Zhihong Zhong, Xiaochun Fang, Fei Lin, Zhongping Yang
Sensorless induction motor control has been widely applied to the rail transit field. However, achieving a safe stop of a train using electric braking without applying air braking has been an urgent problem to be solved. The current research only considers the stability of the speed identification in the low-speed region and does not consider the impact of inaccurate parameters on the stability, which cannot ensure the stable braking and parking of the train under all working conditions. To address this problem, the coupling relationship between the motor speed and the stator resistance is used and an adaptive rate of them is designed based on the Lyapunov stability design law. In addition, aiming to reduce the torque ripple, a torque ripple elimination link is designed to cancel the torque ripple caused by the small-signal injection. Experiments show that the proposed parallel identification strategy of speed, stator resistance, and rotor resistance can ensure the system operation stability in the low- and zero-speed regions without increasing the torque ripple.
{"title":"Multi-parameter identification method of induction motor based on coupling and small signal injection","authors":"Zhihong Zhong, Xiaochun Fang, Fei Lin, Zhongping Yang","doi":"10.1049/elp2.12480","DOIUrl":"https://doi.org/10.1049/elp2.12480","url":null,"abstract":"<p>Sensorless induction motor control has been widely applied to the rail transit field. However, achieving a safe stop of a train using electric braking without applying air braking has been an urgent problem to be solved. The current research only considers the stability of the speed identification in the low-speed region and does not consider the impact of inaccurate parameters on the stability, which cannot ensure the stable braking and parking of the train under all working conditions. To address this problem, the coupling relationship between the motor speed and the stator resistance is used and an adaptive rate of them is designed based on the Lyapunov stability design law. In addition, aiming to reduce the torque ripple, a torque ripple elimination link is designed to cancel the torque ripple caused by the small-signal injection. Experiments show that the proposed parallel identification strategy of speed, stator resistance, and rotor resistance can ensure the system operation stability in the low- and zero-speed regions without increasing the torque ripple.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1317-1331"},"PeriodicalIF":1.5,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12480","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142708024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the in-service induction motors (IMs), friction and windage losses (FWL) value should be determined non-intrusively. Hence, in the in-service IMs, instead of measuring FWL, empirical equations are used to estimate FWL value. A novel technique is proposed for estimating the FWL value in low-voltage three-phase IMs based on obtained data from applying the no-load test on 425 simulated IMs in the MATLAB software. The simulated IMs are 380 V, 50 Hz, with different numbers of poles in the power range of 0.37–400 kW. The FWL value for simulated IMs is calculated based on the IEEE 112 standard and by applying the no-load test. Then, based on the dispersion of the obtained data from the no-load test and using non-linear regression, according to the number of IM poles for each number of poles, a third-degree equation for FWL estimation is fitted to the test data. The proposed method to estimate the FWL value only needs the nominal output power listed on the IM nameplate. Also, unlike existing empirical relationships, the proposed approach estimates the FWL value for IMs with high accuracy and non-intrusively. The effectiveness of the suggested technique is confirmed by simulation and practical results.
在使用中的感应电机(IM)中,摩擦和风动损失(FWL)值应以非侵入方式确定。因此,在使用中的感应电机中,使用经验方程来估算 FWL 值,而不是测量 FWL 值。根据在 MATLAB 软件中对 425 个模拟 IM 进行空载测试所获得的数据,提出了一种估算低压三相 IM 中 FWL 值的新技术。模拟 IM 的电压为 380 V,频率为 50 Hz,功率范围为 0.37-400 kW,具有不同的极数。模拟 IM 的 FWL 值是根据 IEEE 112 标准并通过空载测试计算得出的。然后,根据空载测试所得数据的离散性,并使用非线性回归,按照每个极数的 IM 极数,对测试数据拟合出用于估算 FWL 的三度方程。拟议的 FWL 估值方法只需要 IM 铭牌上列出的额定输出功率。此外,与现有的经验关系不同,所提出的方法能高精度、无干扰地估算出 IM 的 FWL 值。模拟和实际结果证实了所建议技术的有效性。
{"title":"A non-intrusive method for friction and windage losses estimation in induction motors","authors":"Moslem Geravandi, Hassan Moradi","doi":"10.1049/elp2.12482","DOIUrl":"https://doi.org/10.1049/elp2.12482","url":null,"abstract":"<p>In the in-service induction motors (IMs), friction and windage losses (FWL) value should be determined non-intrusively. Hence, in the in-service IMs, instead of measuring FWL, empirical equations are used to estimate FWL value. A novel technique is proposed for estimating the FWL value in low-voltage three-phase IMs based on obtained data from applying the no-load test on 425 simulated IMs in the MATLAB software. The simulated IMs are 380 V, 50 Hz, with different numbers of poles in the power range of 0.37–400 kW. The FWL value for simulated IMs is calculated based on the IEEE 112 standard and by applying the no-load test. Then, based on the dispersion of the obtained data from the no-load test and using non-linear regression, according to the number of IM poles for each number of poles, a third-degree equation for FWL estimation is fitted to the test data. The proposed method to estimate the FWL value only needs the nominal output power listed on the IM nameplate. Also, unlike existing empirical relationships, the proposed approach estimates the FWL value for IMs with high accuracy and non-intrusively. The effectiveness of the suggested technique is confirmed by simulation and practical results.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1347-1358"},"PeriodicalIF":1.5,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12482","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chun-Yao Lee, Truong-An Le, Wei-Lun Chien, Shih-Che Hsu
The authors present a model for diagnosing motor faults based on machine learning, demonstrating advantages over other algorithms in terms of both improved fitness values and reduced running time. The structure of the model involves three primary phases: feature extraction, feature selection and classification. During the feature extraction phase, crucial features are identified using empirical mode decomposition, fast Fourier transform and multiresolution analysis, resulting in a total of 144 features. The feature selection stage employs a new strategy that combines symmetrical uncertainty in the filter approach with the binary grey wolf optimiser and emperor penguin optimiser in the wrapper approach. Finally, a support vector machine is used for classification to generate fitness values. To validate the model's effectiveness and accuracy, motor fault current signal datasets, case Western Reserve University (CWRU) benchmark datasets and mechanical failure prevention technology benchmark datasets are utilised. In the motor fault current signal dataset, the highest average accuracy achieved is 99.95%, with a minimum average running time of 88.02 s obtained under ∞dB conditions. Regarding benchmark datasets and mechanical failures at CWRU, using the prevention technology benchmark dataset resulted in classification accuracies of 99.54% and 99.52%, respectively. Comparative analysis with traditional algorithms reveals that symmetric uncertainty and emperor penguin–grey wolf optimisation model outperforms traditional models in terms of performance.
