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Map-Based Power-Split Strategy Design with Predictive Performance Optimization for Parallel Hybrid Electric Vehicles

Author

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  • Jixiang Fan

    (Department of Engineering and Applied Science, Sophia University, Tokyo 102-8554, Japan
    Department of Electronic Engineering, Harbin Normal University, Harbin 150025, China)

  • Jiangyan Zhang

    (Department of Engineering and Applied Science, Sophia University, Tokyo 102-8554, Japan
    College of Electromechanical & Information Engineering, Dalian Nationalities University, Dalian 116600, China)

  • Tielong Shen

    (Department of Electronic Engineering, Harbin Normal University, Harbin 150025, China)

Abstract

In this paper, a map-based optimal energy management strategy is proposed to improve the consumption economy of a plug-in parallel hybrid electric vehicle. In the design of the maps, which provide both the torque split between engine and motor and the gear shift, not only the current vehicle speed and power demand, but also the optimality based on the predicted trajectory of vehicle dynamics are considered. To seek the optimality, the equivalent consumption, which trades off the fuel and electricity usages, is chosen as the cost function. Moreover, in order to decrease the model errors in the process of optimization conducted in the discrete time domain, the variational integrator is employed to calculate the evolution of the vehicle dynamics. To evaluate the proposed energy management strategy, the simulation results performed on a professional GT-Suit simulator are demonstrated and the comparison to a real-time optimization method is also given to show the advantage of the proposed off-line optimization approach.

Suggested Citation

  • Jixiang Fan & Jiangyan Zhang & Tielong Shen, 2015. "Map-Based Power-Split Strategy Design with Predictive Performance Optimization for Parallel Hybrid Electric Vehicles," Energies, MDPI, vol. 8(9), pages 1-23, September.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:9:p:9946-9968:d:55726
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    References listed on IDEAS

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    1. Hou, Cong & Ouyang, Minggao & Xu, Liangfei & Wang, Hewu, 2014. "Approximate Pontryagin’s minimum principle applied to the energy management of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 115(C), pages 174-189.
    2. Abdelsalam Ahmed Abdelsalam & Shumei Cui, 2012. "A Fuzzy Logic Global Power Management Strategy for Hybrid Electric Vehicles Based on a Permanent Magnet Electric Variable Transmission," Energies, MDPI, vol. 5(4), pages 1-24, April.
    3. Tobias Nüesch & Philipp Elbert & Michael Flankl & Christopher Onder & Lino Guzzella, 2014. "Convex Optimization for the Energy Management of Hybrid Electric Vehicles Considering Engine Start and Gearshift Costs," Energies, MDPI, vol. 7(2), pages 1-23, February.
    4. Trovão, João P. & Pereirinha, Paulo G. & Jorge, Humberto M. & Antunes, Carlos Henggeler, 2013. "A multi-level energy management system for multi-source electric vehicles – An integrated rule-based meta-heuristic approach," Applied Energy, Elsevier, vol. 105(C), pages 304-318.
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    Citations

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    Cited by:

    1. Saiteja, Pemmareddy & Ashok, B., 2022. "Critical review on structural architecture, energy control strategies and development process towards optimal energy management in hybrid vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    2. Ali Solouk & Mahdi Shahbakhti, 2016. "Energy Optimization and Fuel Economy Investigation of a Series Hybrid Electric Vehicle Integrated with Diesel/RCCI Engines," Energies, MDPI, vol. 9(12), pages 1-23, December.
    3. Chien-Hsun Wu & Yong-Xiang Xu, 2019. "The Optimal Control of Fuel Consumption for a Heavy-Duty Motorcycle with Three Power Sources Using Hardware-in-the-Loop Simulation," Energies, MDPI, vol. 13(1), pages 1-16, December.
    4. Andrea Bonfiglio & Damiano Lanzarotto & Mario Marchesoni & Massimiliano Passalacqua & Renato Procopio & Matteo Repetto, 2017. "Electrical-Loss Analysis of Power-Split Hybrid Electric Vehicles," Energies, MDPI, vol. 10(12), pages 1-17, December.
    5. Di Guo & Changqing Du & Fuwu Yan, 2016. "Drivability-Related Discrete-Time Model Predictive Control of Mode Transition in Pre-Transmission Parallel Hybrid Powertrains," Energies, MDPI, vol. 9(9), pages 1-31, September.

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