Reliability Analysis using Advanced Modeling Technique for MEMS Microphone

Shubham, Shubham; Song, Xin; Ma, Yunfei; Silva, Mark G. Da; Guo, Zhixin; Johnson, J. E.; Pedersen, Michael

doi:10.1109/ipfa53173.2021.9617295

Cited by 3 publications

(1 citation statement)

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“…It also enables the simulation of microphone`s sensitivity, noise and THD at different bias voltages. The large signal non-linear model can also be utilized as a powerful tool to simulate the reliability performance of the MEMS devices which involves extremely high pressure events [24]. The described model capability will also be useful for accurately modeling dual backplate or sealed dual membrane MEMS microphone structures [25] - [26].…”

Section: Discussionmentioning

confidence: 99%

A Behavioral Non-Linear Modeling Implementation for MEMS Capacitive Microphones

SHUBHAM¹

2022

Preprint

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<p>We highlight the behavioral non-linear system-level modeling approach for MEMS capacitive microphones. The combination of the finite element modeling and the large signal non-linear circuit modeling provide a strong capability to predict electro-acoustic performance for capacitive transductions. The circuit simulator tool such as Cadence Virtuoso has emerged as a powerful tool in designing behavioral models both in linear as well as in non-linear regimes. Typical small signal lumped element models fail to capture the MEMS behavior which changes over pressure and bias conditions. The models described herein capture diaphragm displacement and capacitance change over large pressure ranges for a simply supported circular plate. This can be coupled with the electrostatic force, due to the applied bias voltage, and is converted back to pressure thereby realizing a feedback loop in the circuit model. The non-linear model capability is extended to predict capacitance-bias behavior and estimate pull-in of the MEMS device. The microphone sensitivity, signal-to-noise ratio and harmonic distortions are accurately predicted using the non-linear large signal model when compared with measured microphone data.</p>

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Section: Discussionmentioning

confidence: 99%