Pub Date : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566042
J. Healy, M. Wan, J. Sheridan
Estimation of the delay between two signals has physical significance in synchronisation problems in, e.g. telecommunications, measurement of motion and vibration, and image registration. Low complexity algorithms can be performed extremely quickly even on limited hardware, and have improved energy consumption over more complex algorithms. We present a partial Fourier analysis of a previously reported algorithm to estimate the magnitude of the delay; the algorithm is the sum of absolute differences. The analysis offers insight into why the algorithm requires the absolute value operation. The algorithm is insensitive to direction of the delay, but the same analysis demonstrates that new approaches are possible to find the signed magnitude of the delay. Arising from that analysis, we propose one such algorithm, and demonstrate its efficacy in simulation, along with its robustness to additive and quantization noise. Our algorithm could be useful in a very wide range of applications, including image stitching, measurement of vibrations in buildings, and synchronisation problems in telecommunications.
{"title":"Direction-Sensitive Fast Measurement of Sub-Sampling-Period Delays","authors":"J. Healy, M. Wan, J. Sheridan","doi":"10.1109/SPIN52536.2021.9566042","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566042","url":null,"abstract":"Estimation of the delay between two signals has physical significance in synchronisation problems in, e.g. telecommunications, measurement of motion and vibration, and image registration. Low complexity algorithms can be performed extremely quickly even on limited hardware, and have improved energy consumption over more complex algorithms. We present a partial Fourier analysis of a previously reported algorithm to estimate the magnitude of the delay; the algorithm is the sum of absolute differences. The analysis offers insight into why the algorithm requires the absolute value operation. The algorithm is insensitive to direction of the delay, but the same analysis demonstrates that new approaches are possible to find the signed magnitude of the delay. Arising from that analysis, we propose one such algorithm, and demonstrate its efficacy in simulation, along with its robustness to additive and quantization noise. Our algorithm could be useful in a very wide range of applications, including image stitching, measurement of vibrations in buildings, and synchronisation problems in telecommunications.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133125498","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565994
J. Roy, N. Pandey
This paper proposes a Threshold Type Binary Memristor Emulator based on Differential Voltage Current Conveyor (DVCC). Additionally, it uses an analog multiplier, two diodes, nine grounded resistors and one grounded capacitor. This threshold sensitive behavior is embedded through anti parallel configuration of diode. Further, threshold voltage is adjusted by resistor ratio. The emulator uses an integrator which ensures the dependence of memductance on history state. The non-volatility and bistability characteristics of the memristor emulator are provided by the bistable circuit. The workability of the proposed emulator circuit is verified through PSPICE simulations.
{"title":"Threshold Type Binary Memristor Emulator based on DVCC","authors":"J. Roy, N. Pandey","doi":"10.1109/SPIN52536.2021.9565994","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565994","url":null,"abstract":"This paper proposes a Threshold Type Binary Memristor Emulator based on Differential Voltage Current Conveyor (DVCC). Additionally, it uses an analog multiplier, two diodes, nine grounded resistors and one grounded capacitor. This threshold sensitive behavior is embedded through anti parallel configuration of diode. Further, threshold voltage is adjusted by resistor ratio. The emulator uses an integrator which ensures the dependence of memductance on history state. The non-volatility and bistability characteristics of the memristor emulator are provided by the bistable circuit. The workability of the proposed emulator circuit is verified through PSPICE simulations.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125776945","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566065
Vipan Verma, Rajneesh Rani
Facial expression recognition technology has boomed over the past few years because of human-computer engagement. Computer vision advancements have made it possible that machines can now understand the human’s actions., expressions, etc. Research in this area is also a hot topic because it offers a wide range of applications and shows that CNN provides impressive results compared to traditional methods. So keeping it as a motivation, in our work, we aimed for such Deep CNN architecture, which can work on real-world images like images having various resolution, angles, poses, illumination, and brightness, etc. So for this, we have implemented our CNN architecture with the Kaggle challenge presented dataset FER-2013 and trained the model to recognize the basic seven expressions. The proposed approach seems to be effective since we were able to achieve a validation accuracy of 70.15%. This approach not only can be applied to other datasets but also in real-world applications.
