Pub Date : 2023-10-09DOI: 10.2174/0123520965272311231004051135
Jun Zhang, Feng Pan, Yilin Ji, Jinli Li, Jicheng Yu
Background:: How to solve the inconsistency of battery pack is a key point to ensure reliable operation of electric vehicles. Battery equalization is an effective measure to address the inconsistency. Passive equalization method has poor efficiency and thermal management problems. Average voltage equalization method is only suitable for situations where there is a significant voltage difference between batteries. The SOC-based equalization method is relatively difficult and may inevitably lead to the accumulation of errors during the process. background: Battery pack active equilibrium is an effective measure to alleviate the inconsistency between cells. Traditional control methods have some disadvantages. Objective:: In order to avoid the disadvantages of traditional control methods, a new control method is proposed to improve the accuracy and self-adaptation of active equalization, which is easy to be realized without online calculation. Methods:: Cascaded bidirectional Buck-Boost circuit is adopted as the novel equalization topology. Based on fuzzy PID theory, an adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed in this paper. Parameter design of the fuzzy PID controller is carried out. A battery equalization system based on cascaded bidirectional Buck-Boost circuit is designed and developed. Experimental verification is conducted on relevant hardware platforms. method: Based on fuzzy PID theory, this paper designs a battery equilibrium system based on fuzzy PID adaptive hybrid control. Simulation analysis was conducted in MATLAB/Simulink environment, and parameter design of the fuzzy PID controller was carried out, and experimental verification was conducted on relevant hardware platforms. Results:: An adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed. Compared to passive equalization, this proposed method provides high efficiency. Regarding traditional voltage control, the method improves control reliability and flexibility. Compared to the average voltage equalization method, the approach needs less convergence time. Moreover, the control method is much easier to realize than the SOC-based equalization method. result: The results show that compared with the traditional equilibrium control method, the equilibrium precision is improved and the degree of self-adaptation of the equilibrium process is better, which fully guarantees the reliability of the equilibrium system. Conclusion:: By using the presented adaptive control based on DC energy conversion circuit, the degree of self-adaptation of the equalization process has been obtained as higher and the inconsistency as smaller. other: none
{"title":"Active Equalization of Lithium Battery Pack with Adaptive Control Based on DC Energy Conversion Circuit","authors":"Jun Zhang, Feng Pan, Yilin Ji, Jinli Li, Jicheng Yu","doi":"10.2174/0123520965272311231004051135","DOIUrl":"https://doi.org/10.2174/0123520965272311231004051135","url":null,"abstract":"Background:: How to solve the inconsistency of battery pack is a key point to ensure reliable operation of electric vehicles. Battery equalization is an effective measure to address the inconsistency. Passive equalization method has poor efficiency and thermal management problems. Average voltage equalization method is only suitable for situations where there is a significant voltage difference between batteries. The SOC-based equalization method is relatively difficult and may inevitably lead to the accumulation of errors during the process. background: Battery pack active equilibrium is an effective measure to alleviate the inconsistency between cells. Traditional control methods have some disadvantages. Objective:: In order to avoid the disadvantages of traditional control methods, a new control method is proposed to improve the accuracy and self-adaptation of active equalization, which is easy to be realized without online calculation. Methods:: Cascaded bidirectional Buck-Boost circuit is adopted as the novel equalization topology. Based on fuzzy PID theory, an adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed in this paper. Parameter design of the fuzzy PID controller is carried out. A battery equalization system based on cascaded bidirectional Buck-Boost circuit is designed and developed. Experimental verification is conducted on relevant hardware platforms. method: Based on fuzzy PID theory, this paper designs a battery equilibrium system based on fuzzy PID adaptive hybrid control. Simulation analysis was conducted in MATLAB/Simulink environment, and parameter design of the fuzzy PID controller was carried out, and experimental verification was conducted on relevant hardware platforms. Results:: An adaptive digital-analog hybrid control strategy based on fuzzy PID is proposed. Compared to passive equalization, this proposed method provides high efficiency. Regarding traditional voltage control, the method improves control reliability and flexibility. Compared to the average voltage equalization method, the approach needs less convergence time. Moreover, the control method is much easier to realize than the SOC-based equalization method. result: The results show that compared with the traditional equilibrium control method, the equilibrium precision is improved and the degree of self-adaptation of the equilibrium process is better, which fully guarantees the reliability of the equilibrium system. Conclusion:: By using the presented adaptive control based on DC energy conversion circuit, the degree of self-adaptation of the equalization process has been obtained as higher and the inconsistency as smaller. other: none","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135149352","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 : 2023-10-09DOI: 10.2174/0123520965272293231005042405
Jun Zhang, Feng Pan, Yilin Ji, Jinli Li, Jicheng Yu
