Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535535
Shreyas Agrawal, Sumanto Dutta, Bidyut Kr. Patra
Sentiment analysis is one of the significant tasks in processing natural language by a machine. However, it is difficult for a machine to understand the feelings of a person and opinion about a topic. Many approaches have been introduced for analyzing sentiment from long text in recent past. In contrast, these approaches fail to address the small length text problem like Twitter data efficiently. Recent advances in the pre-trained contextualized embeddings like Bidirectional Encoder Representations from Transformers (BERT) show far greater accuracy than traditional embeddings. In this paper, we develop a novel architecture to tune the BERT using a Bidirectional Long Short-Term Memory (Bi-LSTM) model. A task-specific layer is incorporated along with the BERT in the proposed model. Our model extracts sentiment from short texts, especially Twitter data. The extensive experiments show the superiority of our model over state-of-the-art models in sentiment analysis task across several gold standard datasets.
{"title":"Sentiment Analysis of Short Informal Text by Tuning BERT - Bi-LSTM Model","authors":"Shreyas Agrawal, Sumanto Dutta, Bidyut Kr. Patra","doi":"10.1109/EUROCON52738.2021.9535535","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535535","url":null,"abstract":"Sentiment analysis is one of the significant tasks in processing natural language by a machine. However, it is difficult for a machine to understand the feelings of a person and opinion about a topic. Many approaches have been introduced for analyzing sentiment from long text in recent past. In contrast, these approaches fail to address the small length text problem like Twitter data efficiently. Recent advances in the pre-trained contextualized embeddings like Bidirectional Encoder Representations from Transformers (BERT) show far greater accuracy than traditional embeddings. In this paper, we develop a novel architecture to tune the BERT using a Bidirectional Long Short-Term Memory (Bi-LSTM) model. A task-specific layer is incorporated along with the BERT in the proposed model. Our model extracts sentiment from short texts, especially Twitter data. The extensive experiments show the superiority of our model over state-of-the-art models in sentiment analysis task across several gold standard datasets.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125903995","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535543
N. Himabindu, Santoshkumar Hampannavar, M. Swapna, K. Patil
In this paper, wind speed assessment of a wind site located in BELAGAVI under warm humid climatic zone is proposed. Weibull and Rayleigh models were used for the statistical analysis and typical meteorological year (TMY) data was considered. Rayleigh model was found to be suitable compared to Weibull model for BELAGAVI site. The techno-economic analysis of a community microgrid in the same location was carried out considering hybrid renewable energy system for grid connected and off grid system. Promising results were obtained in terms of model and cost.
{"title":"Wind Speed Assessment and Techno-Economic Analysis of a Community Microgrid in Warm and Humid Climate Zone of India","authors":"N. Himabindu, Santoshkumar Hampannavar, M. Swapna, K. Patil","doi":"10.1109/EUROCON52738.2021.9535543","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535543","url":null,"abstract":"In this paper, wind speed assessment of a wind site located in BELAGAVI under warm humid climatic zone is proposed. Weibull and Rayleigh models were used for the statistical analysis and typical meteorological year (TMY) data was considered. Rayleigh model was found to be suitable compared to Weibull model for BELAGAVI site. The techno-economic analysis of a community microgrid in the same location was carried out considering hybrid renewable energy system for grid connected and off grid system. Promising results were obtained in terms of model and cost.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121796111","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535604
A. Panwar, Rishika Yadav, Kishor Mishra, Siddharth Gupta
The newly detected virus also called coronavirus spreads the disease Covid19. World Health Organization (WHO) confirmed this virus as a worldwide pandemic as it has infected millions of people and has taken away many lives across the globe. An infection caused by Covid19 disease majorly destroys the respiratory tract of human beings that ends with multiple organ failures or death in the worst case. In the present work, chest radiographs were provided as input to various deep learning CNN architectures for the purpose of feature extraction. After extracting the features, the images were provided as the input to various machine learning classifiers that classify the chest radiographs as Covid-19 positive, pneumonia infection, or healthy scans.
