Suspension Test System Based on Modified Elman Neural Network

Abstract

Abstract:

An improved Elman neural network controller was established, which could meet multi network and multi order system. A programmable automation controller(PAC) controller was established based on modified Elman neural network, and was used to the 6-DOF suspension system test platform control; the effects of suspension parameters on wheel load utilization ratio and phase angle were analyzed. The results show that the matching of the suspension parameters can improve body vibration, reduce the suspension dynamic deflection and tire dynamic load.

Key words: vehicle suspension, 6-DOF, test system, neural network

摘要：

提出了一种能满足多层网络、多阶系统的改进型Elman网络，建立了基于改进Elman神经网络的PAC控制器。对六自由度悬架试验平台系统进行了控制研究，分析了悬架参数对轮荷利用率和相位角的影响。整车实验证明：参数匹配的悬架可以有效减小车身振动，降低悬架动挠度和轮胎动载荷。

关键词: 悬架, 六自由度, 试验系统, 神经网络

CLC Number:

U467.5

宋崇智, 赵又群. 基于改进Elman神经网络的悬架试验系统[J]. 中国机械工程, 2016, 27(01): 1-6.

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