基于pv的并网电动车中带SEPIC变换器的混合优化PI控制器

Ananda Babu Kancherla, N.Bhanu Prasad, D. Kishore
{"title":"基于pv的并网电动车中带SEPIC变换器的混合优化PI控制器","authors":"Ananda Babu Kancherla, N.Bhanu Prasad, D. Kishore","doi":"10.1109/IConSCEPT57958.2023.10170601","DOIUrl":null,"url":null,"abstract":"Electric vehicles (EVs), which assist sustainable transportation while minimising carbon emissions, have recently attracted a lot of interest. Utilizing EVs powered by photovoltaics (PV) significantly minimises the amount of carbon dioxide emitted into the atmosphere. The DC-DC SEPIC converter receives the PV output first, and gives output as high dc output voltage with low switching loss, and a non-inverting output. A hybrid Grey wolf optimization-Particle Swarm Optimization (GWO-PSO) based Proportional Integral (PI) controller is used to manage the performance of the SEPIC converter in order to ensure a steady DC voltage for the three phase Voltage Source Inverter (3-Ø VSI).The EV’s run by BLDC motor is powered by the 3-Ø VSI output. During the day, the EV application may run on power from the PV however, at night, when the sun is not shining, the BLDC motor needs power from the grid. This system is linked to the grid via a 1-Ø VSI. The efficiency of the hybrid GWO-PSO algorithm PI Controller is 96% which is verified using MATLAB Simulation.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid-optimized PI Controller With SEPIC Converter in PV-Based Grid-Integrated Electric Vehicle\",\"authors\":\"Ananda Babu Kancherla, N.Bhanu Prasad, D. Kishore\",\"doi\":\"10.1109/IConSCEPT57958.2023.10170601\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Electric vehicles (EVs), which assist sustainable transportation while minimising carbon emissions, have recently attracted a lot of interest. Utilizing EVs powered by photovoltaics (PV) significantly minimises the amount of carbon dioxide emitted into the atmosphere. The DC-DC SEPIC converter receives the PV output first, and gives output as high dc output voltage with low switching loss, and a non-inverting output. A hybrid Grey wolf optimization-Particle Swarm Optimization (GWO-PSO) based Proportional Integral (PI) controller is used to manage the performance of the SEPIC converter in order to ensure a steady DC voltage for the three phase Voltage Source Inverter (3-Ø VSI).The EV’s run by BLDC motor is powered by the 3-Ø VSI output. During the day, the EV application may run on power from the PV however, at night, when the sun is not shining, the BLDC motor needs power from the grid. This system is linked to the grid via a 1-Ø VSI. The efficiency of the hybrid GWO-PSO algorithm PI Controller is 96% which is verified using MATLAB Simulation.\",\"PeriodicalId\":240167,\"journal\":{\"name\":\"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IConSCEPT57958.2023.10170601\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IConSCEPT57958.2023.10170601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

电动汽车(ev)有助于可持续交通,同时最大限度地减少碳排放,最近引起了很多人的兴趣。利用由光伏发电(PV)驱动的电动汽车可以显着减少排放到大气中的二氧化碳量。dc - dc SEPIC变换器首先接收PV输出,输出为高直流输出电压,低开关损耗,无反相输出。为了保证三相电压源逆变器(3-Ø VSI)的直流电压稳定,采用混合灰狼优化-粒子群优化(GWO-PSO)的比例积分(PI)控制器对SEPIC变换器的性能进行控制。电动汽车由无刷直流电机运行,由3-Ø VSI输出供电。在白天,电动汽车应用程序可以从光伏供电,但在晚上,当太阳没有照耀,无刷直流电机需要从电网供电。该系统通过1-Ø VSI连接到电网。混合GWO-PSO算法PI控制器的效率为96%,并通过MATLAB仿真进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Hybrid-optimized PI Controller With SEPIC Converter in PV-Based Grid-Integrated Electric Vehicle
Electric vehicles (EVs), which assist sustainable transportation while minimising carbon emissions, have recently attracted a lot of interest. Utilizing EVs powered by photovoltaics (PV) significantly minimises the amount of carbon dioxide emitted into the atmosphere. The DC-DC SEPIC converter receives the PV output first, and gives output as high dc output voltage with low switching loss, and a non-inverting output. A hybrid Grey wolf optimization-Particle Swarm Optimization (GWO-PSO) based Proportional Integral (PI) controller is used to manage the performance of the SEPIC converter in order to ensure a steady DC voltage for the three phase Voltage Source Inverter (3-Ø VSI).The EV’s run by BLDC motor is powered by the 3-Ø VSI output. During the day, the EV application may run on power from the PV however, at night, when the sun is not shining, the BLDC motor needs power from the grid. This system is linked to the grid via a 1-Ø VSI. The efficiency of the hybrid GWO-PSO algorithm PI Controller is 96% which is verified using MATLAB Simulation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Three Port Full Bridge PFC Converter for Hybrid AC/DC/DC System with Fuzzy Logic Control ESH: A Non-Monotonic Activation Function For Image Classification Image Classification using Quantum Convolutional Neural Network Machine Learning Based Predictive Model for Intrusion Detection EV Sahayak: Android Assistance App for Electric Vehicle
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1