto Martin-Lozano, 2018. "Analysis and Sizing of Power Distribution Architectures Applied to Fuel Cell Based Vehicles," Energies, MDPI, vol. 11(10), pages 1-30, September.
    5. Xiao, B. & Ruan, J. & Yang, W. & Walker, P.D. & Zhang, N., 2021. "A review of pivotal energy management strategies for extended range electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    6. Emilia M. Szumska & Rafał Jurecki, 2022. "The Analysis of Energy Recovered during the Braking of an Electric Vehicle in Different Driving Conditions," Energies, MDPI, vol. 15(24), pages 1-16, December.
    7. Valery Vodovozov & Zoja Raud & Eduard Petlenkov, 2021. "Review on Braking Energy Management in Electric Vehicles," Energies, MDPI, vol. 14(15), pages 1-26, July.
    8. Cong Geng & Dawen Ning & Linfu Guo & Qicheng Xue & Shujian Mei, 2021. "Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle," Energies, MDPI, vol. 14(8), pages 1-19, April.

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