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Drivability-Related Discrete-Time Model Predictive Control of Mode Transition in Pre-Transmission Parallel Hybrid Powertrains

Author

Listed:
  • Di Guo

    (School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China)

  • Changqing Du

    (School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China
    Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, China)

  • Fuwu Yan

    (School of Automotive Engineering, Wuhan University of Technology, Wuhan 430070, China
    Hubei Key Laboratory of Advanced Technology for Automotive Components, Wuhan University of Technology, Wuhan 430070, China
    Hubei Collaborative Innovation Center for Automotive Components Technology, Wuhan University of Technology, Wuhan 430070, China)

Abstract

During the mode transition from the pure electric propulsion mode to the hybrid propulsion mode, clutch-based pre-transmission parallel hybrid electric vehicles are subject to drivability issues. These issues originate from the fact that in the clutch-based pre-transmission parallel hybrid powertrain (CPPHP) configuration, the clutch connects the engine and the motor. Without a carefully designed mode transition control that coordinates the engine torque, clutch torque and motor torque, torque sluggishness and surges occur during the mode transition, and residual torque oscillation occurs after the mode transition. In this paper, a discrete-time model predictive control (DMPC)-based controller is proposed to address these drivability-related issues. Modeling improvements and novel drivability-related indices and constraints are all taken into consideration in the design of the discrete-time model predictive controller. Furthermore, by using discrete-time Laguerre functions and introducing the equilibrium state and the ranking of constraints, an explicit solution of the discrete-time model predictive controller is obtained. The calculation results demonstrate that the proposed controller can ensure a smooth and rapidly decaying torque difference during the mode transition, alleviating the residual torque oscillation after the mode transition and guaranteeing that the mode transition is completed within an acceptable duration.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:9:p:740-:d:78054
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Kyuhyun Sim & Sang-Min Oh & Ku-Young Kang & Sung-Ho Hwang, 2017. "A Control Strategy for Mode Transition with Gear Shifting in a Plug-In Hybrid Electric Vehicle," Energies, MDPI, vol. 10(7), pages 1-15, July.
    2. Zhao, Chen & Zu, Bingfeng & Xu, Yuliang & Wang, Zhen & Zhou, Jianwei & Liu, Lina, 2020. "Design and analysis of an engine-start control strategy for a single-shaft parallel hybrid electric vehicle," Energy, Elsevier, vol. 202(C).

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