J. Mathew, Yuamfam Yang, M. Ottavia, T. Browna, A. Zampettia, A. Carloa, A. M. Jabirb, D. Pradhan
{"title":"DSC阵列的忆阻器故障检测与修复","authors":"J. Mathew, Yuamfam Yang, M. Ottavia, T. Browna, A. Zampettia, A. Carloa, A. M. Jabirb, D. Pradhan","doi":"10.1109/DFT.2015.7315127","DOIUrl":null,"url":null,"abstract":"Fault tolerant Photovoltaic array used for green energy systems is emerging as an important area of study because of growing emphasis on reliable design. Among various photovoltaic cells Dye Solar Cell (DSC) is a promising low-cost photovoltaic (PV) technology and high energy-conversion efficiency. Recently it has been shown that it has memristive behavior as well. To efficiently support this claim, in this paper we use experimental data to characterize DSC cell and show that it exhibits memristor state behavior and developed a SPICE model. We use memristive DSC cells as sensing devices. This enables us to identify faulty cells in regular DSC. First, we present the model from the experimental data. A search algorithm is defined to identify the faulty components of the DSC array that fulfill the first requirement of a fault tolerant design. The proposed diagnosis method utilizes recently proposed fault detection solution for efficient testing of PV cells in the presence of faults. We divide the array into segments such that any faults is detectable thereby achieving high diagnosis accuracy. The proposed diagnosis method has been validated through SPICE simulation. Spare cells are to repair the faulty array.","PeriodicalId":383972,"journal":{"name":"2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fault detection and repair of DSC arrays through memristor sensing\",\"authors\":\"J. Mathew, Yuamfam Yang, M. Ottavia, T. Browna, A. Zampettia, A. Carloa, A. M. Jabirb, D. Pradhan\",\"doi\":\"10.1109/DFT.2015.7315127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fault tolerant Photovoltaic array used for green energy systems is emerging as an important area of study because of growing emphasis on reliable design. Among various photovoltaic cells Dye Solar Cell (DSC) is a promising low-cost photovoltaic (PV) technology and high energy-conversion efficiency. Recently it has been shown that it has memristive behavior as well. To efficiently support this claim, in this paper we use experimental data to characterize DSC cell and show that it exhibits memristor state behavior and developed a SPICE model. We use memristive DSC cells as sensing devices. This enables us to identify faulty cells in regular DSC. First, we present the model from the experimental data. A search algorithm is defined to identify the faulty components of the DSC array that fulfill the first requirement of a fault tolerant design. The proposed diagnosis method utilizes recently proposed fault detection solution for efficient testing of PV cells in the presence of faults. We divide the array into segments such that any faults is detectable thereby achieving high diagnosis accuracy. The proposed diagnosis method has been validated through SPICE simulation. Spare cells are to repair the faulty array.\",\"PeriodicalId\":383972,\"journal\":{\"name\":\"2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DFT.2015.7315127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DFT.2015.7315127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
摘要
由于对可靠性设计的日益重视,用于绿色能源系统的容错光伏阵列已成为一个重要的研究领域。在各种光伏电池中,染料太阳能电池(Dye Solar Cell, DSC)是一种极具发展前景的低成本、高能量转换效率的光伏电池技术。最近有研究表明,它也有记忆行为。为了有效地支持这一说法,在本文中,我们使用实验数据来表征DSC细胞,并表明它具有忆阻状态行为,并开发了SPICE模型。我们使用记忆性DSC细胞作为传感装置。这使我们能够在常规DSC中识别有缺陷的细胞。首先,我们根据实验数据建立了模型。定义了一种搜索算法来识别DSC阵列中满足容错设计第一要求的故障组件。所提出的诊断方法利用了最近提出的故障检测解决方案,以便在存在故障的情况下对光伏电池进行有效的检测。我们将阵列划分为多个片段,这样任何故障都可以检测到,从而达到较高的诊断精度。通过SPICE仿真验证了该方法的有效性。备用电池用于修复故障阵列。
Fault detection and repair of DSC arrays through memristor sensing
Fault tolerant Photovoltaic array used for green energy systems is emerging as an important area of study because of growing emphasis on reliable design. Among various photovoltaic cells Dye Solar Cell (DSC) is a promising low-cost photovoltaic (PV) technology and high energy-conversion efficiency. Recently it has been shown that it has memristive behavior as well. To efficiently support this claim, in this paper we use experimental data to characterize DSC cell and show that it exhibits memristor state behavior and developed a SPICE model. We use memristive DSC cells as sensing devices. This enables us to identify faulty cells in regular DSC. First, we present the model from the experimental data. A search algorithm is defined to identify the faulty components of the DSC array that fulfill the first requirement of a fault tolerant design. The proposed diagnosis method utilizes recently proposed fault detection solution for efficient testing of PV cells in the presence of faults. We divide the array into segments such that any faults is detectable thereby achieving high diagnosis accuracy. The proposed diagnosis method has been validated through SPICE simulation. Spare cells are to repair the faulty array.