Predictive Performance of Anti-Lock Braking System with PID Controller Optimized by Gravitational Search Algorithm for a Quarter Car Model: Simulation Modeling and Control

Abstract

Anti-lock Braking Systems (ABS) are critical safety components in the passenger vehicles. The ABS prevents wheel lock-up during braking and maintains vehicle control. However, conventional braking systems have produced limitations in stopping distance and slip ratio, especially on varying road surfaces. This research addresses these issues by developing an ABS model using a quarter-car framework incorporated with a PID controller optimized by using Gravitational Search Algorithm (GSA). In this study, the mathematical equation of a quarter-car brake model is derived to represent a conventional braking system to provide a basis system for analyzing its performance. Next, a Simulink model is developed in MATLAB to simulate the conventional braking system. To develop an ABS model, a PID controller is developed. The PID parameters are tuned manually using a trial-and-error approach to provide a baseline for comparison. Subsequently, GSA is applied to optimize the PID controller parameters to improve stopping distance and maintain optimal slip ratios. The ABS performance is evaluated by analyzing performance criteria including stopping distance, slip ratio, vehicle speed, and wheel speed. Comparative analysis indicated significant improvements in braking performance against the conventional system. The ABS with PID controller optimized by GSA reduced stopping distances, better slip ratio control, and improved vehicle stability during braking. The expected finding of the proposed ABS with PID optimized by GSA offers considerable advancements in automotive braking technology. These results underscore the potential for real-world applications in enhancing vehicle safety systems, contributing to safer and more reliable passenger vehicle braking performance.