Real-time pinch detection algorithm: Robust to impulsive noise

Abstract

A robust pinch detection algorithm which can be implemented in a cheap microprocessor is proposed for the development of a safety feature in the automotive power window system. To solve the problems caused by the performance degradation of a Hall sensor or real driving situations, the proposed algorithm makes use of the H ∞ state estimation technique. The motivation of this approach comes from the advantage that the H ∞ filter can minimize or bound the worst-case estimation error energy for all bounded energy disturbances. Herein, the pinch torque rate estimator is derived from applying the steady-state H ∞ filter to the augmented model, which includes the motor dynamics and an additional torque rate state. Then, to redesign an appropriate estimator for real-time implementation, the torque rate estimate can be calculated more efficiently than the previous method [1]. Experimental results verify that, with a small amount of computation, the proposed pinch detection algorithm provides fast pinch detection performance superior to the existing method. Furthermore, it guarantees robustness against the worst-case measurement noises.

A New Real-Time Pinch Detection Algorithm Based on Model Reference Kalman Prediction and SRMS for Electric Adjustable Desk

“…From the above Section 3.1 , is selected as the pinch state variable. According to [ 10 , 11 ], it is reasonable to augment the torque as an additional state and modeled by a random walk using the zero-mean white noise with the variance as follows: …”

“…Many researchers have conducted intensive research on anti-pinch detection. In pinch detection of car window, which is similar to the height adjustable desk, angular velocity detection [ 4 , 5 ], armature current detection [ 6 , 7 , 8 , 9 ], torque rate detection [ 10 , 11 , 12 ], and torque detection [ 13 , 14 , 15 ] of the motor are often used. As the armature current value and motor torque of DC motor are reflected in the running state, those threshold values are selected as a basis for judgment [ 7 ].…”

Smart Pinch Detection for Car's Electric Sunroof Based on Estimation and Compensation of System Disturbance

“…In order verify the result that the pinch detection by torque rate is better than the motor speed and torque in different conditions, the curves of the motor speed, the pinch detection torque and the pinch detection torque rate are analyzed in different input voltages. In general, the range of motor input voltage is 9~16[V] in engineering [16] . Since U changes slowly in most cases, it can be regarded as a constant within a short period.…”

Smart Pinch Detection for Car's Electric Sunroof Based on Estimation and Compensation of System Disturbance

“…In general, the range of motor input voltage is 9~16[V] in engineering [16] . Since U changes slowly in most cases, it can be regarded as a constant within a short period.…”

“…The motivation for this approach comes from the idea that the torque rate is less sensitive to motor parameter uncertainty than the torque or the angular velocity [6] . To weaken the impact of the noise on pinch detection, some researchers proposed H∞ filter to address system noise [15][16][17] , and other researchers proposed Kalman filter to deal with system noise [18][19][20][21] . But H∞ filter does not guarantee that the estimation error variance is minimum or in a limited range.…”