{"title":"Recognition Of Facial Expressions Using A Deep Neural Network","authors":"Vipan Verma, Rajneesh Rani","doi":"10.1109/SPIN52536.2021.9566065","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566065","url":null,"abstract":"Facial expression recognition technology has boomed over the past few years because of human-computer engagement. Computer vision advancements have made it possible that machines can now understand the human’s actions., expressions, etc. Research in this area is also a hot topic because it offers a wide range of applications and shows that CNN provides impressive results compared to traditional methods. So keeping it as a motivation, in our work, we aimed for such Deep CNN architecture, which can work on real-world images like images having various resolution, angles, poses, illumination, and brightness, etc. So for this, we have implemented our CNN architecture with the Kaggle challenge presented dataset FER-2013 and trained the model to recognize the basic seven expressions. The proposed approach seems to be effective since we were able to achieve a validation accuracy of 70.15%. This approach not only can be applied to other datasets but also in real-world applications.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122251244","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565975
Parveen Rani, R. Pandey
In this paper, a voltage differencing transconductance amplifier (VDTA) based voltage-mode (VM) single-input single-output (SISO) fractional order high-pass filter (FHPF) response, is proposed. The proposed filter employs single VDTA and makes use of two fractional order capacitors (FC). Functionality of the filter is verified through Cadence using 180 nm CMOS technology parameters; for fractional orders (FO) ranging from 0.5 to 0.9 in steps of 0.1. Sensitivity analysis has also been carried out to evaluate the performance of ${color{green}{text{the}}}$ proposed filter.
{"title":"Electronically Tunable Fractional Order Filter based on Single VDTA","authors":"Parveen Rani, R. Pandey","doi":"10.1109/SPIN52536.2021.9565975","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565975","url":null,"abstract":"In this paper, a voltage differencing transconductance amplifier (VDTA) based voltage-mode (VM) single-input single-output (SISO) fractional order high-pass filter (FHPF) response, is proposed. The proposed filter employs single VDTA and makes use of two fractional order capacitors (FC). Functionality of the filter is verified through Cadence using 180 nm CMOS technology parameters; for fractional orders (FO) ranging from 0.5 to 0.9 in steps of 0.1. Sensitivity analysis has also been carried out to evaluate the performance of ${color{green}{text{the}}}$ proposed filter.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124896104","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566028
Nitin Sharma, Gaurav G, R. S. Anand
Epilepsy is a neurological condition of intermittent brain dysfunction arising from irregular neuronal discharge through the brain. The electroencephalogram (EEG) offers valuable information about the brain’s physiological states and is also an effective method for detecting epilepsy. This study aims to develop a computer-aided automation system to identify epileptic seizures through EEG data from epileptic and healthy subjects. We employed discrete Short-time Fourier transform (STFT) to decompose EEG data into sub-bands, and sample entropy, mean, and peak mean features were extracted from each sub-band. Feature ’mean’ accounts for baseline differences, ’sample entropy’ for the chaotic nature of EEG data, and ’peak mean’ for the amplitude differences between healthy and epileptic EEG data. We achieved the highest classification accuracy of 100% in distinguishing epileptic ictal EEG signals and EEG signals from healthy subjects through 10-fold cross-validation using the Support vector machine with radial basis function (SVM-RBF) classifier. We also presented the comparison of peak mean feature with other well-known features in epilepsy detection using EEG. The high accuracy results obtained by the peak mean feature show its potential in seizure detection using EEG.
