An Efficient Macromodel Extraction Strategy for Packaged MEMS Thermal Wind Sensor Considering Multiphysics

Abstract

This work presents a novel strategy for efficiently extracting macromodels from multiphysics microelectromechanical system (MEMS) devices with weak coupling. To validate the strategy, the packaged thermal wind sensor is chosen to verify the feasibility of the strategy for the first time. Based on the characteristics of the packaged thermal wind sensor, it can be divided into three distinct energy fields: thermal field, fluid field, and electric field. The packaged thermal wind sensor is initially built as the finite element model, which represents a pure thermal system under no wind flow conditions. Then, the thermal system with linear and time-invariant (LTI) is identified as a state space model by its step response obtained by transient simulation of the finite element model. Other energy fields can be regarded as negative inputs for the state space model. Subsequently, the macromodel is constructed by describing the relationship among thermal field, fluid field and electric field with Verilog-A. Remarkably, the macromodel based on this strategy takes into account geometric factors and material parameters. The tests show that the error of far group thermistors between system-level simulation and experiment is less than 5% under the conventional wind speed range on constant power (CP) mode, and the results of wind direction between them also show a significant degree of overlap. In brief, the strategy of extracting macromodel enables the direct construction of connections between the finite element model of MEMS devices and integrated circuits.