考虑网络诱导时延的电动汽车主动安全控制策略

为了解决汽车CAN网络的消息处理、数据丢包等行为会引起汽车控制系统的时间迟滞效应，从而影响整车动力学控制的准确性的问题，提出了基于鲁棒模型预测控制的汽车横摆稳定性控制策略. 首先分析了CAN网络的消息时延特点，以此为基础构建多胞时滞动力学模型描述汽车网络的参数不确定性. 进一步设计了包含不确定参数的鲁棒模型预测控制器，提高了汽车主动安全控制器的抗干扰能力. 此外，横摆稳定控制策略还使用基于渐进稳定不变椭圆集的变时域最优控制律提高了鲁棒控制算法的在线求解效率，平衡了系统控制鲁棒性和最优性的矛盾. 结果表明，提出的控制策略能够抵抗CAN网络时延诱导的参数不确定性，缓解鲁棒控制算法的保守性，提高汽车转向时的主动安全性能. 

Active Safety Control Strategy of Electric Vehicles Considering CAN-Induced Time Delay

The message processing and data packet loss of the automotive CAN network would cause the time delay effect of the automotive control system, thereby affecting the accuracy of the vehicle dynamics control. In order to solve this problem, a vehicle yaw stability control strategy was proposed based on robust model predictive control. First, the message delay characteristics of CAN network was analyzed, and a multicellular time-delay model was built to describe the parametric uncertainty. A robust model predictive controller containing uncertain parameters was designed to improve the anti-interference ability of the active safety controller. In addition, the comprehensive solution scheme of the variable time-domain robust optimal control law was also studied based on the asymptotically stable invariant ellipse set to improve the online solution efficiency, and meanwhile to balance the robustness and optimality of the system control. The results show that the proposed control strategy can resist the parameter uncertainty induced by the CAN network, alleviate the conservativeness of the robust control algorithm, and improve the active safety performance of the vehicle.