| Selection and design of power supply systems for micro-electromechanical systems (MEMS) and portable devices is challenging because as device sizes diminish, complete system redesign, due to nonlinear power scaling relative to component size is often required to reduce the mass and volume of power supplies. A power supply algorithm has been developed wherein three approaches of grouping voltage and current data have been implemented. This algorithm has been incorporated into a MatLab code, which allows user input of system requirements and power target values; and provides battery number and configuration as problem solutions. The algorithm has been validated with two case studies on an environmental test monitor and a cochlear implant. The Wireless Integrated Microsystems (WIMS) environmental monitor testbed (EMT) is a multicomponent microelectromechanical system (MEMS), incorporating complementary metal oxide semiconductor (CMOS) materials for high-precision circuits used for integrated sensors such as microgravity accelerometers, microgyroscopes, and pressure sensors. The WIMS-EMT duty cycle, like that of many autonomous MEMS systems, has low-power standby periods of sensing, and high-power pulses for R/F transmission and reception. First, four strategies for reduction of power demand by the largest consumer of power in the WIMS-EMT, the preconcentrator were performed: alterations in heater pad placement/size, reduction of thermal mass in the device, vacuum sealing, and incorporation of a gas dwell time during preconcentrator heating. Our numerical results were in general agreement with experimental findings in simpler systems, in terms of the benefits of vacuum sealing. The greatest reductions in power demand were achieved with vacuum sealing (51%) and reductions in thermal mass (15%). Second, a systematic approach for the selection of power systems according to (1) specification of a single, aggregate power supply, resulting in a single electrochemistry and cell size; (2) specification of several power supplies, by a priori division of power sources by power range; and (3) specification of an arbitrary number of power "bundles," based on available space in the device have been established. A discussion of the implementation of the algorithm into a MatLab code and its application to the WIMS-EMT and cochlear implant are provided as a proof of concept. |
