An Adaptive Multi-Layer Anti-Lock Braking Control Method Based on Fuzzy Logic

Abstract

The Anti-lock Braking System (ABS) is a key component in automotive safety, with its controller playing a pivotal role in braking effectiveness. Current ABS technology has excellent performance under normal road conditions, but faces the challenge of dynamic adaptation under extreme weather conditions. To this end, this paper proposes an Adaptive Multi-Layer Anti-Lock Braking Control Method (AMABC). Integrating various control technologies and optimized through an automatic switching logic, AMABC includes a Deceleration Rate Control module, a Pressure Optimization module, and a Fuzzy-based Anti-lock Control module. Notably, the Pressure Optimization module anticipates and intervenes in tire lockup, ensuring smooth braking transitions and effective pressure management, significantly enhancing driving performance and vehicle safety. The application of fuzzy logic further refines the system’s response to changing automobile dynamics. Simulation experiments demonstrate that AMABC reduces braking times by 24.07%, 23.17%, and 10.30% on dry, wet, and snowy roads, respectively. This highlights the potential of integrating basic control methods to enhance braking performance without the need for additional hardware upgrades, offering significant practical application value.

Keywords

• Fuzzy logic
• multi-layer anti-lock braking control
• deceleration rate control
• pressure optimization
• anti-lock control