{"title":"Epileptic seizure detection using STFT based peak mean feature and support vector machine","authors":"Nitin Sharma, Gaurav G, R. S. Anand","doi":"10.1109/SPIN52536.2021.9566028","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566028","url":null,"abstract":"Epilepsy is a neurological condition of intermittent brain dysfunction arising from irregular neuronal discharge through the brain. The electroencephalogram (EEG) offers valuable information about the brain’s physiological states and is also an effective method for detecting epilepsy. This study aims to develop a computer-aided automation system to identify epileptic seizures through EEG data from epileptic and healthy subjects. We employed discrete Short-time Fourier transform (STFT) to decompose EEG data into sub-bands, and sample entropy, mean, and peak mean features were extracted from each sub-band. Feature ’mean’ accounts for baseline differences, ’sample entropy’ for the chaotic nature of EEG data, and ’peak mean’ for the amplitude differences between healthy and epileptic EEG data. We achieved the highest classification accuracy of 100% in distinguishing epileptic ictal EEG signals and EEG signals from healthy subjects through 10-fold cross-validation using the Support vector machine with radial basis function (SVM-RBF) classifier. We also presented the comparison of peak mean feature with other well-known features in epilepsy detection using EEG. The high accuracy results obtained by the peak mean feature show its potential in seizure detection using EEG.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285858","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566120
Alok Rajpurohit, Aniket Raman, Hiral Modi
For some pupils, learning some subjects can be extremely challenging. This could be owing to their disengaging nature or the students’ general lack of interest in them. Hence, game-based learning has been established to address this issue, and the games used for this purpose are known as serious games. In this paper, one such game has been developed and implemented. The new game system is a quiz game that acts as a solution to the shortfalls of the systems and solutions presented in this domain’s literature. It has been created in such a way that many of the voids and research gaps have been filled. One of them is the ability to learn multiple subjects with the same game rather than just one subject. It has a graphical user interface that allows users to interact and engage with it for long periods of time. It’s also based on a popular television reality show, which should be able to pique the curiosity of the younger generation.
{"title":"Development of a Serious Game for the Purpose of Education and Learning","authors":"Alok Rajpurohit, Aniket Raman, Hiral Modi","doi":"10.1109/SPIN52536.2021.9566120","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566120","url":null,"abstract":"For some pupils, learning some subjects can be extremely challenging. This could be owing to their disengaging nature or the students’ general lack of interest in them. Hence, game-based learning has been established to address this issue, and the games used for this purpose are known as serious games. In this paper, one such game has been developed and implemented. The new game system is a quiz game that acts as a solution to the shortfalls of the systems and solutions presented in this domain’s literature. It has been created in such a way that many of the voids and research gaps have been filled. One of them is the ability to learn multiple subjects with the same game rather than just one subject. It has a graphical user interface that allows users to interact and engage with it for long periods of time. It’s also based on a popular television reality show, which should be able to pique the curiosity of the younger generation.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127814946","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566096
Shivani Sharma, M. Tripathy, A. Sharma
In the proposed work, a compact wearable antenna on a polymer-based flexible substrate has been designed and analyzed for Wireless Body Area Network (WBAN). The proposed antenna operates in 2GHz to 6GHz band at the resonant frequency of 5.4 GHz for WLAN applications in on-body communication. The antenna structure has been miniaturized using slotting of the radiating patch to make the antenna light enough, perfectly suiting wearable wireless applications. A larger conductive ground plane between the body and the patch reduces RF coupling and lowers the Specific Absorption Rate (SAR) value. In the simulation, the wearable antenna offers an increased gain of 10 dB with an average SAR value of 1.5 watts/gm, which is within the specified safety limit. The antenna has been designed to provide better isolation against on-body losses and reduced SAR value with improved radiation efficiency.
