摘要
为了改善分布式驱动电动汽车在低附着路面行驶、高速转向等极限工况下的主动安全性,本文提出了一种基于预测控制的动力学集成控制方法。首先,为了均衡预测模型的建模精度与控制器的计算负担,通过分段仿射将非线性横摆动力学模型进行简化,进而建立了混杂系统预测模型。其次,分析了多时变参数系统的失稳机理,将系统发生分岔现象后极易失稳的工况定义为极限工况,统一了低附着、高速等不同极限工况下的车辆稳定性判别方法,制定了控制模式的切换机制。然后,提出了基于鲁棒混杂模型预测控制算法的动力学集成控制策略,系统地考虑了极限工况下的车速变化与轮胎非线性侧偏特性,协同优化了车辆的驱动防滑性能、横摆稳定性等安全性指标。处理器在环试验表明,提出的集成控制策略能够满足低附着路面行驶与高速转向工况的控制需求,显著提高了车辆在极限工况下的主动安全性。
In order to improve the active safety of four-wheel independent drive electric vehicles under extreme conditions such as low adhesion road driving and high-speed steering,a predictive control-based dynamic integrated control method is proposed in this paper.Firstly,in order to balance the modeling accuracy of the prediction model and the computational burden of the controller,the nonlinear yaw dynamic model is simplified by a piecewise affine approximation,and then the prediction model of the hybrid system is established.Secondly,the instability mechanism of the multi-time-varying parameter system is analyzed.The maneuvers with bifurcation are defined as the extreme conditions,and the unified vehicle stability judgement method for different extreme conditions such as low adhesion and high speed is developed to determine the switching mechanism of the control mode.Then,the integrated dynamic control strategy based on the robust hybrid predictive control algorithm is proposed,which systematically considers the vehicle speed variation and tire nonlinear lateral deflection characteristics under the extreme conditions,and coordinately optimizes the anti-skid performance,yaw stability and other safety indexes.The processor-in-the-loop test shows that the proposed integrated dynamic control strategy can meet the control requirements of low adhesion road driving and high-speed steering conditions,and significantly improve the active safety of the vehicle under extreme conditions.
作者
林程
梁晟
宫新乐
于潇
汪博文
Lin Cheng;Liang Sheng;Gong Xinle;Yu Xiao;Wang Bowen(Beijing Institute of Technology,National Engineering Research Center for Electric Vehicles,Beijing 100081;Collaborative Innovation Center of Electric Vehicles in Beijing,Beijing 100081;School of Vehicle and Mobility,Tsinghua University,Beijing 100084)
出处
《汽车工程》
EI
CSCD
北大核心
2022年第9期1372-1385,共14页
Automotive Engineering
基金
国家自然科学基金(51975049)资助。
关键词
分布式驱动电动汽车
极限工况
车辆动力学控制
模型预测控制
four-wheel independent drive electric vehicles
extreme maneuver
veicle dynamic control
model predictive control
