Python-Based Open-Source Electro-Mechanical Co-Optimization System for MEMS Inertial Sensors

Abstract

The surge in fabrication techniques for micro- and nanodevices gave room to rapid growth in these technologies and a never-ending range of possible applications emerged. These new products significantly improve human life, however, the evolution in the design, simulation and optimization process of said products did not observe a similarly rapid growth. It became thus clear that the performance of micro- and nanodevices would benefit from significant improvements in this area. This work presents a novel methodology for electro-mechanical co-optimization of micro-electromechanical systems (MEMS) inertial sensors. The developed software tool comprises geometry design, finite element method (FEM) analysis, damping calculation, electronic domain simulation, and a genetic algorithm (GA) optimization process. It allows for a facilitated system-level MEMS design flow, in which electrical and mechanical domains communicate with each other to achieve an optimized system performance. To demonstrate the efficacy of the methodology, an open-loop capacitive MEMS accelerometer and an open-loop Coriolis vibratory MEMS gyroscope were simulated and optimized—these devices saw a sensitivity improvement of 193.77% and 420.9%, respectively, in comparison to their original state.

Keywords

• microelectromechanical systems (MEMS)
• inertial sensors
• Python
• finite element method
• genetic algorithm
• optimization