{"title":"Dual-Side Capacitor Tuning and Cooperative Control for Efficiency-Optimized Wide Output Voltages in Wireless EV Charging","authors":"Gangwei Zhu;Jianning Dong;Thiago Batista Soeiro;Hani Vahedi;Pavol Bauer","doi":"10.1109/TIE.2024.3436666","DOIUrl":null,"url":null,"abstract":"This article presents a dual-side capacitor tuning and cooperative control strategy for wireless electric vehicle (EV) charging. To improve the efficiency of wireless EV charging across broad output voltages and wide-range load variations, this article introduces a reconfigurable WPT system by incorporating two switch-controlled-capacitors (SCCs) into the double-sided LCC (DLCC) compensation network. Based on the analytical model of the system, optimal capacitor tuning factors are derived to reduce the rms values of the inductor currents and to minimize the turn-<sc>off</small> currents across the semiconductors. Furthermore, a dual-side cooperative control strategy is proposed. Through the collaborative control of the inverter, rectifier, and SCCs, the proposed method achieves dual-side optimal zero-voltage-switching (ZVS), wide power regulation, and maximum efficiency tracking simultaneously. Compared with the existing triple-phase-shift (TPS) method, the proposed approach improves the system efficiency across a wide range of dc output voltages and power levels. Experimental results demonstrate that the proposed method achieves a maximum efficiency improvement of up to 1.8% in the boost mode and 1.9% in the buck mode.","PeriodicalId":13402,"journal":{"name":"IEEE Transactions on Industrial Electronics","volume":"72 3","pages":"2507-2518"},"PeriodicalIF":7.2000,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Electronics","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10638722/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents a dual-side capacitor tuning and cooperative control strategy for wireless electric vehicle (EV) charging. To improve the efficiency of wireless EV charging across broad output voltages and wide-range load variations, this article introduces a reconfigurable WPT system by incorporating two switch-controlled-capacitors (SCCs) into the double-sided LCC (DLCC) compensation network. Based on the analytical model of the system, optimal capacitor tuning factors are derived to reduce the rms values of the inductor currents and to minimize the turn-off currents across the semiconductors. Furthermore, a dual-side cooperative control strategy is proposed. Through the collaborative control of the inverter, rectifier, and SCCs, the proposed method achieves dual-side optimal zero-voltage-switching (ZVS), wide power regulation, and maximum efficiency tracking simultaneously. Compared with the existing triple-phase-shift (TPS) method, the proposed approach improves the system efficiency across a wide range of dc output voltages and power levels. Experimental results demonstrate that the proposed method achieves a maximum efficiency improvement of up to 1.8% in the boost mode and 1.9% in the buck mode.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.