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Threshold-changing control strategy for series hybrid electric vehicles

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  • Shabbir, Wassif
  • Evangelou, Simos A.

Abstract

This paper proposes a new set of design principles to classify and design rule-based control strategies for the powertrain energy management of series hybrid electric vehicles. The design principles proposed consider the two most established rule-based control strategies for series hybrid electric vehicles, the Thermostat and the Power follower control strategies, and also an optimization-based control strategy, the Equivalent consumption minimization strategy, in terms of the mechanisms they employ to ensure charge sustaining operation and fuel efficient driving. Thus, the work then reflects upon the most effective design principles and derives a novel and superior rule-based control strategy for series hybrid electric vehicles that is claimed to outperform all the existing rule-based schemes in terms of fuel economy: the optimal primary source strategy (OPSS). The OPSS is implemented and then compared on a high fidelity hybrid electric vehicle model to Thermostat, Power follower and Equivalent consumption minimization strategies, as well as to a recently developed rule-based control strategy, the Exclusive operation strategy. As compared to conventional rule-based control strategies, the OPSS is found to deliver significantly improved fuel economy and which is remarkably close to that achieved by the optimization-based Equivalent consumption minimization strategy, while the design of the OPSS is simple and robust as compared to optimization-based strategies. The impressive performance is partly attributed to the recent improvements in engine start stop system technology. It is also shown that the battery is operated in a more steady manner, with a lower depth of discharge, consequently reducing battery degradation.

Suggested Citation

  • Shabbir, Wassif & Evangelou, Simos A., 2019. "Threshold-changing control strategy for series hybrid electric vehicles," Applied Energy, Elsevier, vol. 235(C), pages 761-775.
    • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:761-775
    DOI: 10.1016/j.apenergy.2018.11.003
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    References listed on IDEAS

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    14. Caiyang Wei & Theo Hofman & Esin Ilhan Caarls & Rokus van Iperen, 2020. "A Review of the Integrated Design and Control of Electrified Vehicles," Energies, MDPI, vol. 13(20), pages 1-31, October.
    15. Alkhulaifi, Yousif M. & Qasem, Naef A.A. & Zubair, Syed M., 2022. "Exergoeconomic assessment of the ejector-based battery thermal management system for electric and hybrid-electric vehicles," Energy, Elsevier, vol. 245(C).
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    17. Lin, Xinyou & Huang, Hao & Xu, Xinhao & Xie, Liping, 2024. "Dynamic programming solutions extracted SOC-trajectory online learning generation algorithm based approximate global optimization control strategy for a fuel cell hybrid electric vehicle," Energy, Elsevier, vol. 295(C).
    18. Dong, Peng & Zhao, Junwei & Liu, Xuewu & Wu, Jian & Xu, Xiangyang & Liu, Yanfang & Wang, Shuhan & Guo, Wei, 2022. "Practical application of energy management strategy for hybrid electric vehicles based on intelligent and connected technologies: Development stages, challenges, and future trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    19. Navid Balazadeh Meresht & Sina Moghadasi & Sandeep Munshi & Mahdi Shahbakhti & Gordon McTaggart-Cowan, 2023. "Advances in Vehicle and Powertrain Efficiency of Long-Haul Commercial Vehicles: A Review," Energies, MDPI, vol. 16(19), pages 1-37, September.
    20. Fei, Mingda & Zhang, Zhenyu & Zhao, Wenbo & Zhang, Peng & Xing, Zhaolin, 2024. "Optimal power distribution control in modular power architecture using hydraulic free piston engines," Applied Energy, Elsevier, vol. 358(C).
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    22. Lan, Song & Stobart, Richard & Wang, Xiaonan, 2022. "Matching and optimization for a thermoelectric generator applied in an extended-range electric vehicle for waste heat recovery," Applied Energy, Elsevier, vol. 313(C).

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