Shape Optimization of Eigenfrequencies in MEMS Gyroscopes
Daniel Schiwietz, Marian H\"orsting, Eva Maria Weig, Peter Degenfeld-Schonburg, Matthias Wenzel

TL;DR
This paper demonstrates how node-based shape optimization can automatically improve MEMS gyroscope designs by tuning eigenfrequencies and satisfying manufacturability constraints, discovering novel geometries beyond human intuition.
Contribution
It introduces a gradient-based shape optimization method for MEMS gyroscopes that automates design improvements and explores innovative geometries without human intervention.
Findings
Optimized designs shift spurious modes away from target frequencies.
The method achieves manufacturability constraints while improving performance.
Novel geometrical shapes are discovered that defy traditional intuition.
Abstract
Microelectromechanical systems (MEMS) gyroscopes are widely used in consumer and automotive applications. They have to fulfill a vast number of product requirements which lead to complex mechanical designs of the resonating structure. Arriving at a final design is a cumbersome process that relies heavily on human experience in conjunction with design optimization methods. In this work, we apply node-based shape optimization to the design of a MEMS gyroscope. For that purpose, we parametrize the coordinates of the nodes of the finite element method (FEM) mesh that discretize the shapes of the springs. We then implement the gradients of the mechanical eigenfrequencies and typical MEMS manufacturability constraints, with respect to the design parameters, in a FEM code. Using gradient-based optimization we tune the gyroscope's frequency split and shift spurious modes away from the first…
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Taxonomy
TopicsAdvanced MEMS and NEMS Technologies