Background:: The test power supply is one of the key devices in the DC distribution network, which is necessary to supply power with high quality for testing other devices' performance. The double active bridge (DAB) converter is a common circuit topology for test power supply, which has the advantages of high-frequency electrical isolation, bi-directional power flow, and high power density. For the converter, control methods, such as single-phase-shift (SPS) control, and single-current stress or single-return power optimization under extended-phase-shift (EPS) control, have their limitations, which influences efficiency. Objective:: This paper aims to propose a dual-objective optimal control method, which can effectively improve efficiency of the test power supply. Methods:: This paper addresses the limitations of SPS control, and single-current stress or singlereturn power optimization under EPS control of the DAB converter, and proposes a dual-objective optimal control method based on the idea of using objective planning in the full power range under the condition of satisfying soft switching, which effectively improves efficiency of the test power supply. Results:: With the proposed dual-objective optimal control method, the converter achieves a smaller current stress similar to that with the single-current stress optimal control, and the return power is also reduced by 29.51%. Efficiency of the test power supply reaches 86.9%, which is better than 82.5% with SPS control and 85.3% with single-current stress optimization under EPS control. The experimental results fully verify the effectiveness of the proposed control method. Conclusion:: A dual-objective optimal control method is proposed. By using the presented method, current stress and return power are both optimally designed, so the efficiency of the test power supply can be effectively improved. conclusion: A dual-objective optimal control method is proposed. By using the presented method, the efficiency of the test power supply can be effectively improved. other: none
{"title":"The Optimal Control Method of Test Power Supply for DC Distribution Network","authors":"Jun Zhang, Feng Pan, Yilin Ji, Jinli Li, Jicheng Yu","doi":"10.2174/0123520965272293231005042405","DOIUrl":"https://doi.org/10.2174/0123520965272293231005042405","url":null,"abstract":"Background:: The test power supply is one of the key devices in the DC distribution network, which is necessary to supply power with high quality for testing other devices' performance. The double active bridge (DAB) converter is a common circuit topology for test power supply, which has the advantages of high-frequency electrical isolation, bi-directional power flow, and high power density. For the converter, control methods, such as single-phase-shift (SPS) control, and single-current stress or single-return power optimization under extended-phase-shift (EPS) control, have their limitations, which influences efficiency. Objective:: This paper aims to propose a dual-objective optimal control method, which can effectively improve efficiency of the test power supply. Methods:: This paper addresses the limitations of SPS control, and single-current stress or singlereturn power optimization under EPS control of the DAB converter, and proposes a dual-objective optimal control method based on the idea of using objective planning in the full power range under the condition of satisfying soft switching, which effectively improves efficiency of the test power supply. Results:: With the proposed dual-objective optimal control method, the converter achieves a smaller current stress similar to that with the single-current stress optimal control, and the return power is also reduced by 29.51%. Efficiency of the test power supply reaches 86.9%, which is better than 82.5% with SPS control and 85.3% with single-current stress optimization under EPS control. The experimental results fully verify the effectiveness of the proposed control method. Conclusion:: A dual-objective optimal control method is proposed. By using the presented method, current stress and return power are both optimally designed, so the efficiency of the test power supply can be effectively improved. conclusion: A dual-objective optimal control method is proposed. By using the presented method, the efficiency of the test power supply can be effectively improved. other: none","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135149368","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 : 2023-10-06DOI: 10.2174/0123520965260939230928070008
Wenbao Hou, Gang Zhang, Wenjie Wang
Background:: The double-end H-bridge inverters can realize independent control of the stator voltage in each phase and have flexible advantages of modulation and fault tolerance; thus, they are more suitable for multi-phase fault-tolerant motor drives. However, due to the increase of voltage vectors and the coupling between the electromagnetic and non-electromagnetic quantities, the normal control strategies for traditional three-phase motor drives do not work anymore. Objective:: This paper aimed to propose a simplified model predictive current control strategy based on the vector space decomposition (VSD) and the vectors’ gradual simplification for the three-level six-phase H-bridge inverters. Methods:: Firstly, the 729 physical variables were decomposed and mapped onto the fundamental αβ subspace, harmonic xy subspace, and the zero-sequence o1o2 subspace based on the VSD. Then, to eliminate the influence of the harmonic and zero-sequence components on the control performance and make an easy digital implementation, vectors’ simplification has been proposed based on the in-depth analysis of the relationship between the voltage vectors mapped onto different subspaces and vectors’ stratification. With the simplification method, the number of voltage vectors was simplified from 729 to 12, and then the selected voltage vectors were used in the rolling