Model Predictive Control of Wheel Slip Towards Antilock Brake System Using Convex optimization

Model Predictive Control (MPC) has been used in the automotive domain to control powertrain, suspension, and brakes. Active Vehicle Safety Systems (AVSSs), where the brake system plays a significant role, have gained much impetus since they can potentially reduce road fatalities. Wheel Slip Regulation (WSR) is a popular methodology used in developing AVSSs such as Antilock Brake System and Direct Yaw Control using brake control. This work proposes an MPC based algorithm for WSR utilizing linear longitudinal vehicle and wheel dynamics. The MPC problem is developed as a convex optimization formulation, ensuring that the control problem has a unique solution. The problem is formulated as a Quadratic Program with linear inequality constraints, and an efficient custom MPC solver is developed. The custom MPC solver reduces the number of computations by classifying the matrix operations into three categories, namely, constant matrices, reference-dependent matrices, and feedback-dependent matrices. The proposed MPC is evaluated using IPG TruckMaker®, a vehicle dynamics simulation software, interfaced with MATLAB Simulink®. The braking distance improvement with MPC is in the range of 10% to 40%, and the custom solver decreases the computational time of one iteration by 20 times compared to CVX, a MATLAB tool for convex programming.