Iet Electric Power Applications最新文献_第5页

Predictive AI Maintenance of Distribution Oil-Immersed Transformer via Multimodal Data Fusion: A New Dynamic Multiscale Attention CNN-LSTM Anomaly Detection Model for Industrial Energy Management 基于多模态数据融合的配电油浸变压器预测人工智能维护：一种新的工业能源管理动态多尺度关注CNN-LSTM异常检测模型

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-25 DOI: 10.1049/elp2.70011

Elvis Tamakloe, Benjamin Kommey, Jerry John Kponyo, Eric Tutu Tchao, Andrew Selasi Agbemenu, Griffith Selorm Klogo

{"title":"Predictive AI Maintenance of Distribution Oil-Immersed Transformer via Multimodal Data Fusion: A New Dynamic Multiscale Attention CNN-LSTM Anomaly Detection Model for Industrial Energy Management","authors":"Elvis Tamakloe, Benjamin Kommey, Jerry John Kponyo, Eric Tutu Tchao, Andrew Selasi Agbemenu, Griffith Selorm Klogo","doi":"10.1049/elp2.70011","DOIUrl":"https://doi.org/10.1049/elp2.70011","url":null,"abstract":"Reactive and preventive maintenance strategies have been applied to avert transformer failures and safeguard their operations. However, these approaches have limitations of high operational downtimes, over- and under-maintenance issues, maintenance fatigue and revenue loss. The advancements in machine learning and artificial intelligence have positively altered the machine and equipment maintenance landscape. Thus, predictive maintenance (PdM), in contrast to the above-listed maintenance approaches, has laid the foundation for improving transformer maintenance by identifying incipient failures to solve the existing challenges. Recent developments in predictive maintenance of distribution power transformers have made great strides, but to solve the current challenge of accurate fault identification, this study proposed a new model architecture (DMSA CNN-LSTM) using multimodal data fusion to address anomaly detection. A classification accuracy, F1-score, precision and recall of 0.9917, 0.9714, 0.9781 and 0.9647, respectively, were produced on a fused multimodal dataset at a computational time of 619.898 s. The performance was afterwards evaluated against other state-of-the-art benchmark models. The significance of this study lies in providing a scalable data-driven architecture suitable for real-time deployment in providing predictive solutions for transformers at a higher performance efficiency. This approach leverages deep neural networks that provide a comprehensive diagnostic and prognostic approach to mitigate transformer faults and breakdowns.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Direct model predictive torque control for permanent magnet synchronous motor with voltage vector parallel optimisation algorithm 基于电压矢量并联优化算法的永磁同步电机直接模型预测转矩控制

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-24 DOI: 10.1049/elp2.70007

Shejuan Qiao, Jin Huang, Yuhao Xu, Ke Song

{"title":"Direct model predictive torque control for permanent magnet synchronous motor with voltage vector parallel optimisation algorithm","authors":"Shejuan Qiao, Jin Huang, Yuhao Xu, Ke Song","doi":"10.1049/elp2.70007","DOIUrl":"https://doi.org/10.1049/elp2.70007","url":null,"abstract":"The multi-vector-based direct model predictive torque control (DMPTC) inherits the high control precise of vector control and the fast dynamic response of model predictive control. However, the cascade optimisation mode is difficult to guarantee the global optimal performance of the voltage vector (VV) combination, and results in invalid VV time duration in some cases as well as high calculation complexity. In this paper, for the predictive control of permanent magnet synchronous motors widely used in electric propulsion aircraft, a parallel optimisation DMPTC method is proposed to ensure that the multi-vectors applied are all optimal in each control cycle. The optimal double vectors are directly chosen locating the sub-region of the sector of reference VV. With only the absolute value of stator VV error term, the time duration is always in the valid range and robust to motor parameters. In addition, a cost function with a single control objective is designed to control the torque and flux cooperatively, eliminating the stator flux weighting factor and reducing the computation burden. The proposed method is compared with the recent predictive torque control strategies. The experimental results confirm the effectiveness of the proposed method in improving the dynamic response and steady-state performance while reducing computation burden and complexity.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

DeepServo: Deep learning-enhanced state feedback for robust servo system control 深度伺服：用于鲁棒伺服系统控制的深度学习增强状态反馈