optimization of the model predictive current control (MPCC) to choose the optimal one. Finally, sufficient experiments were carried out including static and dynamic conditions, different modulation index and power factor, etc., to verify the feasibility of the proposed strategy. Results:: The simulation and experimental results show that with the simplified MPCC strategy, both the static and dynamic performances are relatively good, and the THDs of the phase current under different modulations and power factors are relatively low. result: The simulation and experimental results show that with the simplified MPCC strategy, both the static and dynamic performances are relatively nice, the THDs of the phase current under different modulations and power factors are relatively low. Conclusion:: The proposed MPCC algorithm for the three-level six-phase H-bridge inverters has shown obvious improvement in solving the control problems of multi-vectors and complex redundancy issues. other: to eliminate the influence of the harmonic and zero-sequence components on the control performance and make an easy digital implementation, vectors simplification has been proposed based on the in-depth analysis of the relationship between the voltage vectors mapped onto different subplaces and vectors stratification.
{"title":"A Simplified Model Predictive Current Control Strategy for Six-phase Hbridge Inverters","authors":"Wenbao Hou, Gang Zhang, Wenjie Wang","doi":"10.2174/0123520965260939230928070008","DOIUrl":"https://doi.org/10.2174/0123520965260939230928070008","url":null,"abstract":"Background:: The double-end H-bridge inverters can realize independent control of the stator voltage in each phase and have flexible advantages of modulation and fault tolerance; thus, they are more suitable for multi-phase fault-tolerant motor drives. However, due to the increase of voltage vectors and the coupling between the electromagnetic and non-electromagnetic quantities, the normal control strategies for traditional three-phase motor drives do not work anymore. Objective:: This paper aimed to propose a simplified model predictive current control strategy based on the vector space decomposition (VSD) and the vectors’ gradual simplification for the three-level six-phase H-bridge inverters. Methods:: Firstly, the 729 physical variables were decomposed and mapped onto the fundamental αβ subspace, harmonic xy subspace, and the zero-sequence o1o2 subspace based on the VSD. Then, to eliminate the influence of the harmonic and zero-sequence components on the control performance and make an easy digital implementation, vectors’ simplification has been proposed based on the in-depth analysis of the relationship between the voltage vectors mapped onto different subspaces and vectors’ stratification. With the simplification method, the number of voltage vectors was simplified from 729 to 12, and then the selected voltage vectors were used in the rolling optimization of the model predictive current control (MPCC) to choose the optimal one. Finally, sufficient experiments were carried out including static and dynamic conditions, different modulation index and power factor, etc., to verify the feasibility of the proposed strategy. Results:: The simulation and experimental results show that with the simplified MPCC strategy, both the static and dynamic performances are relatively good, and the THDs of the phase current under different modulations and power factors are relatively low. result: The simulation and experimental results show that with the simplified MPCC strategy, both the static and dynamic performances are relatively nice, the THDs of the phase current under different modulations and power factors are relatively low. Conclusion:: The proposed MPCC algorithm for the three-level six-phase H-bridge inverters has shown obvious improvement in solving the control problems of multi-vectors and complex redundancy issues. other: to eliminate the influence of the harmonic and zero-sequence components on the control performance and make an easy digital implementation, vectors simplification has been proposed based on the in-depth analysis of the relationship between the voltage vectors mapped onto different subplaces and vectors stratification.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134944944","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 : 2023-10-03DOI: 10.2174/0123520965262291230927052452
Weifeng Song, Gang Ma, Yuxuan Zhao, Weikang Li, Yuxiang Meng
Background:: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation (RDG) access. background: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation access. Objective:: To address the problems caused by the connection of RDG, an RPO model and an improved quantum-behaved particle swarm optimization (IQPSO) algorithm are proposed. Method: In this study, a dynamic S-type function is proposed as the objective function of the minimum active power loss, whereas an exponential function is proposed as the objective function of the minimum voltage deviation to establish an RPO objective function. The operating cost of distribution is considered as the third objective function. To address the RPO problem, a QPSO algorithm based on the ε-greedy strategy is proposed in this paper. ModifiedIEEE33 bus and IEEE69 bus systems were used to evaluate the proposed RPO method in simulations Results:: The simulation results reveal that the IQPSO algorithm obtains a better solution, and the proposed RPO model can considerably reduce active power loss, node voltage deviation, and distribution network operating costs. Conclusion:: The RPO model and IQPSO algorithm proposed in this study provide a highperformance method to analyze and optimize reactive power management in distribution network. conclusion: The RPO model and IQPSO algorithm proposed in this paper provides a high-performance method to analyze and optimize reactive power management in distribution network.
