基于模型的车载分散嵌入式诊断:在智能距离保持功能中的应用

Othman Nasri, H. Shraim, P. Dague, O. Héron, M. Cartron
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引用次数: 8

摘要

提出了一种故障诊断策略在分布式智能测距(SDK)系统中的部署。该SDK系统是自适应巡航控制(ACC)系统的高级版本,已在雷诺-沃尔沃卡车上实施。这项工作的主要目标是分析从SDK元素发出的测量值,以便检测、定位和识别可能产生的一些故障。我们的主要贡献是提出了一种分散的方法,允许在不计算全局模型的情况下进行在线诊断,并将其部署在几个控制单元上。本文介绍了基于模型的分散式诊断方法及其在5个控制单元通过can总线连接的卡车车载SDK系统的嵌入式诊断中的应用。我们还讨论了必须满足的约束条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-based decentralized embedded diagnosis inside vehicles: Application to Smart Distance Keeping function
In this paper, the deployment of a fault diagnosis strategy in the Smart Distance Keeping (SDK) system with a decentralized architecture is presented. The SDK system is an advanced version of the Adaptive Cruise Control (ACC) system, implemented in a Renault-Volvo Trucks vehicle. The main goal of this work is to analyze measurements, issued from the SDK elements, in order to detect, to localize and to identify some faults that may be produced. Our main contribution is the proposition of a decentralized approach permitting to carry out an on-line diagnosis without computing the global model and to deploy it on several control units. This paper explains the model-based decentralized solution and its application to the embedded diagnosis of the SDK system inside truck with five control units connected via a CAN-bus using ”Hardware In the Loop” (HIL) technique. We also discuss the constraints that must be fulfilled.
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