Differential steering is a unique steering technology for distributed drive vehicles, which cannot only be applied to steering power, but also be used as a backup steering scheme for distributed drive vehicles. When the road adhesion conditions are poor, differential steering will lead to wheel slip, reduce the tire lateral force margin, and then affect the vehicle stability. To solve this issue, it is necessary to integrate the differential steering and anti-skid drive control. In this paper, the four-wheel distributed drive electric vehicle (DDEV), tire and wheel dynamics models are firstly established. Then the coordinated control strategy is proposed for anti-skid driving and differential steering of DDEV, where a neural network is adopted for the weights regulation of the two controllers. Next, an improved slip rate estimation method avoiding the calculation of vehicle speed is proposed which can reduce the error when the wheel angular acceleration is less than zero. Then, the slip rate fuzzy threshold controller is designed to control the wheel slip rate, and the feed forward-feedback differential torque controller is designed to obtain the differential torque required in steering. Considering the vehicle stability, the torque distribution adopts the quadratic programing method and combines the constraints of wheel slip rate and tire load rate to optimize the distribution of each wheel’s driving torque. Finally, the joint simulation and hardware-in-the-loop (HIL) are carried out to verify the effectiveness of the proposed improved slip rate estimation method and control strategy. The results show that the calculation error is reduced to 5.13% with the improved slip rate estimation results, and the superiority of proposed control method is verified by both simulation and HIL test.

差速转向是分布式驱动车辆独有的转向技术，不仅可以应用于转向助力，还可以作为分布式驱动车辆的备用转向方案。当路面附着力条件差时，差速转向会导致车轮打滑，降低轮胎侧向力裕度，进而影响车辆稳定性。要解决这个问题，就需要集成差速转向和防滑驱动控制。本文首先建立了四轮分布式驱动电动汽车（DDEV）、轮胎和车轮动力学模型。然后提出了DDEV防滑行驶和差动转向的协调控制策略，其中采用神经网络对两个控制器进行权重调节。下一个，提出了一种改进的滑移率估计方法，避免计算车速，以减少车轮角加速度小于零时的误差。然后，设计了滑移率模糊阈值控制器来控制车轮滑移率，并设计了前馈-反馈差动转矩控制器来获得转向所需的差动转矩。考虑车辆稳定性，扭矩分配采用二次规划法，结合车轮滑移率和轮胎载荷率约束，优化各车轮驱动扭矩的分配。最后，通过联合仿真和硬件在环（HIL）验证了所提出的改进滑移率估计方法和控制策略的有效性。