| 基于RBF网络的轮胎侧向力模型 |
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| 引用本文： | 张国林,谢伟东. 基于RBF网络的轮胎侧向力模型[J]. 浙江工业大学学报, 2005, 33(2): 203-205 |
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| 作者姓名： | 张国林 谢伟东 |
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| 作者单位： | 浙江工业大学,机电工程学院,浙江,杭州,310032 |
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| 摘 要： | RBF神经网络相对于其他网络的特点是计算量小,收敛速度快,具有良好的非线性映射效果.采用人工神经网络中的径向基函数(RBF)神经网络,对车辆操纵稳定性仿真分析中的轮胎侧偏特性进行研究,建立轮胎侧向力神经网络模型.并与用于学习的实验数据进行比较,以验证这种模型的准确性,并以求为车辆动力学仿真和控制提供更好的手段.
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| 关 键 词： | RBF神经网络 轮胎侧向力 模型 |
| 文章编号： | 1006-4303(2005)02-0203-03 |
| 修稿时间： | 2004-09-10 |
The tire side-force model based on RBF neural network |
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| ZHANG Guo-lin,XIE Wei-dong. The tire side-force model based on RBF neural network[J]. Journal of Zhejiang University of Technology, 2005, 33(2): 203-205 |
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| Authors: | ZHANG Guo-lin XIE Wei-dong |
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| Abstract: | Low calculating amounts, fast convergence speed and good nonlinear mapping ability are three advantages of RBF neural network. In this paper, the RBF neural network is used to study the side-force characteristics of vehicle tires. The tire model can be applied to the simulation and analysis of vehicle handling and stability. This article established the side-force neural network model of tire and compared with experimental data for the purpose of validating the accuracy of the model. The aim is to provides more suitable method for the simulation of vehicle dynamics and control. |
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| Keywords: | RBF neural network side-force model |
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