Model predictive control for active vibration suppression of hybrid electric vehicles during mode transition

Abstract

To realize a rapid and comfortable mode transition process from pure electric mode to hybrid mode (E-H), this study proposes an innovative control strategy which combines open-loop control with model predictive control to regulate the E-H process for a P2.5 configuration hybrid electric vehicle. Firstly, a detailed vehicle longitudinal dynamic model is established and the mode transition process is divided into four phases to reveal the control problems. Based on this model, a strategy combining open-loop control with model predictive control is developed. The open-loop control is adopted before the clutch is locked in order to speed up the transition process and limit the vehicle jerk. The model predictive control (MPC) is adopted after the clutch is locked to actively suppress the vibration caused by the abrupt change of clutch torque at the moment of clutch lock-up. Finally, simulation and hardware-in-the-loop test demonstrate that the proposed strategy for mode transition can achieve both switching rapidity and riding comfort. The algorithm robustness is also discussed and the signal transmission delay influence caused by controller area network (CAN) is studied.

Novel Powertrain Vibration Controller With Six Rules-Based Fuzzy Inference for Time-Fluctuated Control Period

“…Earlier research has concentrated on examining the behavior and management of powertrain control systems, which include those powered by HV engines [18]- [22]. The use of real-time predictive controllers has shown potential in mitigating engine delay [18], [19].…”