IFAC-PapersOnLine最新文献_第5页

Validation of Phasor-Domain Transmission and Distribution Co-simulation Against Electromagnetic Transient Simulation⁎ 根据电磁瞬态仿真验证相量域输配电协同仿真⁎

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.488

Yousu Chen, Yuan Liu

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引用次数: 0

Digital Sliding Mode Control of a 3-Phase AC-DC rectifier for Ultra-Fast Charging of EV Battery⁎ 用于电动汽车电池超快充电的三相交直流整流器的数字滑动模式控制⁎

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.520

Seyedamin Valedsaravi , Kuntal Mandal , Abdelali El Aroudi , Luis Martínez-Salamero

{"title":"Digital Sliding Mode Control of a 3-Phase AC-DC rectifier for Ultra-Fast Charging of EV Battery⁎","authors":"Seyedamin Valedsaravi , Kuntal Mandal , Abdelali El Aroudi , Luis Martínez-Salamero","doi":"10.1016/j.ifacol.2024.07.520","DOIUrl":"10.1016/j.ifacol.2024.07.520","url":null,"abstract":"<div><p>This paper describes a digital sliding mode control (SMC) technique applied to a three-phase four-wire rectifier operating at a fixed frequency for ultra-fast charging of electric vehicle (EV) battery. The control algorithm employs three decoupled sliding mode controllers to achieve loss-free resistor (LFR) behavior in each phase for power factor correction (PFC). The design of the sliding mode controller is twofold. The first one is to guarantee convergence of the sliding variable to zero. The equivalent control and the discrete-time dynamic model of the rectifier are obtained by imposing sliding-mode regime in discrete-time. The second one is to stabilize the inner-loop under the obtained control law. Theoretically, the resulting inner-loop is stable with a deadbeat behavior in the inner current loop. The results are validated by numerical simulations using on a 350 kW AC-DC rectifier for EV battery ultra-fast charging applications. The numerical simulation results performed on the switched model implemented in PSIM© software are in close agreement with the theoretical analysis.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 13","pages":"Pages 430-435"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324006190/pdf?md5=c2f9cb1d985e3dd10ccda86ba67036a6&pid=1-s2.0-S2405896324006190-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141993746","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

An overview of the current Advanced Techniques for Frequency Regulation in grid-connected and off-grid Microgrids. 概述当前用于并网和离网微电网频率调节的先进技术。

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.541

M. Laamim , A. Rochd , B. El Barkouki , O. Mahir , S. El Hamaoui , M. El Qasery , A. El Fadili

{"title":"An overview of the current Advanced Techniques for Frequency Regulation in grid-connected and off-grid Microgrids.","authors":"M. Laamim , A. Rochd , B. El Barkouki , O. Mahir , S. El Hamaoui , M. El Qasery , A. El Fadili","doi":"10.1016/j.ifacol.2024.07.541","DOIUrl":"10.1016/j.ifacol.2024.07.541","url":null,"abstract":"<div><p>The integration of renewable energy sources into the power system is an important step towards a sustainable energy transition. This transition could subsequently introduce substantial variability that critically impacts key operational parameters, such as frequency and voltage. This variability poses significant challenges, especially within microgrid configuration, both in grid-connected and isolated modes. Therefore, ensuring the stability of these parameters I paramount of their operational efficiency, reliability, and longevity. Despite these challenges, recent advancements in the field have led to the development of numerous advanced methodologies and control strategies designed to mitigate the impact of renewable sources on microgrid frequency stability. This paper provides a comprehensive overview of these state-of-the-art technologies and methodologies, including cutting-edge technologies such as adaptive load frequency control and Time-series prediction-based approaches. It offers insights into their application, effectiveness, and advantages in frequency control during microgrid operation, contributing to the ongoing discourse on integrating renewable energy sources with enhanced grid stability. Moreover, the discussion section provides insights and barriers impacting the implementation of these technologies in the current microgrid system and the power grid in general.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 13","pages":"Pages 558-562"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324006402/pdf?md5=44d46f470e3c4daf39a73cfaef797639&pid=1-s2.0-S2405896324006402-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141993775","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

Loewner functions for bilinear systems 双线性系统的 Loewner 函数

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.071

Pauline Kergus , Ion Victor Gosea , Mihaly Petreczky

引用次数: 0

System Identification for Battery State Prediction and Lifespan Estimation 电池状态预测和寿命估算的系统识别

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.215

Chenyi Li, Long Zhang

{"title":"System Identification for Battery State Prediction and Lifespan Estimation","authors":"Chenyi Li, Long Zhang","doi":"10.1016/j.ifacol.2024.07.215","DOIUrl":"10.1016/j.ifacol.2024.07.215","url":null,"abstract":"<div><p>In this paper, a nonlinear system Identification method, wavelet-network-based Nonlinear Auto-Regressive Exogenous (NLARX) approach, is employed for battery state estimation and lifespan estimation. More specifically, three key battery parameters and health metrics, including temperature, voltage and State of Charge (SOC), are estimated and these parameters are essential for condition or state monitoring. Further, State of Health (SOH), crucial for forecasting the battery remaining useful life, is also predicted. Two open datasets are used to train and validated the performance of the proposed method. For temperature and voltage forecasting, the NLARX model outperforms the existing Thermal Single Particle Model with electrolyte (TSPMe) for prediction horizons under 600 seconds. In SOC estimations, the NLARX method produces consistent 15-second ahead prediction results even only using a small percentage of training data, while the SOH estimation, the proposed metho provides precise SOH variation prediction for 400 post cycles with less than 10% of the batterys life for training. Extensive results demonstrates that the NLARX model’s promise for the precise prediction of key battery parameters and health metrics and it can be used as a useful tool for battery fault detection and remaining useful life prediction.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 4","pages":"Pages 186-191"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324002994/pdf?md5=82e388d405a5d66317792ba47008e123&pid=1-s2.0-S2405896324002994-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141997758","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