{"title":"Application of symmetric uncertainty and emperor penguin–grey wolf optimisation for feature selection in motor fault classification","authors":"Chun-Yao Lee, Truong-An Le, Wei-Lun Chien, Shih-Che Hsu","doi":"10.1049/elp2.12459","DOIUrl":"https://doi.org/10.1049/elp2.12459","url":null,"abstract":"<p>The authors present a model for diagnosing motor faults based on machine learning, demonstrating advantages over other algorithms in terms of both improved fitness values and reduced running time. The structure of the model involves three primary phases: feature extraction, feature selection and classification. During the feature extraction phase, crucial features are identified using empirical mode decomposition, fast Fourier transform and multiresolution analysis, resulting in a total of 144 features. The feature selection stage employs a new strategy that combines symmetrical uncertainty in the filter approach with the binary grey wolf optimiser and emperor penguin optimiser in the wrapper approach. Finally, a support vector machine is used for classification to generate fitness values. To validate the model's effectiveness and accuracy, motor fault current signal datasets, case Western Reserve University (CWRU) benchmark datasets and mechanical failure prevention technology benchmark datasets are utilised. In the motor fault current signal dataset, the highest average accuracy achieved is 99.95%, with a minimum average running time of 88.02 s obtained under ∞dB conditions. Regarding benchmark datasets and mechanical failures at CWRU, using the prevention technology benchmark dataset resulted in classification accuracies of 99.54% and 99.52%, respectively. Comparative analysis with traditional algorithms reveals that symmetric uncertainty and emperor penguin–grey wolf optimisation model outperforms traditional models in terms of performance.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1107-1121"},"PeriodicalIF":1.5,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12459","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel method is presented for determining the derating factors of a three-phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three-phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three-phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three-phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three-phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.
{"title":"Derating factor determination of the three-phase induction motor under unbalanced voltage using pumping system","authors":"Samar Hameed Majeed, Seyed Ghodratolah Seifossadat, Mohsen Saniei, Seyyed Sajjad Moosapour","doi":"10.1049/elp2.12479","DOIUrl":"10.1049/elp2.12479","url":null,"abstract":"<p>A novel method is presented for determining the derating factors of a three-phase induction motor under the condition of the unbalanced supply voltages. In this method, a mechanical system is used which consist of the a centrifugal pump, two valves, a DC motor, which are connected to the shaft of the three-phase induction motor. A sliding mode control system is used for position control of the DC motor for adjusting the valve angle for derating the induction motor. The authors present the results of an experiment in which a three-phase induction motor was subjected to various unbalanced voltage conditions. The results of simulations were used to look into what happened when there were different levels of imbalanced voltage. This was done to determine how these situations changed an induction motor's speed, torque, and efficiency. For this system, the stator current would be greater than the rated current if there was an imbalance in the supply voltage. Therefore, to reduce the amount of power that the three-phase induction motor can produce, the control system uses a DC motor to reduce the angle of one of the two valves. This decreasing angle continues until the root mean square value of the stator current returns to the rated current. At this point, the derating factor may be calculated by dividing the output power of the three-phase induction motor in the unbalanced condition by the output power when there are ideal sinusoidal. The MATLAB SIMULINK environment is utilised to perform simulations of the proposed system.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1305-1316"},"PeriodicalIF":1.5,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12479","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141810845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
2-D air-gap magnetic field distribution is the essential prerequisite of electrical machine analysis. Because of the natural periodicity of rotary machines, Fourier analysis is a suitable choice for air-gap field prediction. However, due to the end-effect, periodicity is not present in linear machines and the Fourier series is not appropriate. In engineering mathematics, a rigorous method of solving partial differential equations is the separation of the variables method (SVM) which is based on the hypothesis that the field solution is in the form of the product of two functions of orthogonal directions; for example, in an axisymmetric structure, a longitudinal harmonic function (LHF) and a radial harmonic function (RHF). A particular case of these functions is trigonometric functions, which result in the Fourier series. SVM is imposed in a different manner, where RHF is approximated by the Bessel–Fourier series and consequently LHF has a (piecewise) exponential behaviour. This choice of basis functions not only serves the purpose of modelling the end-effect but also removes the Gibbs phenomenon, that is, it precisely models discontinuities of flux density at the surface of PMs. A numerical case-study of a slotless double-sided linear tubular surface-PM machine shows that the piecewise exponential approximation can attain 1% error while utilising only three harmonics, whereas the trigonometric approximation, due to the Gibbs phenomenon, slowly arrives at 20% error with 100 harmonics for approximating flux density. Results of both methods were validated using the finite element method (FEM). Additionally, it was discovered that the computational complexity of the model is independent of varying position; therefore, the analytical method could yield the back electromotive force and electromagnetic thrust force for a number of 320 positions at merely 0.2 s while the FEM software required 5 min.
