在“双碳”战略背景下，经济的快速发展与节能减排的要求形成新能源汽车的双重驱动力。四轮独立驱动电动汽车因各车轮扭矩独立调节、控制精度高、响应速度快等特点，成为了电动汽车领域关注热点。传统车辆在积雪、湿滑等低附着路面行驶中遇到复杂多变的路面类型，会使车辆车轮打滑、横摆失稳、轨迹偏移，严重威胁行驶安全性。本文针对四轮独立驱动电动汽车在低附着路况下的横摆失稳问题，提出基于分层架构的电子差速控制策略，主要研究工作如下：

首先，构建四轮独立驱动电动汽车动力学模型体系。基于车辆结构特征，建立了包含车辆简化二自由度、车轮动力学以及电控系统模型，为后续稳定性控制奠定理论基础。其次，设计上层整车力矩决策控制架构。在横向控制维度，提出超螺旋滑模联合控制算法，通过横摆角速度和质心侧偏角跟踪误差的动态补偿机制实现直接横摆力矩优化；在纵向控制维度，基于模糊PID驱动防滑控制器构建纵向驱动协调体系，有效解决车轮打滑问题。最后，建立下层力矩协调分配机制。突破传统垂向载荷分配法的局限，基于轮胎稳定裕度构建轮胎负荷率最优目标函数，提出一种兼顾效率与稳定性的转矩分配算法；同时为实现高动态响应和快速转矩控制，设计了轮毂电机无磁链观测直接转矩控制系统，实现四轮转矩的实时精准分配。

建立Simulink/CarSim的联合仿真平台，通过低附着直线加速和低附着双移线复合工况的对比实验，验证了所提控制策略的有效性。仿真结果表明：滑转率抑制在0.15以下、横摆角速度跟踪误差降低10.00%、质心侧偏角跟随精度提高24.52%，有效缓解了低附工况下的失稳风险。特别是在轮胎负荷率优化方面，提出的分配策略较传统方法峰值降低30.29%。此外，通过对电机驱动系统的电流谐波、转矩响应特性的时域分析，验证了电机控制策略的有效性。

搭建四轮独立驱动电动汽车实验平台并介绍了硬件模块和软件程序。在积雪路面的实车验证中，提出的动态协调控制策略展现出显著优势：实现滑转率的抑制，横摆角速度跟踪误差减小至3.16%，质心侧偏角偏差控制在±1.12°区间，轮胎稳定裕度提升30.43%。实验数据验证了超螺旋滑模联合控制和基于轮胎负荷率的最优目标分配策略的协同控制效果，为四驱电动汽车在低附着工况下的稳定性控制提供了理论依据与工程实践参考。

Under the background of "double carbon" strategy, the rapid development of economy and the requirements of energy conservation and emission reduction form the dual driving force of new energy vehicles. Four-wheel independent-drive electric vehicles, characterized by independent torque regulation, high control precision, and fast response at each wheel, have become a focal point in the electric vehicle sector. Traditional vehicles traveling on low-adhesion surfaces such as icy or wet roads often encounter complex road conditions, leading to wheel slippage, yaw instability, and trajectory deviation, which severely compromise driving safety. This research investigates the mitigation of yaw instability in four-wheel independently driven electric vehicles operating on low-friction surfaces through the development of a multi-layer electronic torque distribution control architecture. The main contributions are as follows:

Firstly, a multi-dimensional dynamics modeling framework for four-wheel independent drive electric vehicles is established. Based on structural characteristics, comprehensive control models are developed, including a 7-DOF vehicle model, a simplified 2-DOF reference model, wheel dynamics models, an electric system control model, and hub motor models, laying a theoretical foundation for stability control. Secongdly, an innovative torque decision-making architecture is designed. For lateral control applications, a super-twisting sliding mode control algorithm is proposed to replace the conventional fuzzy sliding mode cooperative control approach. This algorithm dynamically compensates for yaw rate and sideslip angle tracking errors to optimize direct yaw moment. For longitudinal control, a fuzzy PID anti-slip controller to coordinate longitudinal drive forces, effectively mitigating wheel slippage. Finally, a multi-objective torque distribution mechanism is developed. Moving beyond traditional vertical load distribution methods, an optimal tire load rate objective function is constructed based on tire stability margins, enabling a torque distribution algorithm that balances efficiency and stability. In order to achieve high dynamic response and fast torque control, a direct torque control without flux linkage observation system of hub motor is designed to achieve real-time accurate torque distribution of four wheels.

An integrated co-simulation framework combining MATLAB/Simulink and CarSim has been constructed to conduct the proposed control strategy under low-adhesion straight-line acceleration and double-lane-change scenarios. Simulation results demonstrate significant improvements: slip ratio suppression below 0.15, 10.00% reduction in yaw rate tracking error, and 24.52% enhancement in centroid sideslip angle following accuracy, effectively mitigating instability risks in low-friction scenarios. Notably, the innovative tire load rate allocation strategy achieved 30.29% peak reduction compared to conventional methods. Time-domain analyses of current harmonics and torque response characteristics further verified the effectiveness of motor drive control strategies.

A four-wheel independent drive electric vehicle experimental platform is established. Field tests on compacted snow surfaces confirmed the superiority of the dynamic coordination strategy: slip ratio stabilization, yaw rate tracking error reduced to 3.16%, centroid sideslip angle constrained within ±1.12°, and tire stability margin improved by 30.43%. Experimental data validated the synergistic effects of super-twisting sliding mode control and tire load rate-based optimal allocation strategy. This study offers innovative methodologies and practical references for active safety control in electric vehicles, with substantial theoretical significance and engineering application potential.

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