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Design and Validation of Real-Time Optimal Control with ECMS to Minimize Energy Consumption for Parallel Hybrid Electric Vehicles

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Listed:
  • Aiyun Gao
  • Xiaozhong Deng
  • Mingzhu Zhang
  • Zhumu Fu

Abstract

A real-time optimal control of parallel hybrid electric vehicles (PHEVs) with the equivalent consumption minimization strategy (ECMS) is presented in this paper, whose purpose is to achieve the total equivalent fuel consumption minimization and to maintain the battery state of charge ( ) within its operation range at all times simultaneously. Vehicle and assembly models of PHEVs are established, which provide the foundation for the following calculations. The ECMS is described in detail, in which an instantaneous cost function including the fuel energy and the electrical energy is proposed, whose emphasis is the computation of the equivalent factor. The real-time optimal control strategy is designed through regarding the minimum of the total equivalent fuel consumption as the control objective and the torque split factor as the control variable. The validation of the control strategy proposed is demonstrated both in the MATLAB/Simulink/Advisor environment and under actual transportation conditions by comparing the fuel economy, the charge sustainability, and parts performance with other three control strategies under different driving cycles including standard, actual, and real-time road conditions. Through numerical simulations and real vehicle tests, the accuracy of the approach used for the evaluation of the equivalent factor is confirmed, and the potential of the proposed control strategy in terms of fuel economy and keeping the deviations of at a low level is illustrated.

Suggested Citation

  • Aiyun Gao & Xiaozhong Deng & Mingzhu Zhang & Zhumu Fu, 2017. "Design and Validation of Real-Time Optimal Control with ECMS to Minimize Energy Consumption for Parallel Hybrid Electric Vehicles," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-13, January.
  • Handle: RePEc:hin:jnlmpe:3095347
    DOI: 10.1155/2017/3095347
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    Cited by:

    1. Shailesh Hegde & Angelo Bonfitto & Renato Galluzzi & Luis M. Castellanos Molina & Nicola Amati & Andrea Tonoli, 2023. "Equivalent Consumption Minimization Strategy Based on Belt Drive System Characteristic Maps for P0 Hybrid Electric Vehicles," Energies, MDPI, vol. 16(1), pages 1-21, January.
    2. Vincenzo De Bellis & Marco Piras & Enrica Malfi, 2022. "Assessment of an Adaptive Efficient Thermal/Electric Skipping Control Strategy for the Management of a Parallel Plug-in Hybrid Electric Vehicle," Energies, MDPI, vol. 15(19), pages 1-20, September.
    3. Shantanu Pardhi & Sajib Chakraborty & Dai-Duong Tran & Mohamed El Baghdadi & Steven Wilkins & Omar Hegazy, 2022. "A Review of Fuel Cell Powertrains for Long-Haul Heavy-Duty Vehicles: Technology, Hydrogen, Energy and Thermal Management Solutions," Energies, MDPI, vol. 15(24), pages 1-55, December.
    4. Weiyi Lin & Han Zhao & Bingzhan Zhang & Ye Wang & Yan Xiao & Kang Xu & Rui Zhao, 2022. "Predictive Energy Management Strategy for Range-Extended Electric Vehicles Based on ITS Information and Start–Stop Optimization with Vehicle Velocity Forecast," Energies, MDPI, vol. 15(20), pages 1-27, October.
    5. Penghui Qiang & Peng Wu & Tao Pan & Huaiquan Zang, 2021. "Real-Time Approximate Equivalent Consumption Minimization Strategy Based on the Single-Shaft Parallel Hybrid Powertrain," Energies, MDPI, vol. 14(23), pages 1-22, November.

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