Verification of Diagnosability for Cyber-Physical Systems via Hybrid Barrier Certificates⁎ 通过混合障碍证书验证网络物理系统的可诊断性⁎

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.07.429

Bingzhuo Zhong , Weijie Dong , Xiang Yin , Majid Zamani

引用次数: 0

Data-Driven Robust Servo Tuning Method Using Fractional-Order PID Controller 使用分数阶 PID 控制器的数据驱动型鲁棒伺服调整方法

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.08.101

K. Jinai , N. Kawaguchi , O. Arrieta , T. Sato

引用次数: 0

Fault Classification in Reciprocating Compressors: A Comparison of Machine Learning and Deep Learning Approaches⁎ 往复式压缩机的故障分类：机器学习与深度学习方法的比较⁎

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.08.066

René-Vinicio Sánchez , Jean-Carlo Macancela , Diego Cabrera , Mariela Cerrada

引用次数: 0

Asset criticality and risk prediction via machine learning in wind farms: problem-based educational activities in a smart industry operations course 通过机器学习预测风电场的资产危急性和风险：智能工业运营课程中基于问题的教育活动

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.08.119

Christos Emmanouilidis , Ype Wijnia

{"title":"Asset criticality and risk prediction via machine learning in wind farms: problem-based educational activities in a smart industry operations course","authors":"Christos Emmanouilidis , Ype Wijnia","doi":"10.1016/j.ifacol.2024.08.119","DOIUrl":"10.1016/j.ifacol.2024.08.119","url":null,"abstract":"<div><p>Smart industry and Industry 4.0 are terms which are often used interchangeably. They characterise industry that capitalises on optimising processes through the successful integration of advanced digitalisation and manufacturing technologies, while applying sound organisation and human factors management principles. Equipping the current and future generation professionals with the necessary skills and personal qualities needed for the transition to Industry 4.0, and its extension to Industry 5.0 has been targeted by academic and professional education. Lessons learned from existing studies point to problem-based learning as an effective mechanism for the internalisation of interdisciplinary concepts, methods, and technologies. This paper outlines the formulation and experience gained from educational activities within the context of a smart industry postgraduate MSc course. The aim was to bring together methods for process and data integration, technologies such as machine learning, and management aspects, targeting domains relevant to smart industry. An educational activity was designed relevant to risk prediction within the asset management of wind farms. With scenarios of diverse criticality assumptions, marking the importance of Industry 5.0, results obtained from the educational activity show that students excelling in individual dimensions of smart industry are valuable contributors in a team setting, but a sound holistic understanding and competences across all three pillars of smart industry are needed for best learning objectives.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 8","pages":"Pages 192-197"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324008413/pdf?md5=342d268ffa69645852eb3d3a14d15b10&pid=1-s2.0-S2405896324008413-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148277","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

Predicting Defect Rates of Printed Circuit Board Assemblies: Towards Zero Defect Manufacturing and Zero-Maintenance Strategies 预测印刷电路板组件的缺陷率：实现零缺陷制造和零维护战略

IFAC-PapersOnLine Pub Date : 2024-01-01 DOI: 10.1016/j.ifacol.2024.08.056

E. Miedema , H. Kortman , C. Emmanouilidis

{"title":"Predicting Defect Rates of Printed Circuit Board Assemblies: Towards Zero Defect Manufacturing and Zero-Maintenance Strategies","authors":"E. Miedema , H. Kortman , C. Emmanouilidis","doi":"10.1016/j.ifacol.2024.08.056","DOIUrl":"10.1016/j.ifacol.2024.08.056","url":null,"abstract":"<div><p>Printed Circuit Boards (PCB) manufacturing is a critical part of volatile supply chains for a wide variety of products and high value assets. PCBs are expected to exhibit zero defects and be subject to zero-maintenance. However low the defect rates, defects are highly disruptive and costly. Such defects can be introduced by a multitude of reasons, including faulty parts or sub-standard manufacturing processes. While sophisticated and dedicated quality inspection systems are typically in place in production environments, they still leave room for erroneous quality control outcomes. Besides in-line or post-production quality inspection, manufacturers can exploit experience gained from historical records of past inspections to predict future defect rates. This paper presents the development of a predictive quality modelling approach, which capitalises on such historical data and domain knowledge, to predict defect rates in new production orders. Employing appropriate encoding of knowledge through data pre-processing and applying regression type of machine learning, the proposed approach is validated on a real case study from an electronics manufacturing company. The developed approach can positively contribute towards optimising consequent maintenance and warranty services and become part of a zero-defect production strategy.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 8","pages":"Pages 91-96"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324007730/pdf?md5=644474ad7953b5c46fe98c9f8da1ce10&pid=1-s2.0-S2405896324007730-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148377","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