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Optimization of Energy Management Strategy of a PHEV Based on Improved PSO Algorithm and Energy Flow Analysis

Author

Listed:
  • Yong Liu

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

  • Jimin Ni

    (College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou 325035, China)

  • Rong Huang

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

  • Xiuyong Shi

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

  • Zheng Xu

    (SAIC MOTOR R&D Innovation Headquarters, SAIC MOTOR, Shanghai 201804, China)

  • Yanjun Wang

    (SAIC MOTOR R&D Innovation Headquarters, SAIC MOTOR, Shanghai 201804, China)

  • Yuan Lu

    (SAIC MOTOR R&D Innovation Headquarters, SAIC MOTOR, Shanghai 201804, China)

Abstract

Single-gear-ratio plug-in hybrid vehicles (SRPHEVs) are favored by major manufacturers due to their excellent energy-saving potential, simple structure, ease of maintenance and control, great cost-saving potential, and the benefits of vehicle lightweighting. Implementing an energy management strategy (EMS) is the key to realizing the energy-saving potential of PHEVs. In this paper, based on a newly developed coaxial configuration, P1-P3 SRPHEV, with the purpose of reducing PHEV fuel consumption, the advantages of various methods were synthesized. An improved intelligent optimization algorithm, the Particle Swarm Optimization (PSO) algorithm, was used to find the optimal rule-based strategy parameters. The PSO algorithm could be easily adjusted to the parameters and obtains the desired results quickly. Different long-distance speed profiles tested under real-world driving cycle (RDC) conditions were used to validate the fuel savings. And an energy flow analysis was conducted to further investigate the reasons for the algorithm optimization. The results show that the optimization plans of the PSO algorithm in different cycle conditions can improve the equivalent fuel consumption of vehicles in different long-distance conditions. Considering the optimization effect of the equivalent fuel consumption and actual fuel consumption, the best case of the equivalent fuel consumption is improved by 2.98%, and the actual fuel consumption is improved by 2.37%. Through the energy flow analysis, it is found that the energy-saving effect of the optimization plan lies in the following principle: lowering the parallel mode switching threshold to increase the parallel mode usage time and to reduce the fuel–mechanical–electrical transmission path loss, resulting in increasing the energy utilization of the whole vehicle.

Suggested Citation

  • Yong Liu & Jimin Ni & Rong Huang & Xiuyong Shi & Zheng Xu & Yanjun Wang & Yuan Lu, 2024. "Optimization of Energy Management Strategy of a PHEV Based on Improved PSO Algorithm and Energy Flow Analysis," Sustainability, MDPI, vol. 16(20), pages 1-27, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:9017-:d:1501352
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    References listed on IDEAS

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