MEMS Accelerometer Design Optimization Using Genetic Algorithm

Abstract

MEMS (Microelectromechanical Systems) refers to the technology integrating electrical and mechanical components with feature size of 1~1000 microns. Due to its small size, low cost, low power consumption and high efficiency, MEMS technology has been widely used in many fields.In this paper,the design optimization of MEMS accelerometer is discussed.The main objective of this investigation is to find a optimum design of MEMS,which satisfies a set of given constraints. The accelerometer employs a double folded beam flexure system and the mass being displaced is the proof mass.Due to the complex nature of the problem,a genetic algorithm (GA) is developed for the optimization of MEMS.The GA attempts to minimize the die area and so the four optimal parameter values can be determined. MEMS accelerometers can be used in air-bag deployment systems in automobiles.The experimental results will show the optimal design of MEMS.