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-18 DOI: 10.1049/elp2.70001

Farhad Amiri, Mohsen Eskandari, Mohammad H. Moradi

{"title":"DeepServo: Deep learning-enhanced state feedback for robust servo system control","authors":"Farhad Amiri, Mohsen Eskandari, Mohammad H. Moradi","doi":"10.1049/elp2.70001","DOIUrl":"https://doi.org/10.1049/elp2.70001","url":null,"abstract":"Servo controllers are essential components in robotics, manufacturing, and various industrial applications. However, achieving fast and accurate reference tracking in servo systems remains challenging due to modelling uncertainties and external disturbances. In this paper, a hybrid control strategy is proposed that combines a Linear Quadratic Regulator (LQR) state-feedback controller with deep learning to address these challenges. The LQR controller utilises system state measurements to optimise the control input, while the integration of a deep neural network enhances accuracy and dynamic response by adapting to changing system conditions. This approach provides robust control performance, effectively mitigating the impact of uncertainties and disturbances on servo system behaviour. The proposed method was validated using AC servo motors, among the most common servo systems, though the approach is adaptable to other servo-like systems. Comparative evaluations are conducted against existing methods, including SIMC-SMC, 2DOF-IMC-SMC, 2DOF-IMC-PID, and SIMC-PD controllers, focusing on the angular position control of a servo motor. Simulation results demonstrate that the proposed controller outperforms these methods in terms of robustness, precision, and disturbance rejection. These findings highlight the potential of the proposed LQR-deep learning framework to significantly improve servo system performance across a wide range of applications.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143431679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Co-simulations of induction machines coupled with a radial ball bearing for mechanical defects analysis 结合径向球轴承的感应电机机械缺陷联合仿真分析

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-17 DOI: 10.1049/elp2.12529

Nada El Bouharrouti, Maksim Sitnikov, Ahmed Hemeida, Floran Martin, Karolina Kudelina, Muhammad U. Naseer, Anouar Belahcen

{"title":"Co-simulations of induction machines coupled with a radial ball bearing for mechanical defects analysis","authors":"Nada El Bouharrouti, Maksim Sitnikov, Ahmed Hemeida, Floran Martin, Karolina Kudelina, Muhammad U. Naseer, Anouar Belahcen","doi":"10.1049/elp2.12529","DOIUrl":"https://doi.org/10.1049/elp2.12529","url":null,"abstract":"In this paper, two co-simulations are introduced to study the behaviour of a 2-D finite-element model and a magnetic equivalent model of an induction machine, both coupled with a mechanical radial ball bearing model. This comprehensive approach allows for the generation of synthetic vibration and current signals of a ball bearing mounted on a shaft, taking into account the entire machinery. The study investigates the misalignment effect caused by an inner ring defect in a ball bearing, analysing its impact on the current of the IM models. Likewise, the effects of eccentricity in the induction machine models on rotor vibration are studied through their coupling with the mechanical ball bearing model. This multiphysics co-simulation provides a novel numerical application to generate data relative to mechanical defects in induction machines. By using this coupled method, an inner ring defect of 1 mm depth and 3 mm length in the bearing model is accurately identified in the frequency spectrum of the stator current, whereas eccentricity faults for levels ranging between 5% and 40% are detected in the vibration spectrum of the ball bearing. The findings are accurately supported by related theory, and further validated through experimental verification for the case of the inner ring fault.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12529","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analytical model for ring winding axial flux permanent magnet motor using Schwarz–Christoffel conformal mapping 基于Schwarz-Christoffel保角映射的环形绕组轴向磁通永磁电机解析模型

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-12 DOI: 10.1049/elp2.70006

Mohammad Bapiri, Abolfazl Vahedi, Hossein Azizi Moghaddam

{"title":"Analytical model for ring winding axial flux permanent magnet motor using Schwarz–Christoffel conformal mapping","authors":"Mohammad Bapiri, Abolfazl Vahedi, Hossein Azizi Moghaddam","doi":"10.1049/elp2.70006","DOIUrl":"https://doi.org/10.1049/elp2.70006","url":null,"abstract":"Recently, there has been a growing interest in new permanent magnet (PM) motor topologies. However, these newly developed PM motors are still in their early design stages and face various challenges. In order to overcome these drawbacks, further development of these motor topologies is necessary. One such new motor topology is the ring winding axial flux permanent magnet (RWAFPM) motor. Enhancing the performance of this motor requires optimising its geometry, which can be a time-consuming process when using the three-dimensional (3D) finite element method (FEM). It is essential to propose a two-dimensional model that offers faster processing but lower accuracy to address this issue compared to 3D FEM for this motor. Due to the three-dimensional structure of ring-winding axial flux machine|axial flux motors, creating a two-dimensional (2D) model for this motor presents a significant challenge. In this article, while studying the RWAFPM motor, the simplifications to the motor's geometry have been proposed in order to create a 2D model that provides sufficient accuracy as a substitute for 3D FEM. To validate our findings, the Schwarz–Christoffel conformal mapping technique has been employed to extract the modelling results. Finally, these findings have been compared with the outcomes obtained from the 3D simulation. Validation. Validation of 3D finite element results has been done by experimental results.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143397084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Magnetic field and rotor impedance analysis of solid rotor induction motors using the multilayer analytical method 用多层分析法分析固体转子感应电动机的磁场和转子阻抗

