滑移辅助转向下的四轮冗余电驱动车辆分层式力矩协同控制

Multi-wheel independent drive electric vehicles have the advantages in flexible structural arrangement and high transmission efficiency. However, while facing with the complex road conditions with nonlinear perturbation, how to achieve effective redundancy torque distribution and differential control during the steering are difficult problems. By using advantages of the in-wheel-motor system which has dual characteristics of the driving and actuating mechanism, this project proposed a skid-assisted steering mode firsly, and take the torque coordination control of four-wheel independent driving electric vehicle as the object of study. Based on the problems in the controller by analytical model, a hierarchical control system is designed for the torque distribution in motors. In the top layer, from the driver command and reference model we can get the control objective. The yaw-moment control is calculated by fuzzy-logic controller in the middle layer. Multi-objective optimization of torque distribution is worked as the low-level controller. Finally, the global collaborative planning of the four independent driving wheels can be realized. By using the theory of nonholonomic constraint system, the reference model of skid-assisted steering and its geometric relationship is investigated. Since the motors are easy to take dynamic observation and collect electric signals in real-time, a method for state forecasting and estimation of electric vehicle is proposed.

多轮独立电驱动车辆具有结构布置灵活、传动效率高的优势,但通常面临在复杂工况的非线性扰动下，如何实现有效的冗余力矩分配与转弯差速问题。针对轮毂电机独立驱动在车辆运动控制方面的优势，本课题首次提出传统转向机构结合轮式滑移的多样转向模式,对四轮独立电驱动车辆的转矩协同控制所涉及的关键技术开展研究。针对以往基于解析模型控制所存在的问题，拟引入分层式设计的电机转矩分配控制系统。首先基于上层参考运动模型与驾驶员输入获得转向动力学控制目标, 通过中层的智能模糊逻辑控制器进行横摆力矩的计算, 最后以多目标驱动力优化分配为底层控制器, 实现电动车辆的四轮驱动力矩全局协同规划。其中滑移辅助转向参考模型采用非完整约束系统理论，基于几何瞬心法建立关系模型。同时利用电驱动系统的易观测性，通过对行驶中的电动化参数进行实时动态提取，设计基于电机模型的车辆状态预估与观测方法。

本项目以电动车辆为研究对象，充分利用电机系统具有驱动与执行机构的双重特性，完成了对多轮独立电驱动车辆实现的冗余力矩分配与差速转向问题的研究。针对轮毂电机独立驱动在车辆运动控制方面的优势，本课题通过研究结合轮式滑移的多样转向模式, 完成对四轮独立电驱动车辆的转矩协同控制关键算法设计。利用电驱动系统的易观测性，通过对行驶中的电动化参数进行实时动态提取，设计基于电机模型的车辆状态预估与观测方法 。首先基于上层参考运动模型与驾驶员输入获得转向动力学控制目标, 通过中层的智能模糊逻辑控制器进行横摆力矩的计算, 最后以多目标驱动力优化分配为底层控制器, 实现电动车辆的四轮驱动力矩全局协同规划。针对以往基于解析模型控制所存在的问题，引入具有多维感知和直觉推理的智能控制方法来实现车辆的自适应驱动控制。完成了以模糊逻辑理论构建的安全辅助决策系统，根据预估安全状态作为输入，进而以定性和定量相结合的模糊推理机制对驱动系统进行安全力矩控制。本课题所设计的控制器将状态观测器与模糊逻辑理论有机结合在电动车辆稳定控制中，实现仿人智能的多维信息融合和力矩动态修正，提高了电动车辆操控的安全和稳定裕度。这些研究成果对改变目前电动汽车研究普遍采用传统汽车的控制思路有很好的创新和借鉴意义。