基于模型分解的车辆稳定控制算法研究

发布时间：2018-05-21 19:46

本文选题：汽车电子 + 模型分解　；参考：《吉林大学》2016年硕士论文

【摘要】：近年来,与汽车有关的各项技术发展迅速,其中汽车电子控制更是发展的主攻方向。车辆稳定性控制作为汽车电子控制中的一个环节,由于其在保障车辆稳定行驶方面起到的积极作用而受到了极大关注。车辆稳定性控制系统是一种主动安全系统,可以有效地提高车辆运行的稳定性,防止侧翻、侧滑及转向过度和转向不足等危险情况发生,从而保证人身安全。本文主要研究如何保持车辆稳定运行的问题。论文主要分为两个部分:上层稳定控制器的设计和下层分配控制器的求解。上层稳定控制器设计目的是在保证车辆的运行状态跟踪上期望的纵向速度、侧向速度、横摆角速度、侧倾角及其速度的前提下,确定车辆的侧向合力、纵向合力以及横摆力矩。此时虽然保证了车辆的稳定运行,但车辆所受合力(矩)并不能直接被控制,因此设计了下层分配控制器,对侧向合力,纵向合力和横摆力矩进行分配,得到每个轮子上的纵向力和侧向力,再进一步得到能提供相应纵向力和侧向力的车轮力矩,实现对车辆的稳定性控制。本文中车辆稳定控制系统的作用过程实际上是以上分析的逆过程,即通过控制各车轮的力矩得出各轮的受力情况,间接实现对车辆侧向合力、纵向合力以及横摆力矩的控制,最终实现对车辆纵向速度、侧向速度、横摆角速度、侧倾角及其速度的控制,保证车辆稳定运行。本文的主要内容及贡献如下:(1)针对四自由度整车模型,提出一种模型分解方法,将原有整车模型分解成两个部分,分别为1)速度横摆模型;2)侧倾模型。这样,每部分模型包含的控制量较整车模型减少,便于对每一部分单独设计控制器。同时整体控制量并没有变化,这样既降低了对车辆模型分析的难度又保证了控制精度。(2)对两个子模型进行处理,实现两个目标:1)去除模型中的非线性部分,2)使控制过程更加严谨。具体方式是:1)侧倾模型通过近似处理去除非线性因素,2)速度横摆模型通过反馈线性化去除非线性因素后,在此线性模型中加入模型不确定性因素,原因是通过反馈方式完全去除非线性部分是一种理想状态,不可避免的存在残余量,此外四自由度模型本身不精确,实际被控车辆更复杂。(3)对车辆的两个子模型分别设计控制器:1)速度横摆模型,设计考虑参数不确定性的次优控制器;2)侧倾模型,设计线性二次型最优控制器。通过保持整车运行的稳定性得到控制器的输入量:纵向力、侧向力以及横摆力矩。(4)将在控制器中得到的合力(矩)分配到每个车轮的执行器上,通过引入伪逆的方法得到保证车辆稳定运行的各车轮纵向力和侧向力,在此基础上,由车轮的动力学方程进一步确定了每个车轮所需提供的力矩,最终实现了直接控制车轮力矩来保持车辆的稳定运行。(5)分别在四自由车辆模型和AMESim十五自由度车辆模型上验证本文设计的车辆稳定控制系统作用效果,结果表明此系统对以上两种模型都有很好的控制性能。在高自由度车辆模型上良好的控制效果证明此车辆稳定控制系统在工程实践中具有积极意义。上述提出的方法及数据结论,将为车辆稳定性控制研究工作提供参考。
[Abstract]:In recent years, automobile related technologies have developed rapidly, and automotive electronic control is the main direction of development. Vehicle stability control, as a part of automotive electronic control, has been greatly concerned because it plays an active role in guaranteeing the stable driving of vehicles. Vehicle stability control system is a kind of initiative. Safety system can effectively improve the stability of vehicle operation, prevent side rollover, sideslip and overturn and lack of steering and so on, so as to ensure the safety of the person. This paper mainly studies how to keep the stable running of the vehicle. The thesis is divided into two parts: the design of the upper stability controller and the lower layer distribution controller The purpose of the upper stability controller is to determine the lateral force, the longitudinal force and the yaw moment of the vehicle on the premise of tracking the desired longitudinal velocity, lateral velocity, yaw rate, yaw angle and speed. While maintaining the stable operation of the vehicle, the resultant force (moment) of the vehicle is guaranteed. It can not be directly controlled, so the lower layer distribution controller is designed to distribute the lateral force, longitudinal force and yaw moment, get the longitudinal force and lateral force on each wheel, and then get the wheel torque which can provide the corresponding longitudinal force and lateral force, so as to realize the stability control of the vehicle. The function process of the system is in fact the reverse process of the above analysis, that is, by controlling the torque of each wheel, the force condition of each wheel is obtained, and the control of the lateral force, longitudinal force and yaw moment of the vehicle is realized indirectly, and the control of the longitudinal velocity, lateral velocity, yaw rate, side tilt angle and speed of the vehicle is finally realized, so as to ensure the stability of the vehicle. The main contents and contributions of this paper are as follows: (1) according to the four degree of freedom vehicle model, a model decomposition method is proposed to decompose the original vehicle model into two parts, 1) the speed yaw model, and 2) the side tilt model. In this way, the control quantity of each part is less than the whole vehicle model, so that each part is easily designed and controlled. At the same time, the overall control amount has not changed, which not only reduces the difficulty of the vehicle model analysis but also ensures the control precision. (2) the two sub models are processed to achieve two objectives: 1) to remove the nonlinear part in the model, 2) to make the control process more rigorous. The body mode is 1) and the lateral tilt model removes the nonlinearity by approximate treatment. Factors, 2) the speed yaw model, after the nonlinear factor is removed by feedback linearization, is added to the model uncertainty factor in this linear model. The reason is that it is an ideal state to completely remove the nonlinear part by feedback, and the four degree of freedom model itself is inaccurate, and the actual controlled vehicle is more complex. (3) for the two sub models of the vehicle, the controller is designed respectively: 1) the speed yaw model, the design of the sub optimal controller considering the parameter uncertainty; 2) the lateral tilt model and the design of the linear two optimal controller. The input of the controller is obtained by maintaining the stability of the whole vehicle operation: the longitudinal force, the lateral force and the yaw moment. (4) will be in the controller. The resultant force (moment) is assigned to the actuator of each wheel. By introducing the pseudo inverse method, the longitudinal forces and lateral forces of the wheels to ensure the stable operation of the vehicle are obtained. On this basis, the torque required by each wheel is further determined by the dynamic equation of the wheel, and the wheel torque is finally controlled to maintain the vehicle. (5) verify the effect of the vehicle stability control system based on the four free vehicle model and the AMESim fifteen degree of freedom vehicle model respectively. The results show that the system has good control performance for the above two models. The good control effect on the high degree of freedom vehicle model proves the stability control system of the vehicle. The above method and data conclusion will provide reference for vehicle stability control research.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.6

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