2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)最新文献

Linear Control Compensator for a Variable-Transformer in Wide-Voltage Power Converters 宽电压变换器中可变变压器的线性控制补偿器

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831508

Diego Bernal Cobaleda, Fanghao Tian, C. Suarez, Miguel Vivert, W. Martínez

引用次数: 1

Insulation Life Loss Prediction of an Oil-Filled Power Transformer Using Adaptive Neuro-Fuzzy Inference System 基于自适应神经模糊推理系统的充油电力变压器绝缘寿命损失预测

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831734

Hulisani Matsila, P. Bokoro

引用次数: 0

Development and Testing of a Wearable Sensor based Driving Confidence Monitoring System for a Prototype Electric Vehicle 基于可穿戴传感器的电动样车驾驶信心监测系统的研制与测试

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831479

Daghan Dogan, T. Acarman, S. Bogosyan

{"title":"Development and Testing of a Wearable Sensor based Driving Confidence Monitoring System for a Prototype Electric Vehicle","authors":"Daghan Dogan, T. Acarman, S. Bogosyan","doi":"10.1109/isie51582.2022.9831479","DOIUrl":"https://doi.org/10.1109/isie51582.2022.9831479","url":null,"abstract":"This study aims to detect the driving confidence level by measuring skin electrical conductance and traction motor torque. Measurement data of 38 drivers were collected, feature vectors (mean, standard deviation, kurtosis, skewness) were extracted, and the classes of the drivers were determined while comparing to the safety expert driver data. The best classification method for the galvanic skin response sensor and the current sensor of the electric traction motor is determined. Fine kNN (fine k-nearest neighbors) is the most successful classification method for the galvanic skin response sensor data and the artificial neural network is the most successful method for the current sensor data. In the second part of the study, the driving confidence of the drivers is elaborated around the road junctions where the driver has to detect and prevent possible hazards. Logged data of the galvanic skin sensor, current sensor and velocity measurement is analyzed to monitor the confidence level while approaching and passing two junctions on the pre-specified route. In the third part of the study, based on the GSR sensor measurement, electric motor torque is intervened when a deviation between the average value and measured value. An experimental setup including the RFID card containing the average skin conductivity of each driver is presented.","PeriodicalId":194172,"journal":{"name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121057934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Formal Methods to Specify Data-Driven Cyber-Physical Systems 使用形式化方法指定数据驱动的信息物理系统

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831686

José Luís Conradi Hoffmann, Leonardo Passig Horstmann, Matheus Wagner, Felipe Vieira, M. M. Lucena, A. A. Fröhlich

{"title":"Using Formal Methods to Specify Data-Driven Cyber-Physical Systems","authors":"José Luís Conradi Hoffmann, Leonardo Passig Horstmann, Matheus Wagner, Felipe Vieira, M. M. Lucena, A. A. Fröhlich","doi":"10.1109/isie51582.2022.9831686","DOIUrl":"https://doi.org/10.1109/isie51582.2022.9831686","url":null,"abstract":"This paper presents a review of formal methods, covering both timed automata and Signal Temporal Logic (STL) approaches, and proposes an integration of formal methods with a data-driven representation of an Autonomous Vehicles (AV) case study. The data-driven representation of the system is done through the concept of SmartData, a data construct that includes concepts of location, timing, and semantics, providing an alternative to represent critical systems through the data they rely on. The timing and dependency relationship between different SmartData are derived into an STL expression that specifies the property monitors to verify each piece of data. The same verification is also presented in the form of timed automata, a closer representation of the tools adopted for runtime verification. The SmartData representation and STL and timed automata models are depicted through a case study considering an autonomous vehicles application. Finally, we demonstrate a general scenario for mapping data-driven systems using SmartData directly into timed automata.","PeriodicalId":194172,"journal":{"name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126133117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

An Innovative Lighting Recognition System Based On Color Rendering Index and Computational Neural Networking 基于显色指数和计算神经网络的照明识别系统

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831603

F. Fambrini, D. G. Caetano, Rangel Arthur, Y. Iano, Ana Marina Santos, Guilherme Ferretti Rissi

{"title":"An Innovative Lighting Recognition System Based On Color Rendering Index and Computational Neural Networking","authors":"F. Fambrini, D. G. Caetano, Rangel Arthur, Y. Iano, Ana Marina Santos, Guilherme Ferretti Rissi","doi":"10.1109/isie51582.2022.9831603","DOIUrl":"https://doi.org/10.1109/isie51582.2022.9831603","url":null,"abstract":"Identifying which type of lamp is installed on each public lighting pole and evaluating its luminous power is important, as the new LED-type models are much more economical in terms of energy, and energy distributors need to know the energy consumption of lighting. In Brazil, there are the following types of lamps in public lighting: incandescent, mercury vapor, sodium vapor, “mixed” lamps (composed of a mercury vapor arc tube in series with an incandescent tungsten filament), metallic lamps and modern LED (Light Emitting Diodes) type lamps. In this article, the authors describe the experimental results of the development of an automated lamp recognition system for street lighting based on the light pattern of each lamp, considering an innovative optical method that uses the Color Rendering Index (CRI) phenomenon and color cards. The objective of this study is to propose an alternative and low-cost technique in opposite use of the spectrophotometer, in order to identify the models of lamps installed on public lighting poles, from the light emitted only, using machine learning techniques and RNN.","PeriodicalId":194172,"journal":{"name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123712690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rule-based Control and Equivalent Consumption Minimization Strategies for Hybrid Electric Vehicle Powertrains: a Hardware-in-the-loop Assessment 基于规则的混合动力汽车动力系统控制与等效能耗最小化策略:硬件在环评估

