Bogdan Pamfil, Richard Palm, A. Vyas, H. Staaf, C. Rusu, P. D. Folkow
{"title":"Multi-Objective Design Optimization of Fractal-based Piezoelectric Energy Harvester","authors":"Bogdan Pamfil, Richard Palm, A. Vyas, H. Staaf, C. Rusu, P. D. Folkow","doi":"10.1109/PowerMEMS54003.2021.9658390","DOIUrl":null,"url":null,"abstract":"This paper studies optimization solutions for a proof-of-concept design methodology for a fractal-based tree energy harvester with a stress distribution optimized structure. The focus is on obtaining a sufficiently high-power output and a high enough stress in the longitudinal branch direction by using Frequency Response Functions. The design methodology shows that using the MATLAB code with Sensitivity Analysis and Multi-objective Optimization in combination with elitist genetic algorithm enables an optimal design.","PeriodicalId":165158,"journal":{"name":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 20th International Conference on Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerMEMS54003.2021.9658390","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies optimization solutions for a proof-of-concept design methodology for a fractal-based tree energy harvester with a stress distribution optimized structure. The focus is on obtaining a sufficiently high-power output and a high enough stress in the longitudinal branch direction by using Frequency Response Functions. The design methodology shows that using the MATLAB code with Sensitivity Analysis and Multi-objective Optimization in combination with elitist genetic algorithm enables an optimal design.