Model-predictive control of powershifts of heavy-duty trucks with dual-clutch transmissions

摘要

This paper presents a cascaded control system with a discrete-time model-predictive control (MPC) in the outer loop and a flatness-based 2-DOF controller in the inner loop. Hereby, the outer loop controller provides the trajectories for the inner loop controller. To significantly lower the computational effort of the MPC, Laguerre functions are used to approximate the control input of the MPC. Since the flatness-based inner loop control also needs the time-derivatives of the provided trajectories, it will be shown how those can be directly obtained from the MPC results. Finally, this control system is applied to a test rig with a dual-clutch transmission for heavy-duty trucks to perform powershifts.