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831702

P. G. Anselma

{"title":"Rule-based Control and Equivalent Consumption Minimization Strategies for Hybrid Electric Vehicle Powertrains: a Hardware-in-the-loop Assessment","authors":"P. G. Anselma","doi":"10.1109/isie51582.2022.9831702","DOIUrl":"https://doi.org/10.1109/isie51582.2022.9831702","url":null,"abstract":"Energy management systems are crucial in hybrid electric vehicles (HEVs). Other than enhanced energy economy, a proper energy management system must guarantee acceptable driving comfort, compliance with the allowed battery state-of-charge window, and on-board computational efficiency. While several studies from the literature have compared different state-of-the-art real-time HEV powertrain energy management strategies, not much work has been performed on the hardware-in-the-loop (HIL) assessment of these control approaches. This paper aims at answering the identified research need by performing an experimental HIL assessment of different state-of-the-art HEV control strategies including a rule-based control (RBC) approach and three different formulations of equivalent consumption minimization strategy (ECMS), both of traditional and adaptive type. A parallel-through-the-road HEV is considered for this case study. Various assessment criteria are retained including HEV fuel economy, measured computational time, and comfort of the ride in terms of frequency of de/activation events and smoothness of the controlled value of torque over time for the internal combustion engine. Obtained results suggest that the RBC approach can achieve improved performance in almost all the retained evaluation criteria. The traditional ECMS can outperform RBC in terms of fuel economy, yet by undermining both ride comfort and compliance with the battery SOC window. Finally, an adaptive ECMS can outperform the RBC in terms of fuel economy while ensuring acceptable comfort and compliance with the battery SOC window, yet at a significant computational cost increase.","PeriodicalId":194172,"journal":{"name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126767991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep Reinforcement Learning for DC-DC converter parameters optimization 基于深度强化学习的DC-DC变换器参数优化

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831660

Fanghao Tian, Diego Bernal Cobaleda, W. Martínez

引用次数: 0

SiC Traction Power Converter for Electromobility 用于电动汽车的SiC牵引电源变换器

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831733

J. Štěpánek, J. Novotný, Š. Janouš

引用次数: 0

An interpretable classification approach for Solar PV load profiles using decision trees 一种基于决策树的太阳能光伏负荷分布可解释分类方法

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831528

Wenhua Ling, Geordie Dalzell, Xinghuo Yu, B. Mcgrath, P. Sokolowski

{"title":"An interpretable classification approach for Solar PV load profiles using decision trees","authors":"Wenhua Ling, Geordie Dalzell, Xinghuo Yu, B. Mcgrath, P. Sokolowski","doi":"10.1109/isie51582.2022.9831528","DOIUrl":"https://doi.org/10.1109/isie51582.2022.9831528","url":null,"abstract":"As penetration of domestic solar PV generation grows there is a need for electricity distribution network operators (DNOs) to have methods for detecting solar PV generators attached to their networks. The cause of this requirement is the need for regulatory compliance, safety of equipment, and protection of workers and consumers. Smart metering is a key component of smart grids and smart metering data creates avenues to address this issue. Algorithmic methods to identify solar PV generation from consumption data will allow DNOs to maintain up to date knowledge of their networks allowing them to address any issues of safety or compliance. In this paper we investigate if classification of smart metering electricity consumption daily load profiles as solar or non-solar is possible with decision tree classifiers. We compare decision trees on our data after different forms of preprocessing are applied. We then apply this approach to smart metering datasets of solar and non-solar customers and show the ability to classify solar PV daily load profiles with up to 92% accuracy. This contributes to the knowledge about smart metering data analytics methods that can be used by smart grid stakeholders.","PeriodicalId":194172,"journal":{"name":"2022 IEEE 31st International Symposium on Industrial Electronics (ISIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122601509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ablation Study of a Person Re-Identification on a Mobile Robot Using a Depth Camera 基于深度相机的移动机器人人体再识别消融研究

2022 IEEE 31st International Symposium on Industrial Electronics (ISIE) Pub Date : 2022-06-01 DOI: 10.1109/isie51582.2022.9831503

S. Flores, J. Jost

引用次数: 1