Modeling and MPC-Based Control of an Electromechanical Brake Booster System

Abstract

With the rise of intelligent and electric vehicles, the demand for high-performance and responsive braking systems has significantly increased. This paper presents a braking control strategy based on model predictive control (MPC) for intelligent electric vehicles. The vehicles use an electromechanical brake booster called iBooster. A dynamic model is established to characterize the actuator dynamics and the vehicle’s longitudinal motion. The control system employs a two-layer architecture: the upper layer utilizes Model Predictive Control (MPC) for deceleration planning, while the lower layer employs a PID controller to track the planned signal and achieve real-time actuator control. To test the control system, simulations are done under three road conditions. These are dry roads, slippery roads, and downhill slopes. Simulation results demonstrate that the control system accurately tracks the target deceleration with rapid response, minimal overshoot, and robust performance against disturbances. The system also works well when road friction is low or when gravity affects braking. In all cases, the system reaches the target within about three seconds. This method is useful for building safe and adaptive braking systems for electric vehicles.