{"title":"A stability improvement control strategy research for LLC resonant converter with single neuron PI-I double closed loop control","authors":"Zhangang Yang , Qingyu Zhou","doi":"10.1016/j.asej.2024.102934","DOIUrl":null,"url":null,"abstract":"<div><p>LLC resonant converters are widely used in the aerospace field. However, under traditional single-loop control, LLC resonant converters are prone to instability in the face of high-power load disturbances, which fails to meet the high stability requirements of the aerospace field. In order to enhance the stability and disturbance rejection capability of the LLC resonant converter, this paper proposes a stability improvement strategy with additional resonant voltage integral control based on the generalized state-space aver-aged model of the LLC resonant converter. By combining eigenvalue sensitivity analysis and eigenvalue analysis theory, the system stability is further optimized. To achieve control parameter adaptive adjustment, a single neuron algorithm is introduced, resulting in an LLC resonant converter with a single neuron PI-I double closed-loop control. Simulation results indicate that the proposed LLC resonant converter with single neuron PI-I double closed-loop control exhibits improved stability compared to the LLC resonant converter under traditional single-loop control.</p></div>","PeriodicalId":48648,"journal":{"name":"Ain Shams Engineering Journal","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2090447924003095/pdfft?md5=1bccc86ed9d4f5aa89c1ec6ae0e569bf&pid=1-s2.0-S2090447924003095-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ain Shams Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2090447924003095","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
LLC resonant converters are widely used in the aerospace field. However, under traditional single-loop control, LLC resonant converters are prone to instability in the face of high-power load disturbances, which fails to meet the high stability requirements of the aerospace field. In order to enhance the stability and disturbance rejection capability of the LLC resonant converter, this paper proposes a stability improvement strategy with additional resonant voltage integral control based on the generalized state-space aver-aged model of the LLC resonant converter. By combining eigenvalue sensitivity analysis and eigenvalue analysis theory, the system stability is further optimized. To achieve control parameter adaptive adjustment, a single neuron algorithm is introduced, resulting in an LLC resonant converter with a single neuron PI-I double closed-loop control. Simulation results indicate that the proposed LLC resonant converter with single neuron PI-I double closed-loop control exhibits improved stability compared to the LLC resonant converter under traditional single-loop control.
期刊介绍:
in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance.
Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.