In situ steering anti-slip control for multi-axle distributed drive electric vehicles based on road surface recognition

To address vehicle instability and excessive wheel slip during the in situ steering of multi-axle distributed drive electric vehicles (DDEVs) on low-adhesion surfaces, this paper proposes a hierarchical cooperative anti-slip control strategy based on real-time road surface recognition. First, an adaptive road-tire interaction model is developed using a fuzzy logic observer based on the Burckhardt tire model, which dynamically estimates the peak adhesion coefficient and determines an optimal expected slip ratio tailored to the unique tire-road scrubbing characteristics of in situ steering; second, a decoupled hierarchical control architecture is established where the upper layer calculates the required yaw moment to stabilize the rotation center, while the lower layer executes a multi-loop cooperative control that synchronizes individual wheel speeds with the desired yaw rate, utilizing the identified slip ratio as a dynamic constraint to optimize torque distribution; third, a dynamic traction optimization mechanism enables localized torque adaptation to overcome intense resistive moments, ensuring symmetric rotation even on slippery roads. Co-simulations conducted in a high-fidelity MATLAB/Simulink and TruckSim environment demonstrate that under packed snow conditions ( <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" overflow="scroll"> <mml:mrow> <mml:mi>μ</mml:mi> <mml:mo>=</mml:mo> </mml:mrow> </mml:math> 0.191), the strategy effectively regulates wheel slip to the target ratio (s ≈ 0.49), suppressing uncontrolled spin and enhancing yaw rate convergence. Finally, variable topology tests involving axle lifting validate adaptive effectiveness of the anti-slip system under shifting vehicle configurations.