• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用于铁路应用中储能系统的具有智能最大功率点跟踪策略的并网改进型Sepic变换器。

Grid connected improved sepic converter with intelligent mppt strategy for energy storage system in railway applications.

作者信息

Vendoti Suresh, Sekhar A Hema, Bharadwaja A V, Kommula Bapayya Naidu, Sateesh Rayala, Prabhakar S, Arunkumar M, Yaping Cui

机构信息

School of Engineering, Electrical and Electronics Engineering Department, Godavari Global University, Rajahmundry, A.P., India.

Electrical and Electronics Engineering Department, VEMU Institute of Technology, Chittoor, A.P., India.

出版信息

Sci Rep. 2025 Apr 16;15(1):13192. doi: 10.1038/s41598-025-96704-1.

DOI:10.1038/s41598-025-96704-1
PMID:40240477
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12003647/
Abstract

In order to increase the utilization rate of regenerative braking energy, reduce the operation cost and improve the power quality of traction power supply system in high-speed railway. This paper presents a grid-connected improved SEPIC converter with an intelligent maximum power point tracking (MPPT) strategy tailored for energy storage systems in railway applications. The proposed system enhances power conversion efficiency and stability by integrating an optimized SEPIC topology with an adaptive MPPT algorithm. The solar PV system supplies voltage to the inverter via an Improved SEPIC converter. A smart MPPT technique is used to regulate the DC bus voltage and control the Improved SEPIC converter. The wind energy conversion system (WECS), featuring a DFIG, performs AC-DC conversion with the help of a PWM rectifier, and the rectifier is managed by a PI controller. The converter's output is fed to the grid through a single-phase VSI, which converts the DC voltage into AC. An LC filter is used to improve the inverter's output. The combined power from the PV and WECS sources is stored in the battery through a bi-directional battery converter. Power from both the battery and the AC output from the single-phase VSI is then injected into the power grid, which supplies energy to the train for its operation. Compared to conventional SEPIC converters, the improved topology reduces voltage stress by 25% and increases efficiency by 97%, ensuring reliable energy storage and grid synchronization. Furthermore, the intelligent MPPT strategy improves tracking speed by 37.5% under dynamic conditions, leading to enhanced energy utilization and reduced response time. Simulation and experimental results (DSPIC30F4011 controller) validate the superior performance, demonstrating its potential for real-world railway applications.

摘要

为了提高再生制动能量的利用率,降低运营成本并改善高速铁路牵引供电系统的电能质量。本文提出了一种并网改进型SEPIC变换器,其具有专门为铁路应用中的储能系统量身定制的智能最大功率点跟踪(MPPT)策略。所提出的系统通过将优化的SEPIC拓扑与自适应MPPT算法相结合,提高了功率转换效率和稳定性。太阳能光伏系统通过改进型SEPIC变换器向逆变器供电。采用智能MPPT技术来调节直流母线电压并控制改进型SEPIC变换器。具有双馈感应发电机(DFIG)的风能转换系统(WECS)借助PWM整流器进行AC-DC转换,并且该整流器由PI控制器管理。变换器的输出通过单相电压源逆变器(VSI)馈入电网,该逆变器将直流电压转换为交流电压。使用LC滤波器来改善逆变器的输出。来自光伏和WECS源的组合功率通过双向电池变换器存储在电池中。然后,来自电池的功率和单相VSI的交流输出都注入到电网中,电网为列车运行提供能量。与传统的SEPIC变换器相比,改进后的拓扑将电压应力降低了25%,效率提高到97%,确保了可靠的能量存储和电网同步。此外,智能MPPT策略在动态条件下将跟踪速度提高了37.5%,从而提高了能量利用率并缩短了响应时间。仿真和实验结果(DSPIC30F4011控制器)验证了其卓越性能,证明了其在实际铁路应用中的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/b06b33b7cdfe/41598_2025_96704_Fig26_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/73d71e80bcf3/41598_2025_96704_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/1ce65aa56724/41598_2025_96704_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/10f8fbf1242f/41598_2025_96704_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/cbf064ef4c3d/41598_2025_96704_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/433575b577ca/41598_2025_96704_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/20b9c1d7339b/41598_2025_96704_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/7f144e96efc9/41598_2025_96704_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/d95a4cdeb040/41598_2025_96704_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a15f120b67b0/41598_2025_96704_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/9542f4737f7f/41598_2025_96704_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/c825b8bb6866/41598_2025_96704_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/8c41e367c037/41598_2025_96704_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/36f262198443/41598_2025_96704_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/307cf7480c81/41598_2025_96704_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/db6dd7eaafaf/41598_2025_96704_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/af920542f9e8/41598_2025_96704_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/229bdbab8576/41598_2025_96704_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/be2aaaad4f39/41598_2025_96704_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/1e638ed94767/41598_2025_96704_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/6a604389c030/41598_2025_96704_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a1b936190a9e/41598_2025_96704_Fig21_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/ad1c84237b0d/41598_2025_96704_Fig22_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/76f66151372c/41598_2025_96704_Fig23_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a043e2c69bf3/41598_2025_96704_Fig24_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/c6adc6fffad9/41598_2025_96704_Fig25_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/b06b33b7cdfe/41598_2025_96704_Fig26_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/73d71e80bcf3/41598_2025_96704_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/1ce65aa56724/41598_2025_96704_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/10f8fbf1242f/41598_2025_96704_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/cbf064ef4c3d/41598_2025_96704_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/433575b577ca/41598_2025_96704_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/20b9c1d7339b/41598_2025_96704_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/7f144e96efc9/41598_2025_96704_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/d95a4cdeb040/41598_2025_96704_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a15f120b67b0/41598_2025_96704_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/9542f4737f7f/41598_2025_96704_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/c825b8bb6866/41598_2025_96704_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/8c41e367c037/41598_2025_96704_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/36f262198443/41598_2025_96704_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/307cf7480c81/41598_2025_96704_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/db6dd7eaafaf/41598_2025_96704_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/af920542f9e8/41598_2025_96704_Fig16_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/229bdbab8576/41598_2025_96704_Fig17_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/be2aaaad4f39/41598_2025_96704_Fig18_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/1e638ed94767/41598_2025_96704_Fig19_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/6a604389c030/41598_2025_96704_Fig20_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a1b936190a9e/41598_2025_96704_Fig21_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/ad1c84237b0d/41598_2025_96704_Fig22_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/76f66151372c/41598_2025_96704_Fig23_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/a043e2c69bf3/41598_2025_96704_Fig24_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/c6adc6fffad9/41598_2025_96704_Fig25_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bf03/12003647/b06b33b7cdfe/41598_2025_96704_Fig26_HTML.jpg

