IEEE Open Journal of the Industrial Electronics Society最新文献_第8页

Power Imbalance Analysis of Modular Multilevel Converter With Distributed Energy Systems 带有分布式能源系统的模块化多电平转换器的功率不平衡分析

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-02-12 DOI: 10.1109/OJIES.2024.3361167

Tomas Salvadores;Javier Pereda;Félix Rojas

{"title":"Power Imbalance Analysis of Modular Multilevel Converter With Distributed Energy Systems","authors":"Tomas Salvadores;Javier Pereda;Félix Rojas","doi":"10.1109/OJIES.2024.3361167","DOIUrl":"10.1109/OJIES.2024.3361167","url":null,"abstract":"The modular multilevel converter (MMC) can integrate distributed energy systems (DES), such as a battery energy storage system, to expand its functionalities and carry out multiple simultaneous tasks. However, a DES induces power imbalances within the MMC, which affects the operating currents and voltages of the converter. This phenomenon has been partially covered in recent works, but an analytical analysis has not yet been carried out to see the behavior and implications in different MMC-DES applications. This article introduces a novel analytical analysis of the power imbalances between MMC clusters. It pioneers the development of general equations and imbalance capability metrics, enabling the assessment of maximum currents and voltages supported by the MMC clusters. The developed tools allow the evaluation of any MMC-DES application regarding the current and voltage rating requirements of MMC clusters. The analysis shows that the MMC operating mode can substantially restrain or enlarge its imbalance capacity, affecting its suitability for different DES applications. While it needs around 33% current overrating in the worst imbalances, under some operating modes it can reach most imbalances without requiring current overrating. The ac compensation mode is much more capable of achieving imbalances than the dc compensation mode, reaching 88.37% and 16.74% of the imbalance points, respectively, without requiring any overrating.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"109-121"},"PeriodicalIF":8.5,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10433267","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139947272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators 自动合成循环神经元，从数控机床操作员身上进行模仿学习

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-02-07 DOI: 10.1109/OJIES.2024.3363500

Hoa Thi Nguyen;Roland Olsson;Øystein Haugen

{"title":"Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators","authors":"Hoa Thi Nguyen;Roland Olsson;Øystein Haugen","doi":"10.1109/OJIES.2024.3363500","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3363500","url":null,"abstract":"Analyzing time series data in industrial settings demands domain knowledge and computer science expertise to develop effective algorithms. AutoML approaches aim to automate this process, reducing human bias and improving accuracy and cost-effectiveness. This article applies an evolutionary algorithm to synthesize recurrent neurons optimized for specific datasets. This adds another layer to the AutoML framework, targeting the internal structure of neurons. We developed an imitation learning control system for an industry CNC machine to enhance operators' productivity. We specifically examine two recorded operator actions: adjusting the engagement rates for linear feed rate and spindle velocity. We compare the performance of our evolved neurons with support vector machine and four well-established neural network models commonly used for time series data: simple recurrent neural networks, long-short-term-memory, independently recurrent neural networks, and transformers. The results demonstrate that the neurons evolved via the evolutionary approach exhibit lower syntactic complexity than LSTMs and achieve lower error rates than other networks. They yield error rates 270% lower for the first operation action, while the error rates are 20% lower for the second action. We also show that our evolutionary algorithm is capable of creating skip-connections and gating mechanisms adapted to the specific characteristics of our dataset.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"91-108"},"PeriodicalIF":8.5,"publicationDate":"2024-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10423805","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139937098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PyMem: A Graphical User Interface Tool for Neuromemristive Hardware–Software Co-Design PyMem：用于神经迷思硬件-软件协同设计的图形用户界面工具

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-02-06 DOI: 10.1109/OJIES.2024.3363093

