摘 要

自从世界上第一辆汽车诞生以来，人们关于汽车领域的研究一直进行着。对于一个国家而言，汽车行业对社会发展有着举足轻重的作用。而在设计汽车的每个系统组成时，研究者们常常将重心放在汽车底盘系统上。汽车底盘由一个个系统构成，如转向系、制动系等。这些系统不仅影响着汽车的行驶性能，而且决定了车辆运行的安全性。同时，底盘系统对汽车各部件起着不可或缺的支承作用，是汽车其余系统的重要依托。悬架，作为底盘不能缺少的部分，其结构设计的合理与否更是与车辆的操纵和安全性能有很深的联系。因此，评定一辆汽车质量的高低，悬架的性能评估是一个重要的标准。本文的目的在于，以汽车悬架系统为讨论的对象，结合目前较为热门的虚拟样机技术，针对目前汽车悬架优化设计中面临的问题和难点，参考以往工作研究者的经验，引入实际的相关整车参数，提出一种有效可靠的悬架性能优化方法。

首先，展开了理论上的分析，寻找合适的优化目标。经过一系列的讨论，对比筛选车辆性能影响要素。通过列举前轮定位参数对汽车性能的影响，表述了它们之间的联系。同时，本章节还介绍了几种常用的优化算法。对比算法的优劣，选定粒子群算法，为最终优化做铺垫。

其次，基于ADAMS/Car的整车模型构建，为后续工作做好准备。在研究了各种汽车系统的几何结构、组件链接和运动特征的基础上，本文使用ADAMS/Car模块构建了虚拟的汽车模型。在仿真软件中将前悬架系统组装到虚拟试验台中，参照实验的流程，利用ADAMS软件推进之后的优化工作。

最后，基于ADAMS/Insight的具体优化过程，并且在结尾比对了实验结果，得出相应结论。完成双轮平行跳动仿真实验后，依据悬架特性确定有代表性的优化对象。设置好横纵轴的记录变量，便能得到优化目标在运动中的变化曲线。通过ADAMS/Insight的虚拟试验台功能，讨论了硬点坐标的灵敏度。根据实验结果，建立合适的响应面函数模型和最终目标函数，并且利用粒子群优化算法求得目标函数最优解。修改相关硬点，进行第二次双轮平行跳动实验。最后，两次仿真结果汇总到一起进行比较。结果表明，相应曲线的变化范围及趋势得到改善，表明优化后的悬架性能优于优化之前。证明本文技术路线和研究方法能够达到预期效果，为汽车悬架优化及算法应用提供了新的思路和方法。

关键词：悬架优化，ADAMS，响应面法，粒子群算法

Abstract

Since the birth of the first automobile in the world, people have been doing research on the field of automobile. For a country, the automobile industry plays an important role in social development. In the design of each composition, researchers often focus on the chassis. The car chassis is composed of systems, such as steering system, braking system, etc. These systems not only affect the driving performance of vehicles, but also determine the safety of vehicle operation. At the same time, the chassis plays an indispensable supporting role for all parts of the car and is an important support for the rest of the car. Suspension, as an indispensable part of chassis, is closely related to the vehicle's handling and safety performance. Therefore, the performance evaluation of suspension is an important standard to evaluate the quality of a car. The purpose of this paper is to take the suspension system as the object of discussion, combined with the current popular virtual prototyping technology, aiming at the problems and difficulties in the optimization design of suspension. Referring to the experience of previous researchers, the paper introduces the actual relevant vehicle parameters, and proposes an effective and reliable suspension performance optimization method.

First of all, the theoretical analysis is carried out to find the appropriate optimization objectives. After a series of discussions, the influencing factors of vehicle performance are compared and screened. By listing the influence of front wheel alignment parameters on vehicle performance, the relationship between them is expressed. At the same time, this chapter also introduces several commonly used optimization algorithms. Comparing the advantages and disadvantages of the algorithm, particle swarm optimization algorithm is selected to pave the way for the final optimization.

Secondly, the whole vehicle model is built based on ADAMS / car to prepare for the follow-up work. Based on the study of the geometry, component links and motion characteristics of various automotive systems, this paper uses Adams / car module to build a virtual vehicle model. In the simulation software, the front suspension system is assembled into a virtual test.bed. Referring to the experimental process, ADAMS is used to promote the optimization work.

Finally, based on the specific optimization process of ADAMS / insight, and at the end of the comparison of the experimental results, the corresponding conclusions are drawn. After completing the simulation experiment of two wheel parallel run out, the representative optimization object is determined according to the suspension characteristics. By setting the recording variables of the horizontal and vertical axis, the curve of the optimal target in motion can be obtained. The sensitivity of hard point coordinate is discussed through the virtual test.bed function of ADAMS / insight. According to the experimental results, the appropriate response surface function model and the final objective function are established, and the optimal solution of the objective function is obtained by particle swarm optimization algorithm. Modify the relevant hard points, and carry out the second double wheel parallel run out experiment. Finally, the two simulation results are summarized and compared. The results show that the change range and trend of the corresponding curve are improved, which shows that the optimized suspension performance is better than that before. It is proved that the technical route and research method in this paper can achieve the expected effect, and provide a new idea and method for the optimization and algorithm application of automobile suspension. 

Key words: suspension optimization, ADAMS, response surface method, particle swarm optimization algorithm

目 录

摘要 I

Abstract II

第1章 引言 1

1.1 研究背景与意义 1

1.1.1 研究背景 1

1.1.2研究意义 1

1.2 国内外研究现状 2

1.2.1 汽车悬架设计研究 2

1.2.2悬架的优化研究 3

1.2.3 悬架优化算法研究 4

1.3研究内容与研究方法 5

1.3.1 研究内容 5

1.3.2 研究方法 6

1.3.3 技术路线 6

第2章 汽车操纵稳定性分析及算法介绍 7

2.1 汽车操纵稳定性的影响因素 7

2.1.1 悬架运动学分析 7

2.1.2 车轮定位参数介绍 7

2.2 优化算法介绍 9

2.3 本章小结 10

第3章 基于虚拟样机技术的整车模型搭建 11

3.1 虚拟样机技术 11

3.2虚拟样机技术关于整车建模的应用 11

3.2.1 前悬架系统 12

3.2.2 后悬架系统 14

3.2.3 转向系统 15

3.2.4前后轮胎系统 16

3.2.5 其他子系统 17

3.2.6 整车模型 18

3.3 本章小结 19

第4章 麦弗逊前悬架优化及优化前后对比 21

4.1 麦弗逊前悬架仿真实验 21

4.1.1 车轮外倾角和车轮跳动量关系曲线及分析 22