{"title":"Multi-objective Reactive Power Optimization of a Distribution Network based on Improved Quantum-behaved Particle Swarm Optimization","authors":"Weifeng Song, Gang Ma, Yuxuan Zhao, Weikang Li, Yuxiang Meng","doi":"10.2174/0123520965262291230927052452","DOIUrl":"https://doi.org/10.2174/0123520965262291230927052452","url":null,"abstract":"Background:: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation (RDG) access. background: Reactive power optimization (RPO) is crucial for distribution networks in the context of large-scale renewable distributed generation access. Objective:: To address the problems caused by the connection of RDG, an RPO model and an improved quantum-behaved particle swarm optimization (IQPSO) algorithm are proposed. Method: In this study, a dynamic S-type function is proposed as the objective function of the minimum active power loss, whereas an exponential function is proposed as the objective function of the minimum voltage deviation to establish an RPO objective function. The operating cost of distribution is considered as the third objective function. To address the RPO problem, a QPSO algorithm based on the ε-greedy strategy is proposed in this paper. ModifiedIEEE33 bus and IEEE69 bus systems were used to evaluate the proposed RPO method in simulations Results:: The simulation results reveal that the IQPSO algorithm obtains a better solution, and the proposed RPO model can considerably reduce active power loss, node voltage deviation, and distribution network operating costs. Conclusion:: The RPO model and IQPSO algorithm proposed in this study provide a highperformance method to analyze and optimize reactive power management in distribution network. conclusion: The RPO model and IQPSO algorithm proposed in this paper provides a high-performance method to analyze and optimize reactive power management in distribution network.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135789232","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 : 2023-10-02DOI: 10.2174/0123520965251866230926050714
Jimeng Song, Ziqi Shen, Han Yu, Rongxin Lai, Yuancheng Li, Qingle Wang, Jianbin Li
Background:: Data regulation can effectively resist data privacy leakage and abuse in the process of external sharing of energy big data, but how to securely retrieve vast amounts of regulatory data is a challenge. Objective:: To securely retrieve vast amounts of regulatory data, a secure and efficient searchable encryption scheme that supports multi-keyword fuzzy retrieval on the alliance chain is proposed. Method:: This scheme encrypts and stores the regulatory data on the hyperledger fabric alliance chain. Energy big data files (EBDF) are encrypted and stored on a cloud server. Using the symmetric searchable encryption technology to achieve secure retrieval of regulatory data on the chain and secure access to EBDF. To improve search efficiency, we propose a SDPHashMap index structure and use the special manhatton distance matrix(SMDM) measurement to calculate the similarity of queried keywords and index keywords to locate the trapdoor retrieval hash address. Utilizing the cuckoo filter cluster to test the membership of queried keywords. Results:: This scheme stores EBDF off-chain, effectively relieving the storage and communication pressure of the blockchain, improving search speed, and providing more accurate retrieval services than single keyword fuzzy retrieval. By the simulation-based adversary- challenger game model, the security analysis demonstrates that the proposed scheme has adaptive selected keyword attack semantic security. Conclusion:: Experimental results show that the proposed scheme has high efficiency in trapdoor generation and multi-keyword search stages. other: no
{"title":"Secure And Efficient Multi-keyword Fuzzy Search Over Encrypted Data On Alliance Chain","authors":"Jimeng Song, Ziqi Shen, Han Yu, Rongxin Lai, Yuancheng Li, Qingle Wang, Jianbin Li","doi":"10.2174/0123520965251866230926050714","DOIUrl":"https://doi.org/10.2174/0123520965251866230926050714","url":null,"abstract":"Background:: Data regulation can effectively resist data privacy leakage and abuse in the process of external sharing of energy big data, but how to securely retrieve vast amounts of regulatory data is a challenge. Objective:: To securely retrieve vast amounts of regulatory data, a secure and efficient searchable encryption scheme that supports multi-keyword fuzzy retrieval on the alliance chain is proposed. Method:: This scheme encrypts and stores the regulatory data on the hyperledger fabric alliance chain. Energy big data files (EBDF) are encrypted and stored on a cloud server. Using the symmetric searchable encryption technology to achieve secure retrieval of regulatory data on the chain and secure access to