A Simulation Based Methodology for Optimizing Correlation of Brake Disc Temperature

Brake disc temperature is a critical factor influencing the performance and wear characteristics of braking systems in automobiles. Hence it is very important to optimize the correlation of brake disc temperature prediction with test. In this study critical parameters of Brake Disc temperature evaluation are identified, and algorithm is used to optimize the critical parameters to achieve the correlation of prediction with experiment data. Through a series of controlled experiments and simulations, disc temperatures are monitored under different braking conditions and simultaneously input parameters for prediction are optimized to achieve the correlation. Statistical methods were applied to evaluate the observed correlations and to model the predictive behavior of brake disc temperatures.

Finally, A front-loading tool is developed to optimize the brake disc keeping target thermal capacity via algorithm. The findings of this study are expected to contribute to the enhancement of brake system design by providing insights into thermal dynamics during braking. This can lead to the development of more efficient cooling strategies and materials that are better suited to dissipate heat, thereby improving safety and performance.