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Multi-Objective Energy Management Strategy Based on PSO Optimization for Power-Split Hybrid Electric Vehicles

Author

Listed:
  • Aimin Du

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Yaoyi Chen

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Dongxu Zhang

    (United Auto Electronics Co. LTD, Shanghai 201804, China)

  • Yeyang Han

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

Abstract

The hybrid electric vehicle is equipped with an internal combustion engine and motor as the driving source, which can solve the problems of short driving range and slow charging of the electric vehicle. Making an effective energy management control strategy can reasonably distribute the output power of the engine and motor, improve engine efficiency, and reduce battery damage. To reduce vehicle energy consumption and excessive battery discharge at the same time, a multi-objective energy management strategy based on a particle swarm optimization algorithm is proposed. First, a simulation platform was built based on a compound power-split vehicle model. Then, the ECMS (Equivalent Consumption Minimization Strategy) was used to realize the real-time control of the model, and the penalty function was added to modify the objective function based on the current SOC (State of Charge) to maintain the SOC balance. Finally, the key parameters of ECMS were optimized by using a particle swarm optimization algorithm, and the effectiveness of the control strategy was verified under the WLTC (Worldwide Light-Duty Test Cycle) and the NEDC (New European Driving Cycle). The results show that under the WLTC test cycle, the overall fuel consumption of the whole vehicle was 6.88 L/100 km, which was 7.7% lower than that before optimization; under the NEDC test cycle, the fuel consumption of the whole vehicle was 5.88 L/100 km, which was 9.8% lower than that before optimization.

Suggested Citation

  • Aimin Du & Yaoyi Chen & Dongxu Zhang & Yeyang Han, 2021. "Multi-Objective Energy Management Strategy Based on PSO Optimization for Power-Split Hybrid Electric Vehicles," Energies, MDPI, vol. 14(9), pages 1-18, April.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:9:p:2438-:d:542878
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    References listed on IDEAS

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    1. Hongwei Liu & Chantong Wang & Xin Zhao & Chong Guo, 2018. "An Adaptive-Equivalent Consumption Minimum Strategy for an Extended-Range Electric Bus Based on Target Driving Cycle Generation," Energies, MDPI, vol. 11(7), pages 1-26, July.
    2. Xixue Liu & Datong Qin & Shaoqian Wang, 2019. "Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor," Energies, MDPI, vol. 12(11), pages 1-17, May.
    3. Ximing Wang & Hongwen He & Fengchun Sun & Xiaokun Sun & Henglu Tang, 2013. "Comparative Study on Different Energy Management Strategies for Plug-In Hybrid Electric Vehicles," Energies, MDPI, vol. 6(11), pages 1-20, October.
    4. Yuying Wang & Xiaohong Jiao & Zitao Sun & Ping Li, 2017. "Energy Management Strategy in Consideration of Battery Health for PHEV via Stochastic Control and Particle Swarm Optimization Algorithm," Energies, MDPI, vol. 10(11), pages 1-21, November.
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    Cited by:

    1. Gianluca Brando & Adolfo Dannier & Andrea Del Pizzo, 2022. "Efficiency Analytical Characterization for Brushless Electric Drives," Energies, MDPI, vol. 15(8), pages 1-11, April.

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