EBDF. To improve search efficiency, we propose a SDPHashMap index structure and use the special manhatton distance matrix(SMDM) measurement to calculate the similarity of queried keywords and index keywords to locate the trapdoor retrieval hash address. Utilizing the cuckoo filter cluster to test the membership of queried keywords. Results:: This scheme stores EBDF off-chain, effectively relieving the storage and communication pressure of the blockchain, improving search speed, and providing more accurate retrieval services than single keyword fuzzy retrieval. By the simulation-based adversary- challenger game model, the security analysis demonstrates that the proposed scheme has adaptive selected keyword attack semantic security. Conclusion:: Experimental results show that the proposed scheme has high efficiency in trapdoor generation and multi-keyword search stages. other: no","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135902420","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}
Abstract: Digitalization has attracted the world to collect increasing data. Background: Proxy signature is a digital alternative for signing documents in the absence of the original signer. Methods: In this paper, we have used the mathematical methods and concepts of Chaotic maps (CMs) and elliptic curve cryptography. Results: We have proposed a new proxy signature scheme (PSS). Security of our PSS relies on "elliptic curve discrete logarithm (ECDL) and integer factorization (FAC) problems". It requires only low-complexity computation, which increases efficiency. Conclusion: It is the first PSS in such a security setting and can also be assumed to be secure in the post-quantum cryptographic world. It can be highly used digitally during thePandemic conditions like COVID-19.
{"title":"New Proxy Signature Scheme over Elliptic Curves using Chaotic Maps Applicable during Pandemic COVID-19","authors":"Namita Tiwari, Mayur Rahul, Ayushi Prakash, Sonu Kumar Jha, Vikash Yadav","doi":"10.2174/2352096516666230915113801","DOIUrl":"https://doi.org/10.2174/2352096516666230915113801","url":null,"abstract":"Abstract: Digitalization has attracted the world to collect increasing data. Background: Proxy signature is a digital alternative for signing documents in the absence of the original signer. Methods: In this paper, we have used the mathematical methods and concepts of Chaotic maps (CMs) and elliptic curve cryptography. Results: We have proposed a new proxy signature scheme (PSS). Security of our PSS relies on \"elliptic curve discrete logarithm (ECDL) and integer factorization (FAC) problems\". It requires only low-complexity computation, which increases efficiency. Conclusion: It is the first PSS in such a security setting and can also be assumed to be secure in the post-quantum cryptographic world. It can be highly used digitally during thePandemic conditions like COVID-19.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135437807","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 : 2023-09-14DOI: 10.2174/2352096516666230914103828
Geeta Pattnaik, Meryleen Mohapatra
Background: The upsurge in the field of radio frequency power electronics has led to the involvement of wide bandgap semiconductor materials because of their potential characteristics in achieving high breakdown voltage, output power density, and frequency. III-V group materials of the periodic table have proven to be the best candidates for achieving this goal. Among all the available combinations of group III-V semiconductor materials, gallium nitride (GaN), having a band gap of 3.4eV, has gradually started gaining the confidence to become the next-generation material to fulfill these requirements. Objective: Considering the various advantages provided by GaN, it is widely used in AlGaN/GaN HEMTs (High Electron Mobility Transistors) as their fundamental materials. This work aimed to review the structure, operation, and polarization mechanisms influencing the HEMT device, different types of GaN HEMT, and the various process technologies for developing the device. Methods: Various available methods to obtain an enhancement type GaN HEMT are discussed in the study. It also covers the recent developments and various techniques to improve the performance and device linearity of GaN HEMT. Conclusion: Despite the advantages and continuous improvement exhibited by the GaN HEMT technology, it faces several reliability issues, leading to degradation of device performance. In this study, we review various reliability issues and ways to mitigate them. Moreover, several application domains are also discussed, where GaN HEMTs have proven their capability. It also focuses on reviewing and compiling the various aspects related to the GaN HEMT, thus providing all necessary information.