Aswani Radhakrishnan;Jushnah Palliyalil;Sreeja Babu;Anuar Dorzhigulov;Alex James

{"title":"PyMem: A Graphical User Interface Tool for Neuromemristive Hardware–Software Co-Design","authors":"Aswani Radhakrishnan;Jushnah Palliyalil;Sreeja Babu;Anuar Dorzhigulov;Alex James","doi":"10.1109/OJIES.2024.3363093","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3363093","url":null,"abstract":"The hardware implementation of neuromorphic system requires energy and area-efficient hardware. Memristor-based hardware architectures is a promising approach that naturally mimics the switching behavior of the neuron models. However, to build complex neural systems, it is a tedious process to select the right memristor models and architectures that are suitable to be used in a range of realistic conditions. To simplify the design and development of neuromemristive architectures, we present a web-based graphical user interface (GUI) called “PyMem” that uses Keras Python to implement multiple memristor models on multiple neural architectures that can be used to analyze their working under a wide range of hardware variability. Without the need for programming, the GUI provides options for adding variability to the memristors and observing the neural network behavior under realistic conditions. The tool has options to characterize the ideal (software) and nonideal (hardware) for performance analysis including accuracy, precision, recall, and relative current error values.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"81-90"},"PeriodicalIF":8.5,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10423246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139916626","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Airflow Cooling Mechanism for High Power-Density Permanent Magnet Motor 用于高功率密度永磁电机的气流冷却机制

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-31 DOI: 10.1109/OJIES.2024.3360509

Awungabeh Flavis Akawung;Besong John Ebot;Yasutaka Fujimoto

{"title":"Airflow Cooling Mechanism for High Power-Density Permanent Magnet Motor","authors":"Awungabeh Flavis Akawung;Besong John Ebot;Yasutaka Fujimoto","doi":"10.1109/OJIES.2024.3360509","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3360509","url":null,"abstract":"High power-density electric machines present the benefits of high torque and speed. However, this generally comes with heating problems characterized by high temperatures that affect performance. Conventional approaches to address overheating are to include cooling fans or jackets within the stator core of the machine. This approach is challenging to implement in small-size high power-density machines. In this article, a cooling mechanism integrated in the rotor of a high power-density permanent magnet motor is proposed. It comprises a set of six holes, shrouded within a hollow shaft. The mechanism is based on conditioning air due to a centrifugal force that is produced by the rotational speed of the rotor from the inlet. A theoretical model based on flow resistance network is proposed to analyze the airflow rate. An analytical thermal model based on lumped parameter thermal network is developed to analyze the effect of the flow rate on the temperature distribution in the motor. Also, a simulation analysis model was conducted using computational fluid dynamics to analyze the effect of air flowing in the motor. An experimental prototype is developed to verify, validate, and evaluate the proposed cooling model. The cooling system is effective in reducing temperatures from speeds above 6000 min\u0000<sup>−1</sup>\u0000.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"67-80"},"PeriodicalIF":8.5,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10417077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139908592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iterative Learning Observer-Based High-Precision Motion Control for Repetitive Motion Tasks of Linear Motor-Driven Systems 基于迭代学习观测器的高精度运动控制，适用于线性电机驱动系统的重复性运动任务

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-29 DOI: 10.1109/OJIES.2024.3359951

Zhitai Liu;Xinghu Yu;Weiyang Lin;Juan J. Rodríguez-Andina

{"title":"Iterative Learning Observer-Based High-Precision Motion Control for Repetitive Motion Tasks of Linear Motor-Driven Systems","authors":"Zhitai Liu;Xinghu Yu;Weiyang Lin;Juan J. Rodríguez-Andina","doi":"10.1109/OJIES.2024.3359951","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3359951","url":null,"abstract":"Repetitive motion is one of the most common motion tasks in linear motor (LM)-driven system. The LM performs repetitive motion based on a periodic target trajectory under control, thus leading to periodic characteristics in certain system uncertainties. For this type of task, this article proposes an iterative learning observer-based high-precision motion control scheme that comprehensively considers high-accuracy model compensation and periodic uncertainties estimation. A recursive least squares (RLS) algorithm-based indirect adaptation strategy is used to achieve high-accuracy parameter estimation and model compensation. A saturated constrained-type iterative learning observer is designed to effectively estimate and compensate for periodic uncertainties. The closed-loop stability of the system is guaranteed in the presence of both periodic and nonperiodic uncertainties due to the composite adaptive robust control design. Comparative experiments are conducted on an LM-driven motion platform to verify the effectiveness and advantages of the proposed control scheme. Furthermore, the experimental results confirm the enhancement of both the transient and steady-state performance of the system.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"54-66"},"PeriodicalIF":8.5,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10416358","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139715144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiobjective Hyperparameter Optimization of Artificial Neural Networks for Optimal Feedforward Torque Control of Synchronous Machines 多目标超参数优化人工神经网络，实现同步电机的最佳前馈转矩控制

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-22 DOI: 10.1109/OJIES.2024.3356721

Niklas Monzen;Florian Stroebl;Herbert Palm;Christoph M. Hackl

引用次数: 0

Reinforcement Learning-Based Adaptive Control of a Piezo-Driven Nanopositioning System 基于强化学习的压电驱动纳米定位系统自适应控制

