Parametric Design Analysis of Magnetic Sensor Based on Model Order Reduction and Reliability-Based Design Optimization

This paper presents a novel parametric design analysis of the magnetic sensor module used to find mover positions in linear motors. The proposed framework utilizes a computationally inexpensive proper orthogonal decomposition-dynamic mode decomposition-based model order reduction (MOR), coupled with a multiparameter moment matching method. The model is then utilized by a moment-based probabilistic design optimization method that considers the manufacturing uncertainties to find the optimal sensor design. A magnetic sensor module is designed for employing the proposed framework, and the results show that: 1) the proposed MOR technique is accurate; 2) the reliability analysis performed during the probabilistic design optimization can help to reduce the excessive non-compliance costs for the manufacturers; and 3) the combined framework is able to significantly expedite the optimal design search.