摘要：列车动力学研究是对列车机车和车辆动力学性能进新货检验的一项重要实验。无论是对于新研发列车还是对改进的列车都要进行动力学研究，获取动力学性能指标，为检验和改进列车提供科学依据。在查阅了与列车动力学有关的资料之后，提出了以单质点列车运动仿真模型为基础的列车运行优化方案，该优化方案的核心思想是通过将列车的区间运行过程描在满足时间、距离和速度的这些限制条件的情况下，以牵引、惰行和制动为实验工况，最终达到能够优化列车运行的力学与数学的双重问题。由于该优化问题属于非线性优化问题，因此无法采用传统的方法进行求解。本课题主要采用粒子群优化算法，粒该算法的优势在于能够可以处理传统方法所不能处理的问题。可以处理一些时时数据变化的问题。同时通过MATLAB算例证明了该方法的可行性。49725

毕业论文关键词 ：列车动力学 ；单质点模型 ；粒子群优化 ；MATLAB

Train Simulation Experiment Based on Dynamic Model

Abstract: The research of the train dynamics is an important experimental train locomotive and vehicle dynamic performance test of the replacements. For the new research and development of the train or to improve the train to carry out a dynamic study, to obtain its dynamic performance indicators, to provide a scientific basis for the inspection and improvement of the train. After consulting and train dynamics related information, put forward to elemental train movement simulation model for train operation based optimization scheme, the core idea of the optimization scheme is the range of train operation process description to meet the time, distance and speed of these restrictions, traction, coasting and braking for the experimental conditions, and ultimately achieve to optimize the dual problems of mechanics and mathematics of train operation. Because the optimization problem is a nonlinear optimization problem, the traditional method can not be used to solve the optimization problem. This topic mainly uses the particle swarm optimization algorithm, the advantage of this algorithm is that it can deal with the problem that the traditional method can not deal with. Can deal with some of the problems from time to time data changes. The feasibility of this method is proved by the example of MATLAB.

 Key Words ：train dynamics；single particle model；particle swarm optimization；MATLAB

 目  录

1绪论 1

1.1研究本课题的目的 1

1.2国内外研究现状与水平 1

1.3当今轨道交通的特点 3

1.4发展趋势 4

1.5本文重点研究内容 5

2列车动力学模型 6

2.1列车运行过程建模 6

2.2牵引力 7

2.3列车阻力 8

2.4列车运行策略优化问题建模 9

2.5工况序列 9

3智能优化算法介绍 11

3.1智能优化算法 11

3.2粒子群算法的简介 12

3.3与遗传算法的比较 13

3.4参数设置 15

3.5粒子群算法的优势和缺陷 15

4程序设计 16

4.1列车运行过程建模