本文设计并分析了一种基于聚合物柔性基板的小型可穿戴天线，用于无线体域网络(WBAN)。该天线工作在2GHz ~ 6GHz频段，谐振频率为5.4 GHz，适用于无线局域网身体通信。天线结构已经小型化，使用了辐射贴片的开槽，使天线足够轻，完全适合可穿戴无线应用。人体与贴片之间较大的导电接地面可以减少射频耦合，降低比吸收率(SAR)值。在仿真中，可穿戴天线的增益增加了10 dB，平均SAR值为1.5 w /gm，在规定的安全限值内。该天线的设计可以更好地隔离机身损耗，降低SAR值，提高辐射效率。
{"title":"Low profile and low SAR flexible wearable patch antenna for WBAN","authors":"Shivani Sharma, M. Tripathy, A. Sharma","doi":"10.1109/SPIN52536.2021.9566096","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566096","url":null,"abstract":"In the proposed work, a compact wearable antenna on a polymer-based flexible substrate has been designed and analyzed for Wireless Body Area Network (WBAN). The proposed antenna operates in 2GHz to 6GHz band at the resonant frequency of 5.4 GHz for WLAN applications in on-body communication. The antenna structure has been miniaturized using slotting of the radiating patch to make the antenna light enough, perfectly suiting wearable wireless applications. A larger conductive ground plane between the body and the patch reduces RF coupling and lowers the Specific Absorption Rate (SAR) value. In the simulation, the wearable antenna offers an increased gain of 10 dB with an average SAR value of 1.5 watts/gm, which is within the specified safety limit. The antenna has been designed to provide better isolation against on-body losses and reduced SAR value with improved radiation efficiency.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129218193","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566129
Shruti Awasthi, P. Jain
Cancer describes the cellular changes which lead to an uncontrolled division or growth of cells. Some types of cancer show visible growth of cells referred to as tumors. Every year hundreds of people are diagnosed with one or the other form of cancer with breast cancer as the most common type in females. This demands early detection, for which microwave imaging is considered to be the most promising method. A lot of contribution has been made in this field with materials having different permittivity and conductivity. In this paper, a 3-D structure of breast and microstrip patch antenna of hexagonal shape, operated at 2.45 GHz is designed using finite element method (FEM) in HFSS 15.0 with FR4 epoxy as a substrate to measure electromagnetic field patterns. The tumor present in breast is detected by observing Electric field patterns and specific absorption rate (SAR).
{"title":"Studying Electromagnetic field pattern for Breast Cancer Detection by Hexagonal Patch Antenna","authors":"Shruti Awasthi, P. Jain","doi":"10.1109/SPIN52536.2021.9566129","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566129","url":null,"abstract":"Cancer describes the cellular changes which lead to an uncontrolled division or growth of cells. Some types of cancer show visible growth of cells referred to as tumors. Every year hundreds of people are diagnosed with one or the other form of cancer with breast cancer as the most common type in females. This demands early detection, for which microwave imaging is considered to be the most promising method. A lot of contribution has been made in this field with materials having different permittivity and conductivity. In this paper, a 3-D structure of breast and microstrip patch antenna of hexagonal shape, operated at 2.45 GHz is designed using finite element method (FEM) in HFSS 15.0 with FR4 epoxy as a substrate to measure electromagnetic field patterns. The tumor present in breast is detected by observing Electric field patterns and specific absorption rate (SAR).","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"727 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120971928","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566031
A. Shal, Richa Gupta
Estimating the value of a property in terms of money can be a very difficult challenge. A good estimation can help both buyer and seller and not also there is a huge demand for the models that can estimate the value of the property more precisely as it can be hugely helpful to avoid possible loss while trading in the property which is beneficial for both buyer and seller. Accordingly to solve this issue a lot of researchers have proposed a lot of Machine Learning and Deep Learning regression algorithms and models like Back Propagation Neural Network, Fuzzy Logic, Arima model, Multilevel Modelling, etc. Some of these models include some optimization or boosting techniques like Swarm optimization and Adaboost which help the model to give more precise results. Some of these previous models will be discussed further in this paper. To predict the property value with maximum effectiveness, we have conducted a comparative study of different Machine Learning Algorithms along with some attribute selection technique Partial Least Square Regression (PLSR), k-folds cross-validation, and pre-processing techniques to boost the accuracy of mentioned models. Hereby the performance will be evaluated on four parameters using the same dataset which will help us to compare the performance of each algorithm. These Four parameters are Average Profit or Loss, Adjusted R-Squared, Mean Absolute Error, and Mean Squared Error. Also, we have introduced a hybrid model to overcome the mentioned problem and this will be discussed further in this paper. Finally looking at the results obtained we can use the best algorithm to solve this problem. The algorithms used in this paper are Kernel Support Vector, XGBoost, and Decision Tree, ElasticNet, and a Hybrid regression model. According to the results obtained the Hybrid Regression model proposed by us is best for the estimation of property value.
