云辅助半主动悬架控制

Zhaojian Li, I. Kolmanovsky, E. Atkins, Jianbo Lu, Dimitar Filev, J. Michelini
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引用次数: 42

摘要

本文从V2C2V (vehicle -to- cloud -to- vehicle)分布式实现的角度考虑汽车悬架控制问题。基于半主动悬架动力学的线性四分之一小车模型,研究了该问题的简化形式。道路干扰被建模为一个已知的道路轮廓,一个未测量的随机道路轮廓和坑洞的组合。当车辆撞击凹坑时,悬架响应被建模为车轮速度的脉冲变化,其大小与凹坑和车辆的物理特性有关。考虑了基于路面轮廓数据从有限阻尼模式中选择最优阻尼模式的问题。信息流和V2C2V实现是基于在车辆和云之间划分计算和数据来定义的。给出了一个仿真实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cloud aided semi-active suspension control
This paper considers the problem of vehicle suspension control from the perspective of a Vehicle-to-Cloud-to-Vehicle (V2C2V) distributed implementation. A simplified variant of the problem is examined based on the linear quarter-car model of semi-active suspension dynamics. Road disturbance is modeled as a combination of a known road profile, an unmeasured stochastic road profile and potholes. Suspension response when the vehicle hits the pothole is modeled as an impulsive change in wheel velocity with magnitude linked to physical characteristics of the pothole and of the vehicle. The problem of selecting the optimal damping mode from a finite set of damping modes is considered, based on road profile data. The information flow and V2C2V implementation are defined based on partitioning the computations and data between the vehicle and the cloud. A simulation example is presented.
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