【作者】 鲍佳；

【导师】 张昆仑；

【作者基本信息】 西南交通大学 ， 电力电子与电力传动， 2003， 硕士

【摘要】 论文在德国航空航天局开发的SIMPACK多体系统仿真平台上，以青城山试验示范线和上海TR08实际工程情况为研究背景，根据实际结构情况建立了参数化的磁浮列车及其磁浮线路的仿真模型。 论文的主要工作是建立含悬浮导向主动控制环节的模块化仿真系统结构，研究悬浮导向系统控制方法与控制参数对磁浮列车动力学性能的影响。因为磁悬浮列车与轨道无接触，而轨道又往往采用高架桥梁，所以其动力学特性比起传统轮轨列车要复杂得多，主要有悬浮、导向稳定性和车轨耦合振动等问题。因此在建模及仿真分析中侧重针对悬浮控制器的研究，先建立简化悬浮系统模型，然后考虑刚性车体、刚性但轨道有激扰的模型，最后建立刚性车体、弹性轨道梁和悬浮导向控制系统的综合模型。 磁浮列车的多磁铁悬浮系统实质上是一个多输入、多输出的相关控制系统，但是现在的磁浮列车车辆一般采用模块化结构，而且二次悬挂弹簧的刚度系数较小，可以实现机械解耦，所以在控制系统中，往往采用分散控制的方法。这使得单铁控制有研究的意义。 用于磁浮列车控制的方法很多，从状态反馈控制、PID调节等经典控制技术到状态观测器等现代控制技术都能够达到稳定控制的结果，但是不同方法的有效性、直观性和简便性却不尽相同。另外，控制系统本身有很多的非线性因素，所以选择合理的控制规律也很重要。 论文首先在数学建模的基础上，根据实际情况，详细分析对比了直接状态反馈控制、PID控制和状态观测器控制等常用的磁浮列车悬浮控制方法，然后将合适的控制规律及优化的控制参数用于SIMPACK中的多体模型，通过计算，给出悬浮稳定性、运行平稳性以及列车曲线通过等动力学特性曲线。 目前，国内主要致力于中低速磁浮列车的研制工作，另外，在上海引进德国技术建成了世界第一条高速磁浮商业线。磁浮列车的多体动力学仿真对研究控制方法的可行性有很一定的指导意义，对目前世界上最先进的常导磁浮列车的技术充分消化吸收也有重要的意义，使国内对高速或中低速常导磁浮列车的结构、性能、运行特点、关键技术有深刻的认识，为自主发展磁浮列车事业创造有利条件。更多还原

【Abstract】 In this thesis, a parameterized maglev train and maglev rail models have been set up in SIMPACK. These models are based on real information of the QIINGCHENG test maglev rail and TR08 in Shanghai. The SIMPACK is a kinematics and dynamics simulation software with multi-body system.The main content of this thesis is to set up modularized simulation system structures which include active control sections of maglev. Then research of the influence of dynamic characters through different control methods and different control parameters in suspension controlled system is carried out by simulating. The maglev train do not contact with guide way, and generally trestles are used as levitation guide way, so the dynamics character of maglev is more complex than that of traditional wheel-rail. The main problems include stability of suspension and guidance control and coupled vibration of vehicle-rail. The purpose of simulation is to research the infects of control system. Thus we need set up a simpelized model of magnetic suspension system at first. Then we should think about models with rigid bodies and rigid but excited railway and at last to set up integrate models with rigid vehicle , elastic guide way beam and control system of suspension and guidance.The multi-magnet suspension system of maglev is a multi-input and multi-output correlation control system in essential. But generally, the structure of modern maglev vehicle is modularized, and the spring stiffness of the second suspension is small, such structure can resolve mechanistic coupling of vehicle. So the methods of separate control are used very common in maglev suspension control systems. And this gives very important meaning to research on single magnetic suspension system.There are many different methods can be used into maglev control system. In those methods , state feedback and PID are used as of a traditional way while states observer and some other methods are used as modern methods. Different methods can result different control characters. Forthermore, because of non-linear factors exist in control system, it is very important to decide how to choose a propriety control law.In this thesis, based on mathematic model and real condition , analysis and compare of different control methods are carried out at first. Then a propriety control law and optimized parameters are choosen and used into multi-body model in SIMPACK. Finally, kinds of dynamic character curves after measurement and calculation are given.Nowadays, the main research object of maglev in China is middle and low speed EMS maglev. And the first high-speed commercial maglev system which uses all technology from Germany has been finished in Shanghai.Therefor the Multi-body Kinematics and dynamics simulation of maglev have important meaning in our maglev industry. In one hand, it can give some directions in research of control methods. In another hand, it can make us know about the structure, character, move performance and key technology of the most modern maglev in the world. Then we can study and absorb it and create advanced condition for developing national maglev in our country.更多还原