Stability Control for Distributed Drive Electric Vehicles 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, traditional ESC systems typically employ single-wheel hydraulic differential braking, failing to fully utilize the independent torque control capabilities of DDEVs. This study proposes a hierarchical control strategy for distributed driving and braking ESC based on particle filter (PF) and fuzzy integral sliding mode control (FISMC). First, the vehicle state estimation layer uses a three-degree-of-freedom vehicle model and the PF to estimate sideslip angle and vehicle speed. Next, the target torque decision layer includes a target speed tracking controller and a yaw moment decision controller. The yaw moment decision controller uses the FISMC to determine additional yaw moment by comparing the estimated yaw rate and sideslip angle with their ideal values, while dynamically adjusting the sliding mode surface parameters based on vehicle state and driving conditions. Finally, the dynamic torque distribution layer allocates the driving and regenerative braking torques to each wheel according to changes in vertical tire load. 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.