Robust pinch estimation and detection algorithm for low-cost anti-pinch window control systems

Abstract

A practical pinch torque estimator based on the Kalman filter is proposed for low-cost anti-pinch window control systems. To obtain the accurate angular velocity from Hall-effect sensor measurements, the angular velocity calculation algorithm is proposed by including the measurement noise reduction logics. Apart from the previous works based on the angular velocity or torque estimates for detecting the pinched condition, the proposed pinch detection algorithm makes use of the torque rate information. To do this, the torque rate is augmented to the system model and the torque rate estimator is derived by applying the steady-state Kalman filter recursion to the model. The motivation of this approach comes from the idea that the torque rate is less sensitive to the motor parameter uncertainties. Hence, the proposed scheme minimizes the anti-pinch window control system's exposure to the false alarm. To detect the pinched condition, a systematic way to determine the threshold level of the torque rate estimates is also suggested via the deterministic estimation error analysis. Experimental results certify the pinch detection performance of the proposed algorithm and its robustness against the motor parameter uncertainties.