Study of Hydraulic ABS Braking Systems under Various Road Friction Coefficients Using Co-Simulation and Experimental Methods

Abstract

The Anti-lock Braking System (ABS) has become an essential safety feature in modern vehicles due to its capability to prevent wheel lock during braking, thereby preserving vehicle stability and steering controllability. As a typical mechatronic system, ABS integrates hydraulic, mechanical, and electronic subsystems governed by an electronic control unit (ECU). This study proposes a multidisciplinary co-simulation framework for investigating the braking performance of a passenger vehicle equipped with ABS. The hydraulic behavior of the system is modeled using AMESim Simcenter, while the vehicle longitudinal dynamics and control strategy are implemented in MATLAB Simulink. In the AMESim environment, a fourchannel hydraulic ABS modulator is developed, where the ECU control signal serves as the input and the brake circuit pressure is generated as the output. This pressure signal is subsequently transmitted to the Simulink model, which utilizes it to evaluate wheel slip behavior under braking conditions at a specified tire–road adhesion coefficient, forming a closed-loop simulation architecture. To enhance braking efficiency under varying slip conditions, a hybrid control strategy combining a conventional PID controller with fuzzy logic is introduced. The proposed co-simulation structure enables real-time bidirectional interaction between the physical hydraulic subsystem and the control module: pressure outputs from AMESim are fed into Simulink, while control signals generated in Simulink are used to actuate the solenoid valves within the AMESim model. An experimental test rig was established to validate the proposed model and to assess the effectiveness of the control algorithm under real operating conditions. Experimental results demonstrate that the vehicle can decelerate from an initial speed of 90 km/h to a complete stop without wheel lock in approximately 2.54 seconds, corresponding to a braking distance of 30.48 meters. Compared with a conventional hydraulic ABS, the proposed control strategy reduces braking time and stopping distance by approximately 8.5 % and 6.5 %, respectively. Furthermore, a close agreement between simulation and experimental results is observed, with deviations of 4.4 % in braking time, less than 0.5 % in stopping distance, and 3.9 % in deceleration, confirming the accuracy and reliability of the developed model. The results indicate that the integration of PID control with fuzzy logic significantly enhances ABS performance, ensuring stable and effective braking under emergency conditions across varying road adhesion scenarios.