부산대학교 도서관

The clutch engagement control is a main factor which influences the power interruption time and shock during mode transformation of hybrid electric vehicles. The key is how to be adaptive to the abrasion in the course of usage and change of working condition. For this purpose,an online adaptive optimal control method based on data-driven and torque estimation is presented. The clutch model is updated online by Artificial Neural Network and clutch torque is estimated by Kalman Filtering in real time to solve clutch parametric dynamic uncertainty. Then an object function is formulated to reduce impact and shorten engagement time integrally,combined with a combination optimization algorithm to obtain the optimal outlet valve duty ratio sequence and optimal engagement time. Meanwhile,clutch speed synchronization is accomplished by engine target speed trajectory tracking control. Test results show that the proposed method can be applied on-board in real time and can restrain impact and decrease engagement time effectively in comparison to other control methods.