A Mems Electro-Mechanical Co-Optimization Platform Featuring Freeform Geometry Optimization Based on a Genetic Algorithm

This paper describes a novel, system-level design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. A MEMS accelerometer comprising a freeform mechanical motion preamplifier embedded in a closed-loop control system is presented to demonstrate the effectiveness of the design approach. The optimization process improves the main figure-of-merit (FOM) by 482%. Measurements show that the displacement of the MEMS accelerometer in the closed-loop system is decreased by 86% with a 4.85 V feedback voltage for 1 g acceleration at 100 Hz compared with an open-loop system.