Abstract
The time-efficient and accurate implementation of physics-based fluidic damping effects is still one of the biggest challenges in the simulation of complex MEMS devices. Two modelling approaches utilizing the CRAIG/BAMPTON component mode synthesis method are discussed and compared in context of a highly automated model generation procedure. The first approach uses a modal projection technique with pressure profiles obtained from REYNOLDS flow simulations using the thermal-fluidic analogy. The second approach is based on the representation of the fluidic domain in form of a generalized KIRCHHOFFian lumped flow resistance network model. Both methods are generally suited for the simulation of structures like gyroscopes or accelerometers, but show different behaviors in terms of scaling and complexity during the model generation step and in the final ROM. The methods are demonstrated on examples and are compared to optical measurements of an out-of-plane teeter-totter type accelerometer.
Highlights
The performance and cost efficiency of MEMS devices is already essentially determined during the design phase
The example of the MEMS accelerometer demonstrated that both approaches are able to provide accurate predictions of the mechanical damping behavior for a MEMS device
Differences can be observed in the computational effort relation between ROM generation and actual simulation
Summary
The performance and cost efficiency of MEMS devices is already essentially determined during the design phase. The fluid flow through the perforation channels has a significant influence on the fluidic damping behavior and is often utilized to optimize the dynamic characteristics of a structure They can have a significant influence on the stiffness of seismic masses, which has an impact on high order eigenfrequencies and mode shapes. Obtained coefficients are assembled to modal system matrices which can be utilized in digital signal flow processors such as MATLAB Simulink to simulate the dynamic behavior Another common approach to model the R EYNOLDS flow domain is the representation of the gap region in form of a KIRCHHOFFian lumped flow resistance network model [4], allowing the simulation in electrical network simulators such as LTSpice or VHDL-AMS. In the context of an efficient simulation environment, strengths and weaknesses of each concept need to be determined to enable deliberate modelling decisions
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