汽车动力学稳定性横摆力矩和主动转向联合控制策略的仿真研究
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摘要
现代汽车的发展趋势是“安全、节能、环保”,汽车主动安全性问题是影响道路交通安全状况的一个重要方面,而汽车稳定性控制系统是提高汽车主动安全性的有效措施,也是当前国内外的研究热点。本文针对汽车在转弯工况下的行驶和制动稳定性,利用横摆力矩和主动转向控制技术进行汽车稳定性控制,结合模糊控制和Fuzzy-PID控制理论,确定相关的控制策略和控制算法,对两种控制模式单独控制和联合控制机理进行了研究,为提高汽车稳定性集成控制提供了一定的研究思路。
     论文从车辆动力学的本质出发,在已有的轮胎实验数据基础上,利用神经网络方法得到轮胎力模型的多维空间特性曲面,分析了汽车在转弯制动时轮胎垂直载荷和侧偏角变化对制动力的影响,提出了根据特性曲面寻求轮胎最佳滑移率的控制策略,并对汽车弯道制动状况进行了仿真研究,验证了汽车弯道制动滑移率最优控制策略相比滑移率固定制动具有更好的制动效果。
     针对汽车在转弯制动时出现的侧向路径偏离状况,根据偏离量大小,利用横摆力矩和主动转向两种控制模式分别进行汽车制动稳定性控制,确立了两种控制模式下的控制策略和控制算法,设计了模糊控制器,根据轮胎最优滑移率变化状况,对模糊输出变量论域的大小按照动态比例系数进行实时在线调整,仿真实验验证了所提出的基于横摆力矩和前轮主动转向的模糊控制方法能提高汽车制动稳定性和路径跟踪能力。
     依据非线性轮胎模型和整车动力学模型,分析了横摆力矩和前轮主动转向控制模式对汽车过多和不足转向的控制特性,选择鲁棒性强的非线性Fuzzy-PID控制技术进行汽车稳定性控制,设计了Fuzzy-PID控制器,利用汽车理想模型的横摆角速度和质心侧偏角作为控制系统跟踪对象,车轮制动力和前轮叠加转角作为控制输出,以轮胎最优滑移率控制方法进行横摆力矩稳定性控制,以前轮叠加转向进行主动转向控制,按照两种控制模式各自的控制策略分别进行了仿真实验,验证了Fuzzy-PID控制系统能使汽车具有良好的操纵稳定性。
     针对横摆力矩和主动转向控制方法联合控制时的耦合作用,采用对两个子控制系统进行协调控制来提高整车性能,提出了前馈和反馈相结合的控制策略来跟踪理想模型,依据两种控制模式不同的适用工况,设计了联合控制双模糊控制器,确定了子控制系统之间的协调控制策略和切换逻辑;以横摆角速度和质心侧偏角作为控制器输入,以车轮制动力和前轮叠加转角作为控制器输出,通过调节双模糊控制器之间的权重系数来平衡控制系统的联合控制效能;对汽车角阶跃输入和变车道输入工况下的稳定性控制进行了仿真,并利用李雅普诺夫和相平面法研究了控制系统的稳定性,对控制系统进行了李雅普诺夫离散化分析。仿真结果表明,通过子控制系统之间的有机协调,联合控制可实现各子系统之间的功能互补,使汽车操纵稳定性得到较大程度的改善。
     本文的研究属于汽车动力学控制领域的较前沿课题。通过对汽车稳定性控制进行相关的研究,可以提高汽车的行驶安全性和操纵稳定性,为汽车稳定性联合控制的实际应用打好理论基础,对于促进汽车动力学控制技术的发展具有一定的作用。
The development trends of modern vehicle are "safety,energy saving and environmental protection", among them, vehicle active safety is an important aspect which influents road traffic safety. The effective way to improve vehicle active safety is to carry out the research on vehicle stability control and it is the international research focus in the field at present. Based on the analysis of vehicle driving and braking stability on large turn, the dissertation studies the technology of vehicle stability control by way of yaw moment and active steering separately. On the basis of the theories of fuzzy and Fuzzy-PID control, the corresponding control strategies and control algorithms are determined, and the mechanisms of separate and combined control by the two methods are also studied. The research fruits provide a certain train of thought to integrated control of vehicle stability.
     The dissertation begins with the nature of vehicle dynamics. On the basis of the existing experimental data of tyre, the multi-dimensional characteristic curved surface of neural network tyre force model is got, the influence of variations of vertical load and side slip angle of tyre on braking force is analyzed, the control strategy of finding tyre optimum slip rate according to characteristic curved surface is put forward and the simulation of vehicle braking condition on a turn is made. The simulation results show the control strategy of optimum slip rate has better braking effect than that of constant slip rate.
     To the condition of deviation from side path when vehicles are turning and braking, according to the deviation distance, the control strategies and control algorithms of vehicle braking stability by two control methods, yaw moment and active steering, are determined. The fuzzy controller are designed whose outputs can be adjusted online according to the variation of slip rate and dynamic proportionality factor. The simulation results prove that the method of fuzzy control which is based on the yaw meoment and front wheel active steering can improve vehicle braking stability and ability of path tracking.
     Based on the models of unlinear tyre and full vehicle dynamics, the characteristics of the control methods of yaw moment and front wheel active steering under the conditions of excessive vehicle and less steering are analyzed. The technology of unlinear Fuzzy-PID with robustness for vehicle stability control is selected. The Fuzzy-PID controllers are designed whose tracking objects are ideal yaw rate and side slip angle and the outputs are wheel braking force and front wheel steering angle. The simulation experiments by two methods, yaw moment stability control which is based on the optimum slip rate of tyre and active steering control that is based on front wheel nestification, are carried out. The results prove that the vehicles applied Fuzzy-PID control have good performance stability.
     To the coupling function of the combined control by yaw moment and active steering, coordination between two control sub-systems is required to improve the performance of the full vehicle. The control strategy of feedforward combined with feedback is applied to track the ideal model. According to the working conditions by two different control methods, the double fuzzy controller for combined control is designed and the coordination control strategy and switch logic between sub-systems are determined. The combined control performances between sub-systems are balanced by adjusting the weight coefficient of the double fuzzy controller whose inputs are yaw rate and side slip angle and outputs are wheel braking force and front wheel steering angle. The simulation of vehicle stability control under conditions of angle step input and variable lane input is made, the stabilities of control sub-systems are analyzed by way of Lyapunov and phase plane and Lyapunov discretization analyses of the control sub-systems are made. The results show from coordinating between control sub-systems, the combined control can realize complementation of the functions between sub-systems and improve vehicle performance stability to a higher level.
     The research in the dissertation is a front subject in the control field of vehicle dynamics. Studies of vehicle stability control can improve vehicle driving safety and performance stability, provide theoretical basis for combined control of vehicle stability and prompt the development of control technology of vehicle dynamics.
引文
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