Clutch Control Timing Optimization for Adjacent Gearshift Process with Multiple Clutches Based on Adaptive Kriging Surrogate Model

Abstract

Controlling more than two active clutches within one shift event in mass-produced automatic transmission is challenging. Determination of the control timings and the control trajectories for the actively controlled clutches are two essential issues in the gearshift process with multiple clutches. In this study, an efficient multi-objective optimization framework for clutch control timing is established. A multi-objective optimization problem is formulated to determine the optimal clutch control timings by considering the shift jerk, shift duration, and clutch friction work. To mitigate the excessive computation required by the iterative simulation of the physical model in the multi-objective optimization process, we construct a surrogate model to substitute for physical model based on Kriging model and an adaptive sampling method. The efficient surrogate-assisted multi-objective optimization framework based on NSGA-II is proposed. A Pareto set containing various optimal solutions is obtained through the proposed optimization framework. The improved radar method is employed to determine an optimal trade-off solution in the Pareto set. The shift transitions of the optimal trade-off solution are simulated and analyzed. Results validate the effectiveness of the proposed optimization framework in improving shift performance and optimization efficiency.