A gain-switched self-optimizer for braking controller

What is it about?

This paper proposes a braking control algorithm, which maximizes the tire braking forces in different and unknown road conditions. Without knowing the road conditions, the controller applies a self optimization algorithm to seek and find the most appropriate braking action in order to utilize maximum braking potential of the tire-road system. By switching the gain in the optimization loop, fast convergence to the unknown set point and operation with less aggressive control action in the close neighborhood around the set point is accomplished.

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Why is it important?

Due to the unknown and variable road conditions, finding the optimum braking torque to utilize maximum friction potential of the tires is a challenging task in ABS braking situations. A misjudgment about the optimal set point choice may cause lower performance of braking via either less friction force generation or via blocking the tire rotation and hence the vehicle steer ability. The minimum stopping distance is ensured when the tires operate at the peak point of the braking force versus slip characteristics subject to unknown road conditions. In addition, headway stability and steer ability are also improved as locking of the wheels are prevented.

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