{"title":"Deep Learning Techniques for the Real Time Detection of Covid19 and Pneumonia using Chest Radiographs","authors":"A. Panwar, Rishika Yadav, Kishor Mishra, Siddharth Gupta","doi":"10.1109/EUROCON52738.2021.9535604","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535604","url":null,"abstract":"The newly detected virus also called coronavirus spreads the disease Covid19. World Health Organization (WHO) confirmed this virus as a worldwide pandemic as it has infected millions of people and has taken away many lives across the globe. An infection caused by Covid19 disease majorly destroys the respiratory tract of human beings that ends with multiple organ failures or death in the worst case. In the present work, chest radiographs were provided as input to various deep learning CNN architectures for the purpose of feature extraction. After extracting the features, the images were provided as the input to various machine learning classifiers that classify the chest radiographs as Covid-19 positive, pneumonia infection, or healthy scans.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125293607","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535599
Roman Statkevych, S. Stirenko, Yuri G. Gordienko
Segmentation approaches based on deep neural networks are researched for the microscopical images of the human kidney tissues. Several existing methods, used for medical imaging analysis and based on neural networks, were examined. Among several U-Net architectures, which are widely used for image segmentation, some their variations demonstrated the quite high performance despite the 4 times lower model size. As a result, the reasonable precision was obtained by a rudimentary network architectures and limited train time augmentations. It will open the promising perspectives for their deployment of the Edge Computing devices with the limited computing resources.
{"title":"Human Kidney Tissue Image Segmentation by U-Net Models","authors":"Roman Statkevych, S. Stirenko, Yuri G. Gordienko","doi":"10.1109/EUROCON52738.2021.9535599","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535599","url":null,"abstract":"Segmentation approaches based on deep neural networks are researched for the microscopical images of the human kidney tissues. Several existing methods, used for medical imaging analysis and based on neural networks, were examined. Among several U-Net architectures, which are widely used for image segmentation, some their variations demonstrated the quite high performance despite the 4 times lower model size. As a result, the reasonable precision was obtained by a rudimentary network architectures and limited train time augmentations. It will open the promising perspectives for their deployment of the Edge Computing devices with the limited computing resources.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127880572","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535547
L. Herenčić, Perica Ilak, I. Rajšl, Marko Kelava
Local energy trading is a concept that allows trading between distribution grid participants such as consumers, producers, and prosumers on a local level in a transparent and competitive way. This can provide better local demand-supply balancing, decrease voltage deviations, and improve social welfare. However, economic feasibility of implementation of such a concept greatly depends on regulatory framework, as certain regulatory provisions can either lead to barriers and costs that can undermine the potential benefits of local energy trading, or support implementation of such projects. In this paper, feasibility of local energy trading under different variations of regulatory framework are assessed and implications on market participants and energy balance in distribution grids analyzed. It is shown that regulatory provisions have high influence on potential benefits and implementation of local energy trading in wider scope.
{"title":"Local Energy Trading Under Emerging Regulatory Frameworks: Impacts on Market Participants and Power Balance in Distribution Grids","authors":"L. Herenčić, Perica Ilak, I. Rajšl, Marko Kelava","doi":"10.1109/EUROCON52738.2021.9535547","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535547","url":null,"abstract":"Local energy trading is a concept that allows trading between distribution grid participants such as consumers, producers, and prosumers on a local level in a transparent and competitive way. This can provide better local demand-supply balancing, decrease voltage deviations, and improve social welfare. However, economic feasibility of implementation of such a concept greatly depends on regulatory framework, as certain regulatory provisions can either lead to barriers and costs that can undermine the potential benefits of local energy trading, or support implementation of such projects. In this paper, feasibility of local energy trading under different variations of regulatory framework are assessed and implications on market participants and energy balance in distribution grids analyzed. It is shown that regulatory provisions have high influence on potential benefits and implementation of local energy trading in wider scope.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127747043","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535594
B. Bairwa, Santoshkumar Hampannavar, Kaushik S Vishal, K. Bhargavi
This work shows the modeling and simulation-based health analysis for the lithium-ion battery. In the lithiumion batteries health is the burning issue. In this work health is predicted for the lithium-ion single cell. The lithium-ion generic model is trained by the various number of charging and discharging cycles 100 cycle to 1000 cycles for the analysis. Lithium-ion battery voltage is predicted with aging at constant discharging rate 1C. The capacity of the battery compared with the SoC of the with time and voltage. Nominal 3.8 volt and 2Ah rated Lithium Ion NMC cell have been investigated for this work .This study exhibits the lithium ion battery health condition with higher use of the battery in the everyday day life. The simulation results show the overall capacity fading behaviour in the proposed work.