相似文献

1
Grid connected improved sepic converter with intelligent mppt strategy for energy storage system in railway applications.用于铁路应用中储能系统的具有智能最大功率点跟踪策略的并网改进型Sepic变换器。
Sci Rep. 2025 Apr 16;15(1):13192. doi: 10.1038/s41598-025-96704-1.
2
MPPT efficiency enhancement of a grid connected solar PV system using Finite Control set model predictive controller.基于有限控制集模型预测控制器的并网太阳能光伏系统最大功率点跟踪效率提升
Heliyon. 2024 Mar 7;10(6):e27663. doi: 10.1016/j.heliyon.2024.e27663. eCollection 2024 Mar 30.
3
Implementation of high step up converter using RBFN MPPT controller for fuel cell based electric vehicle application.基于径向基函数神经网络(RBFN)最大功率点跟踪(MPPT)控制器的高升压变换器在基于燃料电池的电动汽车中的应用
Sci Rep. 2024 Nov 26;14(1):29364. doi: 10.1038/s41598-024-79857-3.
4
Analysis and control of grid-interactive PV-fed BLDC water pumping system with optimized MPPT for DC-DC converter.采用优化的最大功率点跟踪(MPPT)控制策略的并网光伏驱动无刷直流(BLDC)水泵系统的分析与控制,用于DC-DC变换器。
Sci Rep. 2024 Oct 29;14(1):25963. doi: 10.1038/s41598-024-77822-8.
5
ANN-based dynamic control and energy management of inverter and battery in a grid-tied hybrid renewable power system fed through switched Z-source converter.基于人工神经网络的并网混合可再生能源发电系统中逆变器和电池的动态控制与能量管理,该系统通过开关型Z源变换器供电。
Electr Eng (Berl). 2021;103(5):2285-2301. doi: 10.1007/s00202-021-01231-7. Epub 2021 Feb 17.
6
A new wide input voltage DC-DC converter for solar PV systems with hybrid MPPT controller.一种用于太阳能光伏系统的新型宽输入电压DC-DC转换器,带有混合最大功率点跟踪(MPPT)控制器。
Sci Rep. 2024 May 9;14(1):10639. doi: 10.1038/s41598-024-61367-x.
7
Improved tunicate swarm search-based MPPT for photovoltaic on a "grid-connected" inverter system.基于改进被囊动物群搜索算法的光伏“并网”逆变器系统最大功率点跟踪控制
Environ Sci Pollut Res Int. 2022 Nov;29(52):78650-78665. doi: 10.1007/s11356-022-21157-2. Epub 2022 Jun 13.
8
SVPWM control strategy for Novel Interleaved High Gain DC converter fed 3-level NPC Inverter for Renewable Energy Applications.用于可再生能源应用的新型交错式高增益直流变换器供电的三电平中点钳位逆变器的空间矢量脉宽调制(SVPWM)控制策略
ISA Trans. 2023 Sep;140:426-437. doi: 10.1016/j.isatra.2023.05.019. Epub 2023 May 30.
9
Modeling & implementation of DRLA based partially shaded solar system integration with 3- conventional grid using constant current controller.基于恒流控制器的部分阴影太阳能系统与三相传统电网集成的DRLA建模与实现
Heliyon. 2022 Jun 6;8(6):e09669. doi: 10.1016/j.heliyon.2022.e09669. eCollection 2022 Jun.
10
Development of multiple input supply based modified SEPIC DC-DC converter for efficient management of DC microgrid.基于多输入电源的改进型SEPIC DC-DC转换器的开发,用于高效管理直流微电网。
Sci Rep. 2024 May 14;14(1):11066. doi: 10.1038/s41598-024-61713-z.

本文引用的文献

1
An intelligent Hybrid Wind-PV farm as a static compensator for overall stability and control of multimachine power system.一种智能混合风力-光伏电站作为多机电力系统整体稳定性和控制的静止补偿器。
ISA Trans. 2022 Apr;123:286-302. doi: 10.1016/j.isatra.2021.05.014. Epub 2021 May 17.