This paper presents the design and performance evaluation of an optical energy harvesting system for a wireless actuated micro-electro-mechanical system (MEMS) The latter consists of an antagonistic double beam and two active shape memory alloy elements (SMA: \(\:{3*1*0.1\:mm}^{3}\) ) responsible for actuating the beams among the two stable positions, when heated by a laser diode. The research focuses on harvesting the unused laser energy using a vertical multi-junction photovoltaic cell (PV cell: \(\:{3*3*0.4\:mm}^{3}\) ). To extract the maximum efficiency, the energy harvesting system is optimized by homogenizing the laser beam using an N-BK7 light pipe homogenizing rod. The uniformity test is validated experimentally by using an optoelectronic system able to move along the output and measure the power on different zone of the surface; resulting a percentage of uniformity ( across a surface of \(\:3.5*3\:{mm}^{2}\) , with a standard deviation of ± 3%. The Current/Voltage (IV) curve of the PV cell is extracted under direct illumination of irradiance of 0.93 \(\:{W/cm}^{2}\) , resulting a maximum power of 25.2 mW with a fill factor of 84%. To enhance energy utilization, a MEMS active mirror is being introduced to the system to steer the pseudo-uniform laser rays onto the SMA elements alternately (period = 5 s). The IV curve of the PV cell for each position is extracted resulting a fill factor of 92.3% for position 1 and 93% for position 2. While cycling, the unused energy from the laser is being captured by the PV cell resulting to harvest \(\:37.4\:mJ\) for the first cycle. This cycle is repeated 50 times to calculate the cumulative amount of energy harvested then 300 times to charge 90% of the capacity of a solid-state thin film micro-battery with initial state of charge (SOC) of 48%. Finally, the decrease in the efficiency of the PV cell is calculated after introducing the bistable beams resulting in a drop of 5%. This research introduces an advances approach to energy harvesting for MEMS, offering valuable insights into efficiency optimization and potential applications in autonomous systems.
