Nature Based Self-Learning Mechanism and Simulation of Automatic Control Smart Hybrid Antilock Braking System

Abstract

The antilock braking system (ABS) is intended to augment braking effectiveness, maintains understeer and oversteer conditions. The braking system performance is degraded in the case of severe road conditions. The research paper presented the effectiveness of smart hybrid antilock braking system in automobiles. The concept of antilock braking system and manual braking system is anticipated to a single unit to overcome the problem facing in the braking system in vehicles. Lyapunov’s theoretical stability approach is used for the system stability. The concept of smart control development is used to solve system complexity and real time issues in different road conditions. Directional Control Valve (DCV) plays very important role in controlling the flow direction of brake oil. The Electronic Control Unit (ECU) is the slip controller for antilock braking system, which takes inputs from brake pedal, speed of all four wheels and various road conditions, processes the accumulated data to generate corresponding PWM signal for the DCVs. The ignition switch and ECU controls the activation and de-activation of directional control valve. The MATLAB/Simulink, 2015 version and experimental analysis using Automation Studio verified the model behavior in both ABS and manual braking mode. The system performance is analyzed during ignition ‘ON’ and ‘OFF’ conditions. The comparative study of the ABS mode and manual mode against wheel speed and vehicle speed is predicted in different time intervals. The smart hybrid ABS control provides better response in comparison to conventional braking. It is experimentally proved that the acclaimed antilock braking system reduces the stopping distance in comparison to the manual braking unit.