A framework for eigenvalue-based topology optimization of torsional resonant microscanner to improve dynamic stability

The micro-electro-mechanical system (MEMS) technology has led to improvements in the manufacturability and scalability of the semiconductor-based sensors and actuators. This study proposes a framework for topology optimization to improve the dynamic stability of a resonant MEMS scanner for a light detection and ranging (LiDAR) system installed on an autonomous vehicle. The microscanner must have excellent dynamic stiffness and rigidity for in-plane disturbances because the vehicle system is subjected to several types of disturbances owing to road harshness and power train vibration. This paper is the first one to apply the topology optimization method to the design of torsional spring of the microscanner to maximize the lateral yawing mode frequency, which might degrade stable operation. The optimization was constrained to the mode frequencies for the torsional and the two bending modes, similar to the reference model. The proposed framework can facilitate the systematical design of a torsional resonant microscanner that satisfies frequency requirements with improved dynamic stability for in-plane disturbance.