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基于随机路面识别的半主动悬架控制策略研究
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Abstract:
为了解决半主动悬架系统存在的时滞问题，本文提出一种基于随机路面识别和半主动悬架控制技术相结合的智能悬架控制方法。目前量产车型配置的半主动悬架系统一般有三种模式：舒适、标准及运动。每种模式是由驾驶员根据不同路况进行选择，导致了半主动悬架系统使用的局限性，不能对工况进行自适应控制。本文通过构建卷积神经网络对随机路面进行分类识别，将识别的路面不平度信息提前反馈给半主动悬架控制器，可以满足不同路况下的自适应悬架控制，并通过整车道路实验验证了所提算法的有效性。
To solve the time-delay problem of semi-active suspension system, an intelligent suspension control method based on the combination of random road surface identification and semi-active suspension control technology is proposed. At present, there are three modes of semi-active suspension system configured for mass production vehicles: comfort, standard and sport. Each mode is selected by the driver according to different road conditions, which leads to the limitation of semi- active suspension system, and cannot adaptively control the working conditions. In this paper, a convolutional neural network is constructed to classify and identify random road surfaces. The identified road roughness information is fed back to the semi-active suspension controller in advance, which can meet the adaptive suspension control under different road conditions. The effectiveness of the proposed algorithm is verified by vehicle road experiments.
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