Fuzzy Cognitive Maps-Based Switched-Mode Power Supply Design Assistant System

Abstract

Traditional engineering design approaches primarily solve technical problems and often ignore the importance of human factors. To reduce human errors and workload in power electronics, this paper proposes a switched-mode power supply design (SMPS) assistant system based on Fuzzy Cognitive Maps (FCMs). This system incorporates both technical requirements and human factors that involve designers' knowledge and skills in the SMPS design domain. First, we identify the critical concepts from power management lab kits and power electronics books, and extract latent sub-skills of SMPS design using exploratory factor analysis to build the starting concept list of FCM. Second, we use factor analysis and correlation analysis to determine the causal weights between the captured components to build the initial FCM based on the starting concept list of FCM. Third, through interviews with subject-matter experts, we get their inputs on the initial main map and capture their individual FCMs. Then, we integrate experts' individual FCMs with different weights. After that, we determine the degree of fuzzification of the threshold function through analyzing data collected based on the prediction results of the only decision concept in the proposed FCM - SMPS quality. Two WHAT-IF scenarios are analyzed based on different inputs using the FCM Expert tool. The scenario test results provide guidelines to designers in terms of knowledge or skills improvements and power supply debugging. Finally, we evaluate the proposed system using eight scenarios. The evaluation results of components' actual states are consistent with their preferred states, which suggests that the proposed FCM-based assistant system is reliable and effective. The proposed system provides useful guidelines in terms of knowledge or skills improvements for SMPS designers and can help improve the power supply design process.