{"title":"GaN HEMT for High-performance Applications: A Revolutionary Technology","authors":"Geeta Pattnaik, Meryleen Mohapatra","doi":"10.2174/2352096516666230914103828","DOIUrl":"https://doi.org/10.2174/2352096516666230914103828","url":null,"abstract":"Background: The upsurge in the field of radio frequency power electronics has led to the involvement of wide bandgap semiconductor materials because of their potential characteristics in achieving high breakdown voltage, output power density, and frequency. III-V group materials of the periodic table have proven to be the best candidates for achieving this goal. Among all the available combinations of group III-V semiconductor materials, gallium nitride (GaN), having a band gap of 3.4eV, has gradually started gaining the confidence to become the next-generation material to fulfill these requirements. Objective: Considering the various advantages provided by GaN, it is widely used in AlGaN/GaN HEMTs (High Electron Mobility Transistors) as their fundamental materials. This work aimed to review the structure, operation, and polarization mechanisms influencing the HEMT device, different types of GaN HEMT, and the various process technologies for developing the device. Methods: Various available methods to obtain an enhancement type GaN HEMT are discussed in the study. It also covers the recent developments and various techniques to improve the performance and device linearity of GaN HEMT. Conclusion: Despite the advantages and continuous improvement exhibited by the GaN HEMT technology, it faces several reliability issues, leading to degradation of device performance. In this study, we review various reliability issues and ways to mitigate them. Moreover, several application domains are also discussed, where GaN HEMTs have proven their capability. It also focuses on reviewing and compiling the various aspects related to the GaN HEMT, thus providing all necessary information.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134970661","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 : 2023-09-07DOI: 10.2174/2352096516666230907145027
Haibo Shen, Liyuan Deng, Lingzi Wang, Xianzhuo Liu
Background: With the gradual construction of new power systems, new energy sources, such as wind and photovoltaic power, will gradually dominate positions in the power supply structure, directly leading the new power system to rely heavily on accurate meteorological forecasts. High-precision and high-resolution meteorological forecasts are important technical methods to improve the safe, stable, and economic operation of the new power system. Objective: Since the analysis of meteorological elements is the basis of meteorological forecasting, in this paper, the effect of different meteorological elements including temperature, relative humidity, air pressure, wind speed, wind direction, and radiation on the performance of power forecasting, was analyzed by using 7 machine learning algorithms in 5 provinces in southern China. Method: About 5 provinces in southern China were selected as the research objects, and 7 typical machine learning algorithms were applied and compared, including support vector machine (SVM), decision tree (DT), random forest (RFR), K-nearest neighbor (KNN), Linear Regression (LR), Ridge Regression (RR), and Lasso Regression (Lasso R). At the same time, the influence of different meteorological elements, such as temperature, relative humidity, air pressure, wind speed, wind direction, and radiation amount, on the prediction performance of wind power and photovoltaic power was considered. Then, the performance of different regression models was further investigated and analyzed. Results: Based on the data of 10 new energy stations in 5 regions, the research on the prediction performance of 7 machine learning methods shows that the performance of models in different regions varies greatly. Among the 10 selected new energy stations, the RFR model and KNR model have superior overall performance. Conclusion: This study shows how variable importance and prediction accuracy depend on regression methods and climatic variables, providing effective methods to assess the interdependence of meteorological variables and the importance of meteorological variables in predicting output power.