{"title":"Modeling and Simulation for Capacity Fade Prediction of Lithium-Ion Battery","authors":"B. Bairwa, Santoshkumar Hampannavar, Kaushik S Vishal, K. Bhargavi","doi":"10.1109/EUROCON52738.2021.9535594","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535594","url":null,"abstract":"This work shows the modeling and simulation-based health analysis for the lithium-ion battery. In the lithiumion batteries health is the burning issue. In this work health is predicted for the lithium-ion single cell. The lithium-ion generic model is trained by the various number of charging and discharging cycles 100 cycle to 1000 cycles for the analysis. Lithium-ion battery voltage is predicted with aging at constant discharging rate 1C. The capacity of the battery compared with the SoC of the with time and voltage. Nominal 3.8 volt and 2Ah rated Lithium Ion NMC cell have been investigated for this work .This study exhibits the lithium ion battery health condition with higher use of the battery in the everyday day life. The simulation results show the overall capacity fading behaviour in the proposed work.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130733778","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535569
Habib Ibrahim, F. Özkaynak
The cryptology science has gradually gained importance with our digitalized lives. Ensuring the security of data transmitted, processed and stored across digital channels is a major challenge. One of the frequently used components in cryptographic algorithms to ensure security is substitution-box structures. Random selection-based substitution-box structures have become increasingly important lately, especially because of their advantages to prevent side channel attacks. However, the low nonlinearity value of these designs is a problem. In this study, a dataset consisting of twenty different substitution-box structures have been publicly presented to the researchers. The fact that the proposed dataset has high nonlinearity values will allow it to be used in many practical applications in the future studies. The proposed dataset provides a contribution to the literature as it can be used both as an input dataset for the new post-processing algorithm and as a countermeasure to prevent the success of side-channel analyzes.
{"title":"A Random Selection Based Substitution-box Structure Dataset for Cryptology Applications","authors":"Habib Ibrahim, F. Özkaynak","doi":"10.1109/EUROCON52738.2021.9535569","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535569","url":null,"abstract":"The cryptology science has gradually gained importance with our digitalized lives. Ensuring the security of data transmitted, processed and stored across digital channels is a major challenge. One of the frequently used components in cryptographic algorithms to ensure security is substitution-box structures. Random selection-based substitution-box structures have become increasingly important lately, especially because of their advantages to prevent side channel attacks. However, the low nonlinearity value of these designs is a problem. In this study, a dataset consisting of twenty different substitution-box structures have been publicly presented to the researchers. The fact that the proposed dataset has high nonlinearity values will allow it to be used in many practical applications in the future studies. The proposed dataset provides a contribution to the literature as it can be used both as an input dataset for the new post-processing algorithm and as a countermeasure to prevent the success of side-channel analyzes.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"24 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131187133","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535605
S. Yelmanov, Y. Romanyshyn
This study is devoted to the problem of improving digital image and video in real-time applications. This paper looks at the task of enhancing images in automatic mode without distortions and loss of information. This work addresses the challenge of improving the effectiveness of image enhancement based on the use of the technique of clipped histogram equalization. To that end, we offer a new technique to image enhancement by gain-limited histogram equalization (GLHE). The proposed GLHE technique is based on a new approach to normalizing the result of clipped histogram equalization. This approach improves the efficiency of improving complex images without the appearance of undesirable distortions and artifacts. The proposed GLHE technique is intended to be used in real-time applications to normalize and improve video content.
{"title":"Image Enhancement by Gain-Limited Histogram Equalization","authors":"S. Yelmanov, Y. Romanyshyn","doi":"10.1109/EUROCON52738.2021.9535605","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535605","url":null,"abstract":"This study is devoted to the problem of improving digital image and video in real-time applications. This paper looks at the task of enhancing images in automatic mode without distortions and loss of information. This work addresses the challenge of improving the effectiveness of image enhancement based on the use of the technique of clipped histogram equalization. To that end, we offer a new technique to image enhancement by gain-limited histogram equalization (GLHE). The proposed GLHE technique is based on a new approach to normalizing the result of clipped histogram equalization. This approach improves the efficiency of improving complex images without the appearance of undesirable distortions and artifacts. The proposed GLHE technique is intended to be used in real-time applications to normalize and improve video content.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132432549","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535539
Mickael Cormier, Dmitrii Seletkov, J. Beyerer
Automatic pedestrian detection in real-world un-cooperative scenarios is a well-known problem in computer vision, which has again gained in visibility last year due to distancing requirements. This remains a very challenging task, especially in crowded areas. Due to diverse technical and privacy issues, embedded systems such as smart cameras and smaller drones are becoming ubiquitous. Those complex detection models are not designed for on-edge processing in resource-constrained environments. Therefore, quantization techniques are required, in order to reduce the weights of a model to low-precision and not only effectively compress the model, but also allow to use low bitwidth arithmetic, which in term can be accelerated from specialized hardware. However, using an effective quantization scheme while maintaining accuracy is challenging. In this work we first establish a Quantization-aware training (QAT) and Post-training Quantization (PTQ) baseline for 8-bit uniform quantization to RetinaNet for person detection on the extremely challenging PANDA dataset. Those achieve near lossless performance in terms of accuracy by about 5× speed-up of the CPU inference and 4× model size reduction for 8-bit PTQ quantized model. Further experiments with aggressive quantization scheme in 4- and 2-bit show diverse challenges resulting in severe instabilities. We apply both uniform and non-uniform quantization to overcome those and provide insights and strategies to fully quantize in 4- and 2-bit. Through this process we systematically evaluate the sensibility of individual parts of RetinaNet for quantization in very low precision. Finally, we show the resistance of quantization for limited amount of data.
