Multi-dynamic torque coordination control strategy for a power-split hybrid electric vehicle during mode shift

  • Kun Huang*
  • , Weida Wang
  • , Jiankang Cheng
  • , Chao Yang
  • , Changle Xiang
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Mode shift is a special mechanism for a power-split hybrid electric vehicle (HEV) to realise electrically variable transmission, but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock. Therefore, a smooth transient process, among other concerns, typically associated with this category of vehicles, is of great importance. The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore improve ride comfort. To this end, a dynamic model of the objective power-split HEV is first built. To resolve the contention between vehicle jerk and clutch friction loss, a model predictive control (MPC) combined with control allocation (CA) is then designed for the clutch-engaged phase. To reduce the torque fluctuation caused by the inertia torques of multiple power sources, a dynamic compensation control strategy (DCCS) that coordinates motor–generator torque to compensate for the transition torque is proposed for the brake-disengaged phase. Finally, the proposed control strategy is validated by simulation and bench test, and results show great potential in reducing shift duration, torque variation, vehicle jerk and friction loss (the simulation results show decreases of 22%, 39%, 83% and 53%, and the experimental results show decreases of 21%, 74%, 77%, and 59%, respectively), thereby improving shift quality.

Original languageEnglish
Article number100009
JournalChinese Journal of Mechanical Engineering (English Edition)
DOIs
Publication statusAccepted/In press - 2026
Externally publishedYes

Keywords

  • Control allocation
  • Dynamic compensation control
  • Mode shift
  • Model predictive control
  • Power-split hybrid electric vehicle

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