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-07 DOI: 10.1049/elp2.70004

Hao Xu, Jinghong Zhao, Sinian Yan, Hanming Wang

{"title":"Magnetic field and rotor impedance analysis of solid rotor induction motors using the multilayer analytical method","authors":"Hao Xu, Jinghong Zhao, Sinian Yan, Hanming Wang","doi":"10.1049/elp2.70004","DOIUrl":"https://doi.org/10.1049/elp2.70004","url":null,"abstract":"This paper proposes a multilayer analytical model for calculating the magnetic field and equivalent circuit parameters of solid rotor induction motors (SRIM), and the B–H curve of rotor material is used to consider the influence of saturation effect of solid rotor. The equivalent circuit of SRIM based on surface impedance theory can fully consider the influence of rotor material. Then, the magnetic vector potential in the rotor is solved in the three-dimensional electromagnetic field, and the rotor is segmented along the axial direction to obtain the end coefficient considering the axial non-linear effect of the rotor. The air gap magnetic field distribution, rotor loss, rotor impedance and torque were analysed by finite element simulation, and the accuracy of the multilayer analytical model and end coefficient was verified. Compared with the finite element method, the analytical method proposed in this paper is time saving, resulting in that it is suitable for the optimised design. Finally, an experimental prototype is developed and tested, confirming the accuracy of both the finite element simulation and the analytical model.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on double transistor open circuit fault diagnosis of T-type three level rectifier based on mixed logical dynamical model 基于混合逻辑动态模型的t型三电平双晶体管开路故障诊断研究

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-07 DOI: 10.1049/elp2.12536

Jianyuan Wang, Yuxiang Liu, Dongsheng Yuan, Cong Liu, Kaiyue Zuo

{"title":"Research on double transistor open circuit fault diagnosis of T-type three level rectifier based on mixed logical dynamical model","authors":"Jianyuan Wang, Yuxiang Liu, Dongsheng Yuan, Cong Liu, Kaiyue Zuo","doi":"10.1049/elp2.12536","DOIUrl":"https://doi.org/10.1049/elp2.12536","url":null,"abstract":"The T-type three-level rectifier has garnered significant attention due to its ability to enhance the voltage waveform quality in power systems and reduce electromagnetic interference with other equipment. To ensure high reliability in high-power wind and photovoltaic power generation systems, conducting fault diagnosis for T-type three-level rectifiers is crucial. This paper first analyzes the input current characteristics of both in-phase and out-of-phase dual transistor open-circuit faults. A current-extended observer is developed using a hybrid logic dynamic model to estimate the current value during normal operation. The residual state equation is derived by comparing this estimated current with the actual fault current. A residual information table for fault currents is created through differential solutions of the residual state equation, enabling fault localisation by comparing the residual information against predefined threshold values. Finally, the feasibility and accuracy of the proposed fault diagnosis method are validated through simulations and experiments.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Low-frequency noise removal and acoustic spectral distribution assessment method for high-voltage power transformers with varying service lifetimes 变使用寿命高压电力变压器低频噪声去除及声谱分布评估方法