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-17 DOI: 10.1109/OJIES.2024.3355192

Liheng Chen;Qingsong Xu

引用次数: 0

On the Detection of Neutral Loss, Islanding, and Meter Tampering in Electrical Installations 关于检测电气装置中的中性线损耗、孤岛和篡改电表问题

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-16 DOI: 10.1109/OJIES.2024.3354799

Syllas Frantzeskakis;Nick Rigogiannis;Christos Christodoulou;Nick Papanikolaou

{"title":"On the Detection of Neutral Loss, Islanding, and Meter Tampering in Electrical Installations","authors":"Syllas Frantzeskakis;Nick Rigogiannis;Christos Christodoulou;Nick Papanikolaou","doi":"10.1109/OJIES.2024.3354799","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3354799","url":null,"abstract":"Neutral conductor loss on the upstream network of an electrical installation, as well as unintentional islanding operation, are two critical issues directly related to the safety of both human life and equipment of the electrical installation. Furthermore, another critical issue is meter tampering, which affects the operation and development of national power sectors. The state-of-the-art methods deal with those issues separately, without providing a holistic solution; moreover, they are facing several challenges in the prospect of mass storage installations at buildings. This article introduces a new scheme for the detection of neutral loss at the upstream network, the unintentional islanding conditions, and meter tampering simultaneously. In this context, a suitable technical solution is given by using one low-power H-bridge inverter and a current transformer, along with voltage and current measuring instruments. The detection scheme is based on the injection of a (zero-sequence) 12th harmonic voltage component in series with the utility voltage and the monitoring of the corresponding harmonic current component. The theoretical analysis of the proposed technique is discussed, whereas its effectiveness is validated through simulation and experimental results.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"1-12"},"PeriodicalIF":8.5,"publicationDate":"2024-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10400944","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139654493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EV Smart Charging in Distribution Grids–Experimental Evaluation Using Hardware in the Loop Setup 配电网中的电动汽车智能充电--利用环路中的硬件设置进行实验评估

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2024-01-10 DOI: 10.1109/OJIES.2024.3352265

Yunhe Yu;Lode De Herdt;Aditya Shekhar;Gautham Ram Chandra Mouli;Pavol Bauer

{"title":"EV Smart Charging in Distribution Grids–Experimental Evaluation Using Hardware in the Loop Setup","authors":"Yunhe Yu;Lode De Herdt;Aditya Shekhar;Gautham Ram Chandra Mouli;Pavol Bauer","doi":"10.1109/OJIES.2024.3352265","DOIUrl":"https://doi.org/10.1109/OJIES.2024.3352265","url":null,"abstract":"The rising demand for electric vehicles (EVs) in the face of limited grid capacity encourages the development and implementation of smart charging (SC) algorithms. Experimental validation plays a pivotal role in advancing this field. This article formulates a hierarchical mixed integer programming EV SC algorithm designed for low voltage (LV) distribution grid applications. A flexible receding horizon scheme is introduced in response to system uncertainties. It also considers the practical constraints in protocols, such as IEC/ISO 15118 and IEC 61851-1. The proposed algorithm is verified and assessed in a power hardware-in-the-loop testbed that incorporates models of real LV distribution grids. Furthermore, the algorithm's capabilities are examined through eight scenarios, out of which four focus on the uncertainties of the input data and two address the engagement of extra grid capacity restrictions. The results demonstrate that the SC algorithm adequately lowers the EV charging cost while fulfilling the charging demand, and substantially reduces the peak power as well as the overloading duration, even when faced with input data uncertainty. The additional grid restrictions in place are proven to improve peak demand reduction and overloading mitigation further. Finally, the limitations and potentials of the developed algorithm are scrutinized.","PeriodicalId":52675,"journal":{"name":"IEEE Open Journal of the Industrial Electronics Society","volume":"5 ","pages":"13-27"},"PeriodicalIF":8.5,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10387706","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139676258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Computationally Efficient MPC for Modular Multilevel Matrix Converters Operating With Fixed Switching Frequency 采用固定开关频率工作的模块化多电平矩阵转换器的计算高效 MPC

IF 8.5

IEEE Open Journal of the Industrial Electronics Society Pub Date : 2023-12-28 DOI: 10.1109/OJIES.2023.3347101

Rodrigo H. Cuzmar;Andrés Mora;Javier Pereda;Ricardo P. Aguilera;Pablo Poblete;Sebastián Neira

引用次数: 0