{"title":"Towards Lower Precision Quantization for Pedestrian Detection in Crowded Scenario","authors":"Mickael Cormier, Dmitrii Seletkov, J. Beyerer","doi":"10.1109/EUROCON52738.2021.9535539","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535539","url":null,"abstract":"Automatic pedestrian detection in real-world un-cooperative scenarios is a well-known problem in computer vision, which has again gained in visibility last year due to distancing requirements. This remains a very challenging task, especially in crowded areas. Due to diverse technical and privacy issues, embedded systems such as smart cameras and smaller drones are becoming ubiquitous. Those complex detection models are not designed for on-edge processing in resource-constrained environments. Therefore, quantization techniques are required, in order to reduce the weights of a model to low-precision and not only effectively compress the model, but also allow to use low bitwidth arithmetic, which in term can be accelerated from specialized hardware. However, using an effective quantization scheme while maintaining accuracy is challenging. In this work we first establish a Quantization-aware training (QAT) and Post-training Quantization (PTQ) baseline for 8-bit uniform quantization to RetinaNet for person detection on the extremely challenging PANDA dataset. Those achieve near lossless performance in terms of accuracy by about 5× speed-up of the CPU inference and 4× model size reduction for 8-bit PTQ quantized model. Further experiments with aggressive quantization scheme in 4- and 2-bit show diverse challenges resulting in severe instabilities. We apply both uniform and non-uniform quantization to overcome those and provide insights and strategies to fully quantize in 4- and 2-bit. Through this process we systematically evaluate the sensibility of individual parts of RetinaNet for quantization in very low precision. Finally, we show the resistance of quantization for limited amount of data.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131627729","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}
Pub Date : 2021-07-06DOI: 10.1109/EUROCON52738.2021.9535536
Burhan Hükümen, E. Şehirli
In this paper, a LCL filtered power factor corrected (PFC) converter to feed permanent magnet synchronous machines (PMSM) having field-oriented control (FOC) method has been proposed. In order to compensate the total harmonic distortion (THD) and poor power factor (PF) problem while achieving the high efficiency and reducing the switching losses of the converter and the voltage source inverter (VSI), the proposed system has been designed as LCL filtered bridgeless single-stage PFC isolated cuk converter for low power applications. Value of the output inductor provides discontinuous conduction mode (DCM) operation for reducing the conduction losses on switches of the converter. On the other hand, source filter was designed as LCL type to ensure power quality improvement. Results of this paper through the simulation have demonstrated that the proposed system has a capability to drive low power applications within the boundaries of international power quality standards and speed of the PMSM was controlled as desired.
{"title":"Speed Control of PMSM Fed By Bridgeless PFC Isolated Cuk Converter Using LCL filter","authors":"Burhan Hükümen, E. Şehirli","doi":"10.1109/EUROCON52738.2021.9535536","DOIUrl":"https://doi.org/10.1109/EUROCON52738.2021.9535536","url":null,"abstract":"In this paper, a LCL filtered power factor corrected (PFC) converter to feed permanent magnet synchronous machines (PMSM) having field-oriented control (FOC) method has been proposed. In order to compensate the total harmonic distortion (THD) and poor power factor (PF) problem while achieving the high efficiency and reducing the switching losses of the converter and the voltage source inverter (VSI), the proposed system has been designed as LCL filtered bridgeless single-stage PFC isolated cuk converter for low power applications. Value of the output inductor provides discontinuous conduction mode (DCM) operation for reducing the conduction losses on switches of the converter. On the other hand, source filter was designed as LCL type to ensure power quality improvement. Results of this paper through the simulation have demonstrated that the proposed system has a capability to drive low power applications within the boundaries of international power quality standards and speed of the PMSM was controlled as desired.","PeriodicalId":328338,"journal":{"name":"IEEE EUROCON 2021 - 19th International Conference on Smart Technologies","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134252610","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}
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