Machine Learning based Approach for Brake Pad Pressure Distribution

The Brake system in automobiles plays a vital role in customer safety. Brake pads are crucial components that experience huge pressure while slowing down the vehicle’s movement. Designing a brake pad requires sound knowledge of structural design, manufacturing ability, and material properties. Further, an optimized model is chosen based on the size of the brake pad and the brake power requirement. Brake pad pressure distribution is one of the main studies in designing automobile brake pads. Numerical solvers are used to validating the experimental results, which is a repetitive process for every new design under the study. Computer-aided engineering tools are costly and time-consuming for design iterations. The present paper provides a new approach for estimating brake pad pressure distribution using machine learning techniques. The accuracy of the machine learning models for various designs shows promising outcomes.