Adaptive robust lateral stability control of distributed drive electric vehicles with extended state observer under uncertainties

Stability control remains a critical challenge in distributed drive electric vehicles (DDEVs) with mechanical elastic electric wheels (MEEWs), especially under extreme operating conditions. To address this, a hierarchical direct yaw moment control (DYC) strategy integrating adaptive robust control (ARC) and an extended state observer (ESO) is proposed, which explicitly accounts for both structural and non-structural uncertainties. Firstly, a two-degree-of-freedom vehicle dynamics model considering uncertainties is established. In the upper-level controller, the ARC generates an ideal yaw moment to enhance lateral stability while compensating for structural uncertainties, and its asymptotical stability is guaranteed by Lyapunov theory. Furthermore, the ESO is integrated to address non-structural uncertainties, forming the ARCESO framework. Finally, a PID speed controller calculates the desired longitudinal force, and the lower-level controller optimizes four-wheel torque distribution with tire workload minimization. The simulation results under three test conditions demonstrate that, compared to the uncontrolled scenario, the RMSE of the sideslip angle and yaw rate under the proposed controller are reduced by over 60.64% and 51.01%, respectively. Furthermore, robustness validation reveals that the variation rates of RMSE for these two stability indicators are constrained within 3% and 4% separately.