分布式驱动电动汽车具有可控自由度高、执行响应速度快、能量利用率高等特点。然而，其现有的状态估计与参数辨识方法尚未完善；动力学控制未能有效利用硬件优势、充分发挥整车性能。本文针对分布式驱动电动汽车，设计了状态估计与参数辨识方法，提出了基于多执行器协调的横向与侧倾稳定性控制、路径跟踪控制策略，以提高车辆在有人与无人驾驶场景下的稳定性、机动性与安全性。 首先，本文提出了状态估计与参数辨识的联合估计方法，对车辆的质心侧偏角、车身侧倾角、路面峰值附着系数进行估计。针对轮胎纵侧向力估计，提出了基于一阶滑模观测器的估计方案。针对质心侧偏角与车身侧倾角估计，设计了基于平方根容积卡尔曼滤波器的估计方法，并结合横向加速度积分重置的方法对质心侧偏角的估计值进行修正，通过自适应权重实现两者的融合。针对路面峰值附着系数估计，设计了基于正则化递归最小二乘的估计方法，通过引入滑移率与侧偏角的参数更新阈值，以提高估计的鲁棒性与准确性。 其次，本文提出了一种分层式的横向与侧倾稳定性协调控制方法，对分布式的驱动电机、液压制动以及半主动悬架进行协调控制。在上层协调控制器中，通过模型预测控制跟踪名义参考值，得到期望的附加横摆力矩与抗侧倾力矩；在轮胎纵向力分配中，考虑到期望总转矩与期望附加横摆力矩的要求，通过优化分配得到各个车轮的期望纵向力；在轮胎滑移率控制器中，由期望纵向力转换得到目标滑移率，通过滑模控制得到输出转矩；在悬架阻尼力分配中，考虑垂向载荷分布的要求，以及悬架阻尼限制的约束条件，分配得到悬架阻尼力；而电液制动分配中，通过分频的方法设计电液制动的分配策略，以实现最优的制动性能。 然后，本文提出了一种路径跟踪控制方法，实现了对分布式的驱动电机与主动转向的协调控制。首先，建立了分布式驱动汽车的路径跟踪被控系统模型；同时，考虑路径跟踪的准确性、控制输出的平稳性等控制目标，并结合驾驶员的期望总转矩、动力学稳定性边界及执行器的物理限制等约束条件，建立了路径跟踪的最优控制问题；然后，通过一种基于增广拉格朗日法的迭代线性二次型调节器对该问题进行求解，从而实现路径跟踪控制。 最后，搭建了实车试验平台，开展了状态估计与参数辨识、横向与侧倾稳定性控制、路径跟踪控制方法的实车试验，验证了所提方法的有效性。

Distributed drive electric vehicles have the characteristics of high degree of controllability, fast response speed, and high energy utilization. However, the existing state estimation and parameter identification methods are not yet perfect; dynamics control fails to effectively take advantage of hardware advantages and give full play to vehicle performance. This paper designs state estimation and parameter identification methods for distributed drive electric vehicles, and proposes lateral and roll stability control and path tracking control strategies based on cross-actuator coordination to improve the stability, maneuverability and safety of vehicles in manned and unmanned driving scenarios. First, this paper proposes a joint estimation method of state estimation and parameter identification to estimate the vehicle side slip angle, roll angle, and road peak adhesion coefficient. For tire longitudinal and lateral force estimation, an estimation scheme based on a first-order sliding mode observer is proposed. For the estimation of vehicle slip angle and roll angle, an estimation method based on the square root cubature Kalman filter is designed, and combined with the lateral acceleration integral method to correct the estimated value of vehicle side slip angle, and achieve fusion of both through adaptive weights. For the estimation of the peak adhesion coefficient of the road surface, an estimation method based on regularized recursive least squares was designed, and the parameter update thresholds of slip rate and slip angle were introduced to improve the stability and accuracy of the estimation. Secondly, this paper proposes a hierarchical coordinated control method for lateral and roll stability, using distributed drive motors, hydraulic brakes and active suspensions for coordinated control. In the upper-level coordination controller, the nominal reference value is tracked through model predictive control to obtain the expected additional yaw moment and anti-roll moment; in the tire longitudinal force distribution, the desired total torque and the expected additional yaw moment are taken into account According to the requirements, the expected longitudinal force of each wheel is obtained through optimal distribution; in the tire slip rate controller, the target slip rate is obtained by converting the expected longitudinal force, and the output torque is obtained through sliding mode control; in the suspension damping force distribution, Considering the requirements of vertical load distribution and the constraints of suspension damping limit, the suspension damping force is obtained by distribution; in the electro-hydraulic braking distribution, the electro-hydraulic braking distribution strategy is designed through the frequency division method to achieve the optimal braking performance. Then, this paper proposes a path tracking control method to achieve coordinated control of distributed drive motors and active steering. First, a path tracking controlled system model of a distributed drive vehicle is established; at the same time, control objectives such as path tracking accuracy and control output stability are considered, and the driver‘s expected total torque, dynamic stability boundary and The optimal control problem of path tracking is established based on the physical limitations of the actuator and other constraints; then, the problem is solved through an augmented Lagrangian iterative linear quadratic regulator, thereby realizing path tracking control. Finally, a real vehicle test platform was built, and real vehicle tests of state estimation and parameter identification, lateral and roll stability control, and path tracking control methods were carried out to verify the effectiveness of the proposed method.