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MPC-based coordinated control for mode transition in power-split hybrid electric vehicles: Dynamic modeling, torque fluctuation suppression, and experiment

  • Qi Yan
  • , Hui Liu
  • , Pu Gao*
  • , Dianzhao Yang
  • , Jiaxin Jiao
  • *此作品的通讯作者
  • Beijing Institute of Technology
  • B&H Unmanned Intelligent System Research Institute

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

Among the various configurations of hybrid electric vehicles (HEVs), power-split HEVs typically achieve superior fuel economy by dynamically coordinating their operational modes to keep the engine operating within its optimal efficiency region across a wide range of driving conditions. However, for power-split HEVs, mode transition causes torque fluctuations and imptacts driving smoothness and drivetrain safety. To address this challenge, we propose a novel dynamic coordinated control strategy (DCCS) that integrates a staged control framework with model predictive control (MPC) to effectively suppress transient disturbances. First, a dynamic model of the power coupling mechanism is established to characterize the transition between electric vehicle (EV) mode and electric variable transmission (EVT) mode. Then, a multi-stage control scheme is designed to segment the engine start-stop process into distinct phases. Next, the MPC algorithm is further employed to formulate jerk minimization as a constrained optimization problem, enabling real-time coordination of motor torques to maintain near-constant output shaft acceleration. Finally, simulation results demonstrate that the proposed method significantly reduces both output torque fluctuations and maximum jerk compared to conventional control strategies. Bench experiments validate a 38.2 % reduction in engine start time with minimized vibration. This study introduces a novel approach to transient control in power-split HEVs, paving the way for significant improvements in vehicle operation smoothness.

源语言英语
期刊论文编号100174
期刊Chinese Journal of Mechanical Engineering (English Edition)
卷39
DOI
出版状态已出版 - 12月 2026
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