Prediction of LIN communication robustness against EFT events using dedicated failure models

Escudié, Frédéric; Caignet, Fabrice; Nolhier, Nicolas; Bafleur, Marise

doi:10.1016/j.microrel.2017.07.032

Cited by 1 publication

(1 citation statement)

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“…Is "…OR frequency simulators" meant?) Failure criteria could be added as described in paper [37]. The present document is set out as follows: following this introduction, the second section discusses the consideration of using frequency parameters to reproduce ESD protection behavior, even if such devices are non-linear.…”

Section: Introductionmentioning

confidence: 99%

Frequency Based Method Investigation to Extract an ESD Protection Dynamic SPICE Model From TLP Measurement

Escudié

Caignet

Nolhier

et al. 2022

IEEE Trans. Electromagn. Compat.

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In order to ensure reliability of systems early in the design phase, it is becoming crucial to have models able to predict the behavior of systems exposed to ElectroStatic Discharge (ESD). This is an increasing necessity since the number of embedded electronic products is growing and since they are employed in applications where people's safety is a requirement, such as automotive and aeronautic applications. Until now, quasi-static models of protection devices have succeeded in providing fairly good results in failure predictions (mainly hard failures). Today, the increased frequency range of such devices requires dynamic models able to reproduce their transient behavior. In this paper, we investigate if conventional methods for modeling linear devices, generally used in the frequency domain, could be used to obtain an equivalent frequency model for ESD protection devices, which exhibit non-linear behavior. A methodology to extract an ESD protection SPICE model from Transmission Line Pulse (TLP) measurements to address transient and frequency simulation is proposed and detailed. We demonstrate that, in well-defined conditions, such frequency models can give accurate results to predict overshoots related to protection device triggering delays. Validation of the models is performed under TLP and Human Metal Model (HMM) conditions on three off-the-shelf devices.

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Section: Introductionmentioning

confidence: 99%