Abstract

Bench inspection approach for automobile Anti-lock Braking System (ABS) has gained research interests recently due to its high efficiency, small site occupation and insusceptibility to environment influences. The current work proposed a novel systematic bench inspection approach for ABS. In order to dynamically simulate various road adhesion coefficients, torque controllers are used for loading different torques to the drums. Furthermore, flywheels are adopted to simulate the translational inertia of the vehicle braking on road for compensating the inertial energy of ABS road experiment on the bench. The principal component analysis (PCA) is applied for accurate and efficient data analysis. The automatic evaluation of ABS is achieved by using the processed PCA data as an input to the back-propagation (BP) neural network classifier. The experiments established that the new approach can accurately simulate various road braking conditions. It can be carried out for the inspection of ABS installed in the car.

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