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-07 DOI: 10.1049/elp2.12545

Yunpeng Liu, Guanyu Chen, Fuseng Xu, Tao Zhao, Hongliang Liu

{"title":"Low-frequency noise removal and acoustic spectral distribution assessment method for high-voltage power transformers with varying service lifetimes","authors":"Yunpeng Liu, Guanyu Chen, Fuseng Xu, Tao Zhao, Hongliang Liu","doi":"10.1049/elp2.12545","DOIUrl":"https://doi.org/10.1049/elp2.12545","url":null,"abstract":"The acoustic signals of power transformers serve as key indicators for assessing operational statuses and detecting internal mechanical issues. However, low-frequency noise, such as fan noise, often obscures critical features. This study introduces an adaptive low-frequency denoising algorithm based on the filtered-x least mean square (FxLMS) model. By optimising the step size and convergence factor, the algorithm resolves the peak offset issue in traditional LMS methods, enhances denoising performance and computational efficiency, and demonstrates effectiveness in practical scenarios. Using denoised acoustic data, quantitative analysis based on information entropy (frequency complexity analysis (FCA)) evaluates changes in mechanical properties. The analysis indicates that healthy transformers exhibit lower FCA values, whereas aged transformers show values approximately double those of healthy units, reflecting the mechanical changes associated with normal ageing. Further analysis of transformers commissioned in 2004 reveals that FCA values of abnormally aged transformers exceed three times those of typically aged units, indicating severe mechanical degradation. These findings demonstrate that combining the FxLMS algorithm with FCA analysis effectively extracts denoised acoustic features and distinguishes between healthy states, normal ageing, and abnormal ageing in transformers.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12545","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Structural optimisation of oil immersed transformer winding block washers based on WOA-DRBF surrogate model optimisation strategy 基于WOA-DRBF代理模型优化策略的油浸式变压器绕组垫圈结构优化

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-02-01 DOI: 10.1049/elp2.70003

Yufei Dong, Chenglong Gao, Wenxin Xiang, Gang Liu, Yunpeng Liu, Yang Liu, Zhenbin Du

{"title":"Structural optimisation of oil immersed transformer winding block washers based on WOA-DRBF surrogate model optimisation strategy","authors":"Yufei Dong, Chenglong Gao, Wenxin Xiang, Gang Liu, Yunpeng Liu, Yang Liu, Zhenbin Du","doi":"10.1049/elp2.70003","DOIUrl":"https://doi.org/10.1049/elp2.70003","url":null,"abstract":"In order to reduce the transformer winding hot spot temperature (HST), a dynamic radial basis function surrogate model optimisation strategy is proposed to optimise the structure of the forced oil circulation transformer winding's block washers in this paper. The whale optimisation algorithm (WOA) is introduced to obtain the optimal hyperparameter, and the WOA-DRBF surrogate model optimisation strategy is used to improve the fitting and optimisation ability. After optimisation, the HST corresponding to the size of the block washers decreased by 3.67°C, and the maximal temperature rise decreased by 12.93%, effectively ameliorating the phenomenon of excessive local temperature rise within each partition. Comparing the above optimisation results with those of the WOA-RBF static surrogate model and the genetic algorithm (GA), the proposed method shows superior performance in both optimisation search capability and efficiency. Comparing the optimisation efficiencies of the three methods, the number of model calls for the WOA-DRBF method is 23.89% of the WOA-RBF method and 1.77% of the GA method, respectively. The proposed method significantly enhances optimisation efficiency while improving global optimisation search capability. It offers a feasible solution for efficiently and accurately solving the optimisation problem of the transformer winding's block washer.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Closed-loop input current control strategy based on waveform similarity index for the emerging matrix converters with harmonic injection technique 基于波形相似度指标的新型谐波注入矩阵变换器闭环输入电流控制策略

IF 1.5 4区工程技术

Iet Electric Power Applications Pub Date : 2025-01-30 DOI: 10.1049/elp2.70005

Zhichao Yang, Jiaxing Lei, Bingtuan Gao, Wu Chen

{"title":"Closed-loop input current control strategy based on waveform similarity index for the emerging matrix converters with harmonic injection technique","authors":"Zhichao Yang, Jiaxing Lei, Bingtuan Gao, Wu Chen","doi":"10.1049/elp2.70005","DOIUrl":"https://doi.org/10.1049/elp2.70005","url":null,"abstract":"Harmonic injection matrix converter (HIMC) achieves direct AC-AC power conversion with maximum voltage transfer and reduced transistor capacity. However, the existing open-loop current control method for HIMC may bring in low-order harmonics if the injected harmonic current deviates from its desired value. To address this issue, this paper proposes a closed-loop input current control strategy based on the waveform similarity index (WSI) for these emerging MC topologies. The WSIs are defined as the ratios of the corresponding input currents against the maximum and minimum input voltages. Multi resonant controllers are adopted to regulate the WSI difference so that its low-order harmonics are eliminated, which generate an additional signal to correct the injected harmonic current. By adopting the proposed current control strategy, the 5th and 7th harmonics are suppressed to lower than 1.0% under the sinusoidal input voltages and nominal load scenario. Even with inaccuracies in the reference harmonic current generation, the proposed strategy enables the input currents to approach sinusoidal waveforms with significantly reduced WSIs difference, thus enhancing the input power factor over the conventional open-loop method. Besides, the proposed method is effective under unbalanced and distorted conditions through the experimental verification.","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"19 1","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.70005","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143120795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0