Stability Control for Distributed-Drive Electric Vehicle Using Particle Filter and Fuzzy Integral Sliding-Mode Control

The Distributed Drive Electric Vehicles (DDEVs) offer advantages such as independently controllable driving and braking forces at each wheel, rapid response, and precise control. These features enable effective electronic stability control (ESC) by appropriately distributing torque across each wheel. However, conventional ESC systems primarily rely on single-wheel hydraulic differential braking, which underutilizes the full potential of independent torque control in DDEVs. To address this, a hierarchical control strategy is proposed for distributed driving and braking ESC, combining particle filter (PF) and fuzzy integral sliding mode control (FISMC). The strategy comprises three layers: the vehicle state estimation layer employs a three-degree-of-freedom vehicle model and PF to estimate sideslip angle and vehicle speed; the target torque decision layer integrates a speed tracking controller and a yaw moment controller using FISMC, which computes corrective yaw moment by comparing estimated and ideal yaw rate and sideslip angle, while adaptively tuning sliding mode surface parameters based on vehicle dynamics; the dynamic torque distribution layer then allocates driving and regenerative braking torques to each wheel based on vertical tire load variation. A co-simulation platform using MATLAB/Simulink and CarSim is established to validate the proposed control strategy under double lane change and J-turn maneuvers, comparing it with traditional ESC. The results show that the proposed ESC achieves high accuracy in estimating vehicle state and effectively adapts to varying driving conditions while maintaining stable vehicle speed, thereby enhancing driving stability.