首页> 外文会议>Proceedings of the 2012 IEEE 18th International Mixed-Signals, Sensors and Systems Test Workshop >Hierarchical Modeling of Automotive Sensor Front-Ends for Structural Diagnosis of Aging Faults
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Hierarchical Modeling of Automotive Sensor Front-Ends for Structural Diagnosis of Aging Faults

机译:汽车传感器前端的分层建模,用于老化故障的结构诊断

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The semiconductor industry for automotive applications is growing rapidly. This is because advanced electronics is now being developed to monitor and control many vital functions previously handled purely mechanical. In addition hybrid and pure electrical cars are emerging. Parts of these electronic systems have strict safety-critical requirements, while operating in a harsh environment. Although functional diagnosis is currently the norm, many occurring faults during lifetime, e.g. due to aging, cannot be diagnosed. This poses serious threats during operation as correction for dependability is not possible in this case. This suggests the introduction of structural diagnosis techniques. Major problem is that a number of different hierarchies have to be considered and reuse of reliability data at different hierarchies should be possible. This paper investigates a new approach for the development of dependable analogue/mixed-signal car front-ends, by interfacing aging models between different hierarchies enabling structural diagnosis, and explicitly using simultaneously design and simulation data as well as built-in observation measurements at all hierarchies.
机译:用于汽车应用的半导体行业正在迅速发展。这是因为现在正在开发先进的电子设备,以监视和控制以前纯粹由机械处理的许多重要功能。此外,混合动力和纯电动汽车也正在兴起。这些电子系统的某些部分在苛刻的环境中运行时具有严格的安全关键要求。尽管目前功能诊断是很普遍的方法,但在生命周期内仍会发生许多故障,例如由于老化,无法诊断。由于在这种情况下无法进行可靠性校正,因此在操作期间会构成严重威胁。这建议引入结构诊断技术。主要问题是必须考虑许多不同的层次结构,并且应该有可能在不同的层次结构上重用可靠性数据。本文研究了开发可靠的模拟/混合信号汽车前端的新方法,方法是将不同层次之间的老化模型连接起来,以进行结构诊断,并明确同时使用设计和仿真数据以及内置的观测测量值。层次结构。

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