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Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach

Author

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  • Chaofeng Pan

    (Automotive engineering research institute, Jiangsu University, Zhenjiang 212013, China
    College of automotive and traffic engineering, Jiangsu University, Zhenjiang 212013, China)

  • Yanyan Liang

    (College of automotive and traffic engineering, Jiangsu University, Zhenjiang 212013, China)

  • Long Chen

    (Automotive engineering research institute, Jiangsu University, Zhenjiang 212013, China
    College of automotive and traffic engineering, Jiangsu University, Zhenjiang 212013, China)

  • Liao Chen

    (College of automotive and traffic engineering, Jiangsu University, Zhenjiang 212013, China)

Abstract

In this paper, the efficiency characteristics of battery, super capacitor (SC), direct current (DC)-DC converter and electric motor in a hybrid power system of an electric vehicle (EV) are analyzed. In addition, the optimal efficiency model of the hybrid power system is proposed based on the hybrid power system component’s models. A rule-based strategy is then proposed based on the projection partition of composite power system efficiency, so it has strong adaptive adjustment ability. Additionally. the simulation results under the New European Driving Cycle (NEDC) condition show that the efficiency of rule-based strategy is higher than that of single power system. Furthermore, in order to explore the maximum energy-saving potential of hybrid power electric vehicles, a dynamic programming (DP) optimization method is proposed on the basis of the establishment of the whole hybrid power system, which takes into account various energy consumption factors of the whole system. Compared to the battery-only EV based on simulation results, the hybrid power system controlled by rule-based strategy can decrease energy consumption by 13.4% in line with the NEDC condition, while the power-split strategy derived from the DP approach can reduce energy consumption by 17.6%. The results show that compared with rule-based strategy, the optimized DP strategy has higher system efficiency and lower energy consumption.

Suggested Citation

  • Chaofeng Pan & Yanyan Liang & Long Chen & Liao Chen, 2019. "Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach," Energies, MDPI, vol. 12(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:588-:d:205423
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Macdonald Nko & S.P. Daniel Chowdhury & Olawale Popoola, 2019. "Application Assessment of Pumped Storage and Lithium-Ion Batteries on Electricity Supply Grid," Energies, MDPI, vol. 12(15), pages 1-36, July.
    2. Aleš Hace, 2019. "The Advanced Control Approach based on SMC Design for the High-Fidelity Haptic Power Lever of a Small Hybrid Electric Aircraft," Energies, MDPI, vol. 12(15), pages 1-31, August.
    3. Tengda Hu & Yunwu Li & Zhi Zhang & Ying Zhao & Dexiong Liu, 2021. "Energy Management Strategy of Hybrid Energy Storage System Based on Road Slope Information," Energies, MDPI, vol. 14(9), pages 1-18, April.
    4. Pier Giuseppe Anselma, 2021. "Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort," Energies, MDPI, vol. 14(10), pages 1-28, May.
    5. Li, Cheng & Xu, Xiangyang & Zhu, Helong & Gan, Jiongpeng & Chen, Zhige & Tang, Xiaolin, 2024. "Research on car-following control and energy management strategy of hybrid electric vehicles in connected scene," Energy, Elsevier, vol. 293(C).

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