A New Scheme for Semi-active Suspension Control based on BP Neural Network Model of Magnetorheological Damper

Honghui Zhang, Zhiyuan Zou, Hang Su
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Abstract

Magnetorheological (MR) controllable damping is promising in suspension control and almost commercialized in luxuries. However, the development of MR semi-active control for vehicles is complicated because of the messed interdisciplinary process both in the suspension control and the MR damper control. In this paper, a new scheme of driving control based on BP neural network is proposed to package the MR damper as a black box implementing the strong nonlinearity mapping between the excitation current and damping force by the embedded driver. The sensor also embedded in the MR damper for integrated solution, and a mechanism for tackling the sedimentation problem of the MR damper are also pointed out.
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基于BP神经网络模型的磁流变减振器半主动悬架控制新方案
磁流变阻尼技术在悬架控制领域具有广阔的应用前景,在奢侈品领域已基本实现商业化。然而,由于悬架控制和磁流变阻尼器控制的交叉交叉,使得车辆磁流变半主动控制的发展十分复杂。本文提出了一种基于BP神经网络的驱动控制新方案,将磁流变阻尼器封装成一个黑匣子,通过嵌入式驱动器实现励磁电流和阻尼力之间的强非线性映射。将传感器嵌入到磁流变阻尼器中进行集成解决,并提出了解决磁流变阻尼器沉降问题的机理。
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