Estimating the clutch transmitting torque during HEV mode-switch based on the Kalman filter

A power train dynamics model of a coaxial parallel hybrid electric vehicle (HEV) was built for different clutch operating states. With the state vector constituted by the motor rotation speed and the clutch transmitting torque at two successive time steps, a discrete state space model for estimating the clutch transmitting torque was built, and the Kalman filtering algorithm was used to estimate the clutch transmitting torque. The Matlab/Simulink was employed to simulate the clutch transmitting torque for two mode-switch processes. Estimation errors were analyzed through comparing the estimated and simulated values of the clutch torque. Impact of the noise covariance and the sample time on clutch torque estimation errors were explored. The results show that the developed estimation method can be used to estimate the clutch transmitting torque for HEV with good accuracy. The results are useful for torque direct control of automatic diaphragm clutches.