MPC-based coordinated control for mode transition in power-split hybrid electric vehicles: Dynamic modeling, torque fluctuation suppression, and experiment
Abstract
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 impacts 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.
Fields of Study & Subjects
Electric and Hybrid Vehicle Technologies
Vehicle Dynamics and Control Systems
Control Systems in Engineering
Publication details
- Journal / source
- Chinese Journal of Mechanical Engineering
- Publisher
- Elsevier BV
- Volume
- 39
- Pages
- 100174–100174
- Publication date
- 5 March 2026
- Language
- EN