Distributed-drive commercial vehicles are prone to skidding or rolling over when operating on low-friction roads or negotiating tight curves. To address this issue, this paper proposes a control strategy based on Adaptive Model Predictive Control (AMPC) to coordinate yaw and roll stability of distributed-drive commercial vehicles. By analyzing the improved β−β˙ phase-plane boundary and the roll stability threshold, this study identifies the yaw rate, sideslip angle, and predicted lateral load transfer rate (PLTR) as key indicators for vehicle stability assessment. The AMPC controller employs these metrics to dynamically adjust the control weights associated with yaw and roll stability in real time, thereby calculating the required additional yaw moment, which is applied through optimal torque distribution among all four wheels to achieve coordinated control. Finally, experiments are conducted on a Simulink-TruckSim co-simulation platform to assess the performance of AMPC. Compared with the conventional MPC method, the proposed approach achieves obvious improvements in both roll and yaw stability under sinusoidal and fishhook operating conditions.
Na et al. (2026) studied this question.