Hierarchical ABS control based on MPC slip rate tracking

To address the inherent limitations of conventional Anti-lock Braking Systems (ABS) characterized by time-varying single slip rate characteristics during vehicular deceleration, this study proposes a novel double-layer ABS control strategy integrating Model Predictive Control (MPC)-based slip rate tracking with wheel angular acceleration regulation. The research framework comprises three principal phases: First, we establish a comprehensive dynamic braking system model incorporating single-wheel dynamics, slip rate dynamics, nonlinear tire behavior, and hydraulic brake actuator characteristics. Subsequently, an upper-layer MPC controller is developed to achieve real-time tracking of the predefined optimal slip rate through predictive state estimation and constrained optimization. In parallel, a lower-layer proportional-integral-derivative (PID) controller is implemented to regulate wheel angular acceleration as a secondary control objective. The hierarchical control architecture ensures coordinated operation between the two control layers until braking termination conditions are met. Extensive co-simulations are conducted across three distinct road surfaces (dry asphalt, wet concrete, and snowy road) under 65 km/h initial velocity conditions. Comparative analyses with conventional single-objective ABS control demonstrate that the proposed double-layer control strategy achieves 12.7% reduction in braking distance, 18.3% improvement in slip rate tracking accuracy, and enhanced transient response characteristics during emergency braking scenarios. In the subsequent plan, we will also conduct further verification of the algorithm's real-time performance and robustness in engineering hardware through hardware-in-the-loop experiments