{"title":"A comparative Study to Predict the Property value using Machine Learning","authors":"A. Shal, Richa Gupta","doi":"10.1109/SPIN52536.2021.9566031","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566031","url":null,"abstract":"Estimating the value of a property in terms of money can be a very difficult challenge. A good estimation can help both buyer and seller and not also there is a huge demand for the models that can estimate the value of the property more precisely as it can be hugely helpful to avoid possible loss while trading in the property which is beneficial for both buyer and seller. Accordingly to solve this issue a lot of researchers have proposed a lot of Machine Learning and Deep Learning regression algorithms and models like Back Propagation Neural Network, Fuzzy Logic, Arima model, Multilevel Modelling, etc. Some of these models include some optimization or boosting techniques like Swarm optimization and Adaboost which help the model to give more precise results. Some of these previous models will be discussed further in this paper. To predict the property value with maximum effectiveness, we have conducted a comparative study of different Machine Learning Algorithms along with some attribute selection technique Partial Least Square Regression (PLSR), k-folds cross-validation, and pre-processing techniques to boost the accuracy of mentioned models. Hereby the performance will be evaluated on four parameters using the same dataset which will help us to compare the performance of each algorithm. These Four parameters are Average Profit or Loss, Adjusted R-Squared, Mean Absolute Error, and Mean Squared Error. Also, we have introduced a hybrid model to overcome the mentioned problem and this will be discussed further in this paper. Finally looking at the results obtained we can use the best algorithm to solve this problem. The algorithms used in this paper are Kernel Support Vector, XGBoost, and Decision Tree, ElasticNet, and a Hybrid regression model. According to the results obtained the Hybrid Regression model proposed by us is best for the estimation of property value.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121429459","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566059
C. Chaudhary, Saurabh Mishra, U. Nangia
This paper presents onboard battery charging with a modified Zeta converter. Charging system is incorporated with two clamping diodes and two extra switches at Zeta converter input resulting in low THD input current and better charging efficiency by mitigating the problems of conventional Zeta converter. An AC-DC conversion is employed by diode bridge rectifier (DBR) followed by modified Zeta converter as power factor correction (PFC) unit, and the flyback converter is used to synchronize the current of battery with the implementation of closed loop cascaded PI control during constant voltage (CV) mode and constant current (CC) mode. Zeta converter is operated in Discontinuous conduction mode (DCM) mode such that Zeta converter can work with better dynamic response, and low ripple at the output voltage. Linear PI control topology is employed here, which has cascaded control for the better working efficiency of the charger. Proposed converter operation is to achieve low total harmonic distortion (THD) within IEC 61000-3-2 standards. Due to inbuilt isolation, components are less and hence proving the system to be more reliable. Proposed system’s efficacy is validated in MATLAB SIMULINK.
{"title":"A Modified-Zeta Converter based Onboard Battery Charging with Improved THD","authors":"C. Chaudhary, Saurabh Mishra, U. Nangia","doi":"10.1109/SPIN52536.2021.9566059","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566059","url":null,"abstract":"This paper presents onboard battery charging with a modified Zeta converter. Charging system is incorporated with two clamping diodes and two extra switches at Zeta converter input resulting in low THD input current and better charging efficiency by mitigating the problems of conventional Zeta converter. An AC-DC conversion is employed by diode bridge rectifier (DBR) followed by modified Zeta converter as power factor correction (PFC) unit, and the flyback converter is used to synchronize the current of battery with the implementation of closed loop cascaded PI control during constant voltage (CV) mode and constant current (CC) mode. Zeta converter is operated in Discontinuous conduction mode (DCM) mode such that Zeta converter can work with better dynamic response, and low ripple at the output voltage. Linear PI control topology is employed here, which has cascaded control for the better working efficiency of the charger. Proposed converter operation is to achieve low total harmonic distortion (THD) within IEC 61000-3-2 standards. Due to inbuilt isolation, components are less and hence proving the system to be more reliable. Proposed system’s efficacy is validated in MATLAB SIMULINK.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124342964","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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