Design of freeform geometries in a MEMS accelerometer with a mechanical motion preamplifier based on a genetic algorithm
Chen Wang, Xiaoxiao Song, Weidong Fang, Fang Chen, Ioannis Zeimpekis, Yuan Wang, Aojie Quan, Jian Bai, Huafeng Liu, Gerold Schröpfer, Chris Welham, Michaël Kraft
Abstract
This paper describes a novel, semiautomated design methodology based on a genetic algorithm (GA) using freeform geometries for microelectromechanical systems (MEMS) devices. The proposed method can design MEMS devices comprising freeform geometries and optimize such MEMS devices to provide high sensitivity, large bandwidth, and large fabrication tolerances. The proposed method does not require much computation time or memory. The use of freeform geometries allows more degrees of freedom in the design process, improving the diversity and performance of MEMS devices. A MEMS accelerometer comprising a mechanical motion amplifier is presented to demonstrate the effectiveness of the design approach. Experimental results show an improvement in the product of sensitivity and bandwidth by 100% and a sensitivity improvement by 141% compared to the case of a device designed with conventional orthogonal shapes. Furthermore, excellent immunities to fabrication tolerance and parameter mismatch are achieved.