Stability-Margin-Aware Lateral Control for Four-Wheel Independent-Drive Electric Vehicles

Abstract

This paper presents a real-time lateral stability control framework for four-wheel independent-drive electric vehicles subject to model mismatch, nonlinear tire behavior, and varying road adhesion. The proposed method combines a hierarchical yaw-moment controller with a stability-margin-aware analytical torque allocator. In the upper layer, a sideslip-regulated yaw-rate reference is first generated, and lumped disturbances are then compensated for through observer-assisted robust tracking to produce a smooth desired yaw moment. In the lower layer, the longitudinal torque demand and desired yaw moment are converted into individual wheel torques by continuously adjusting the allocation weights according to the vehicle-level yaw and sideslip deviations and the wheel-level remaining stability margins. This closed-form allocation avoids online iterative optimization and reduces excessive torque assignment to wheels approaching saturation. Comparative co-simulation results under double-lane-change and slalom maneuvers demonstrated improved yaw-rate and sideslip-angle tracking accuracy, smoother torque commands, and favorable phase-plane convergence compared with representative sliding-mode and predictive-control benchmarks. These results support the practical implementation of high-frequency chassis-control loops for electric vehicles.