Estimation of Synchromesh Frictional Torque and Output Torque in a Clutchless Automated Manual Transmission of a Parallel Hybrid Electric Vehicle

This paper studies the estimation of the synchromesh frictional torque and the output torque of the integrated system of an electric motor and a clutchless automated manual transmission (AMT) as part of a two-shaft parallel hybrid electric vehicle powertrain. The case study powertrain is discussed, and the dynamical model of the powertrain from the electric motor to the AMT output shaft, where it is linked to the torque coupler, is developed constituting the basis for the observer design. Given the fact that the aforementioned torques are unknown inputs to the system, they are modeled as state variables of a fictitious unforced linear time-invariant system in order to be aggregated into the systems dynamics. For the augmented system of the actual and fictitious states, a deterministic Luenberger observer and a stochastic Kalman-Bucy filter (KBF) are designed to estimate the synchromesh frictional torque and the output torque of the AMT. The estimation is based on measuring angular velocities of the electric motor and the AMT output shaft, together with the imparted electromagnetic torque of the traction motor on the system. A set of experiments with distinct scenarios is performed to compare the performance of the designed observers and to quantify by how much the KBF can improve the root-mean-square error (RMSE) of the estimation by mitigating the effect of the process and measurement noises. Ultimately, after validation of the designed observers, the estimated value of the synchromesh frictional torque is exploited in a closed-loop feedback configuration in order to track desired trajectories such as step, ramp, and sinusoidal torque commands.