Abbas Soltani - Department of Industrial, Mechanical and Aerospace Engineering, Buein Zahra Technical University, Qazvin, Iran.
Milad Arianfard - Department of Mechanical Engineering, Technical and Vocational University (TVU), Tehran, Iran.

In this study, an adaptive sliding mode controller (ASMC) based on estimation of tire-road friction coefficient is proposed for engagement control of automotive dry clutch. The control of clutch engagement is one of the most important parts of gear-shift process for automated manual transmission. Accurate amount of drive shaft torque in modelling of powertrain system is essential to guarantee smooth engagement of the clutch and rapid response of the control system. As the tire-road friction coefficient has significant influence on drive shaft torque, an estimator is designed to calculate this parameter. The ASMC is proposed for the clutch control to overcome the system uncertainties and a proportional integral (PI) controller is adopted to engine speed control. In addition, a nonlinear estimator utilizing unscented Kalman filter is applied to estimate the state variables that are measured hardly such as wheel slip and longitudinal vehicle velocity. The simulation results demonstrate the high effectiveness of the combined use of presented controller and road friction coefficient estimator for improving the smooth clutch engagement in comparison to the control system without estimator.

Clutch engagement control, Parameter estimation, Road friction coefficient, Adaptive sliding mode control, Unscented Kalman filter