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Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes

Author

Listed:
  • In-Gyu Jang

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea)

  • Chung-Seong Lee

    (Central R&D Center, Mando Corporation, Seongnam 13486, Korea)

  • Sung-Ho Hwang

    (School of Mechanical Engineering, Sungkyunkwan University, Suwon 16419, Korea)

Abstract

In a battery-electric vehicle, a representative electric vehicle, there is a growing demand for performance and one-charge mileage improvement. As an alternative to such improvements, the capacity of the battery has been increased; however, due to the corresponding increase in the weight of the battery and the limited space in the vehicle, increasing the capacity of the battery also has limitations. Therefore, researches are being actively conducted to improve system operation efficiency to overcome such limitations. This paper proposes a distributing method of the driving forces to a battery-powered electric shuttle bus for last-mile mobility equipped with the decentralized driving system while taking into account voltage changes of the input terminals due to changes in the battery charge. The system operation efficiency changes were compared and evaluated by performing energy consumption analysis using ‘Manhattan Bus Driving Cycle’ at low voltage condition (SOC 20%). Various analyzes were performed and compared, such as the uniform distribution method of driving forces of the front and rear wheels ( Uniform ), the optimization method without considering the input terminal voltage change ( V norm = 90 V), and the optimization method considering the input terminal voltage change ( V dclink ). As a result, it shows that the proposed algorithm can improve 6.0% compared to the conventional uniform driving force distribution method ( Uniform ). Moreover, it shows that the real-time optimization method without considering the input voltage change ( V norm = 90 V) can improve 5.3% compared to the uniform distribution method. The proposed method can obtain an additional 0.7% increase in total cost compared to the existing optimization method, which shows that the vehicle system has cost-effectiveness by reducing the battery capacity required to achieve the same mileage.

Suggested Citation

  • In-Gyu Jang & Chung-Seong Lee & Sung-Ho Hwang, 2021. "Energy Optimization of Electric Vehicles by Distributing Driving Power Considering System State Changes," Energies, MDPI, vol. 14(3), pages 1-18, January.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:3:p:594-:d:486470
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    References listed on IDEAS

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    1. Jürgen Janek & Wolfgang G. Zeier, 2016. "A solid future for battery development," Nature Energy, Nature, vol. 1(9), pages 1-4, September.
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    Cited by:

    1. Francis F. Assadian, 2022. "Advanced Control and Estimation Concepts and New Hardware Topologies for Future Mobility," Energies, MDPI, vol. 15(4), pages 1-3, February.
    2. Changqing Du & Shiyang Huang & Yuyao Jiang & Dongmei Wu & Yang Li, 2022. "Optimization of Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Based on Dynamic Programming," Energies, MDPI, vol. 15(12), pages 1-25, June.

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