{"title":"Analysis of the effect of meteorological elements on new energy power prediction based on machine learning","authors":"Haibo Shen, Liyuan Deng, Lingzi Wang, Xianzhuo Liu","doi":"10.2174/2352096516666230907145027","DOIUrl":"https://doi.org/10.2174/2352096516666230907145027","url":null,"abstract":"Background: With the gradual construction of new power systems, new energy sources, such as wind and photovoltaic power, will gradually dominate positions in the power supply structure, directly leading the new power system to rely heavily on accurate meteorological forecasts. High-precision and high-resolution meteorological forecasts are important technical methods to improve the safe, stable, and economic operation of the new power system. Objective: Since the analysis of meteorological elements is the basis of meteorological forecasting, in this paper, the effect of different meteorological elements including temperature, relative humidity, air pressure, wind speed, wind direction, and radiation on the performance of power forecasting, was analyzed by using 7 machine learning algorithms in 5 provinces in southern China. Method: About 5 provinces in southern China were selected as the research objects, and 7 typical machine learning algorithms were applied and compared, including support vector machine (SVM), decision tree (DT), random forest (RFR), K-nearest neighbor (KNN), Linear Regression (LR), Ridge Regression (RR), and Lasso Regression (Lasso R). At the same time, the influence of different meteorological elements, such as temperature, relative humidity, air pressure, wind speed, wind direction, and radiation amount, on the prediction performance of wind power and photovoltaic power was considered. Then, the performance of different regression models was further investigated and analyzed. Results: Based on the data of 10 new energy stations in 5 regions, the research on the prediction performance of 7 machine learning methods shows that the performance of models in different regions varies greatly. Among the 10 selected new energy stations, the RFR model and KNR model have superior overall performance. Conclusion: This study shows how variable importance and prediction accuracy depend on regression methods and climatic variables, providing effective methods to assess the interdependence of meteorological variables and the importance of meteorological variables in predicting output power.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135097825","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 : 2023-09-01DOI: 10.2174/2352096516666230901122406
Hardeep Kaur, S. Sengar, M. Ikbal
To improve the flexibility and efficiency of measurement of influenza virus prevention and control, and realize the combination of modern Internet technology and medical technology, in this article, the cases of influenza virus outbreaks in the past five years will be retrieved from various websites. A total of 5087 articles including clinical case analysis literature, individual infection case reports, review literature, Chinese and English literature, outbreak cases, and duplicate literature of non-human infection cases should be excluded Natural Development of Influenza Virus Infection in Individuals The results show that in the influenza virus epidemic database, the longest course of influenza virus infection is 10 days, the shortest is 2 days, the average course is 5.6 (5.6 ± 1.7) days, and the proportion of cases with the course of 5 days is the largest, and the proportion of cases with the course of 8 days is the smallest. In the international common mathematical modelling research, it is found that the latency of influenza viruses is 1-7 days, most of them are 2-4 days, the average latency is 1.9 days, and the course of the disease is 3-6 days. In this study, through the medical information sensor system based on cloud computing, the SEIAR model of the influenza virus outbreak database is built, and the average latency of all outbreaks is calculated. The average latency of the influenza virus is 2.0 days, which is very close to the international research data, and the difference between the two is only 0.1 days. Compared with non-interventional outbreaks, influenza virus control measures push the peak period from 145 days (no intervention) to 169 days (i.e. 24 days later). The infection rate of the influenza virus decreases from 74.75% untreated to 26.41%, that is to say, 48.34
{"title":"Cloud Computing based Influenza Virus Prevention and Control for \u0000Bio-Medical Applications","authors":"Hardeep Kaur, S. Sengar, M. Ikbal","doi":"10.2174/2352096516666230901122406","DOIUrl":"https://doi.org/10.2174/2352096516666230901122406","url":null,"abstract":"\u0000\u0000To improve the flexibility and efficiency of measurement of influenza virus prevention and control, and realize the combination of modern Internet technology and medical technology, in this article, the cases of influenza virus outbreaks in the past five years will be retrieved from various websites.\u0000\u0000\u0000\u0000A total of 5087 articles including clinical case analysis literature, individual infection case reports, review literature, Chinese and English literature, outbreak cases, and duplicate literature of non-human infection cases should be excluded\u0000\u0000\u0000\u0000Natural Development of Influenza Virus Infection in Individuals\u0000\u0000\u0000\u0000The results show that in the influenza virus epidemic database, the longest course of influenza virus infection is 10 days, the shortest is 2 days, the average course is 5.6 (5.6 ± 1.7) days, and the proportion of cases with the course of 5 days is the largest, and the proportion of cases with the course of 8 days is the smallest.\u0000\u0000\u0000\u0000In the international common mathematical modelling research, it is found that the latency of influenza viruses is 1-7 days, most of them are 2-4 days, the average latency is 1.9 days, and the course of the disease is 3-6 days. In this study, through the medical information sensor system based on cloud computing, the SEIAR model of the influenza virus outbreak database is built, and the average latency of all outbreaks is calculated. The average latency of the influenza virus is 2.0 days, which is very close to the international research data, and the difference between the two is only 0.1 days. Compared with non-interventional outbreaks, influenza virus control measures push the peak period from 145 days (no intervention) to 169 days (i.e. 24 days later). The infection rate of the influenza virus decreases from 74.75% untreated to 26.41%, that is to say, 48.34\u0000","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"28 1","pages":""},"PeriodicalIF":0.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72884359","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}