{"title":"Air-gap field prediction in tubular doubly sided surface magnet machine using Bessel–Fourier series","authors":"M. H. Javanmardi, A. Rahideh","doi":"10.1049/elp2.12473","DOIUrl":"10.1049/elp2.12473","url":null,"abstract":"<p>2-D air-gap magnetic field distribution is the essential prerequisite of electrical machine analysis. Because of the natural periodicity of rotary machines, Fourier analysis is a suitable choice for air-gap field prediction. However, due to the end-effect, periodicity is not present in linear machines and the Fourier series is not appropriate. In engineering mathematics, a rigorous method of solving partial differential equations is the separation of the variables method (SVM) which is based on the hypothesis that the field solution is in the form of the product of two functions of orthogonal directions; for example, in an axisymmetric structure, a longitudinal harmonic function (LHF) and a radial harmonic function (RHF). A particular case of these functions is trigonometric functions, which result in the Fourier series. SVM is imposed in a different manner, where RHF is approximated by the Bessel–Fourier series and consequently LHF has a (piecewise) exponential behaviour. This choice of basis functions not only serves the purpose of modelling the end-effect but also removes the Gibbs phenomenon, that is, it precisely models discontinuities of flux density at the surface of PMs. A numerical case-study of a slotless double-sided linear tubular surface-PM machine shows that the piecewise exponential approximation can attain 1% error while utilising only three harmonics, whereas the trigonometric approximation, due to the Gibbs phenomenon, slowly arrives at 20% error with 100 harmonics for approximating flux density. Results of both methods were validated using the finite element method (FEM). Additionally, it was discovered that the computational complexity of the model is independent of varying position; therefore, the analytical method could yield the back electromotive force and electromagnetic thrust force for a number of 320 positions at merely 0.2 s while the FEM software required 5 min.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1244-1253"},"PeriodicalIF":1.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12473","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pengcheng Han, Ying Lou, Chao Wu, Li Zeng, Huimin Wang
In view of the cost and reliability issues caused by mechanical position sensors, position sensorless control (PSC) of permanent magnet synchronous motors (PMSMs) has received widespread attention. A series of rotor position estimation (RPE) schemes have been developed, in which the phase-locked loop (PLL) plays an important role. However, the conventional phase-locked loops face two thorny issues, one is the degradation of RPE performance under motor acceleration and deceleration conditions, and the other is high noise sensitivity. To this end, an adaptive gain PLL (AG-PLL) is proposed for PSC of PMSM drives. The gains of the loop filter in the proposed AG-PLL are adaptively adjusted with the estimation error in order to find a compromise between the estimation performance under motor acceleration and deceleration conditions and the noise sensitivity. Moreover, the proposed scheme avoids increasing the order of the PLL, so its dynamic performance is also guaranteed. The proposed scheme is tested based on the hardware-in-the-loop platform.
{"title":"An adaptive gain phase-locked loop for position sensorless control of permanent magnet synchronous motor drives","authors":"Pengcheng Han, Ying Lou, Chao Wu, Li Zeng, Huimin Wang","doi":"10.1049/elp2.12474","DOIUrl":"10.1049/elp2.12474","url":null,"abstract":"<p>In view of the cost and reliability issues caused by mechanical position sensors, position sensorless control (PSC) of permanent magnet synchronous motors (PMSMs) has received widespread attention. A series of rotor position estimation (RPE) schemes have been developed, in which the phase-locked loop (PLL) plays an important role. However, the conventional phase-locked loops face two thorny issues, one is the degradation of RPE performance under motor acceleration and deceleration conditions, and the other is high noise sensitivity. To this end, an adaptive gain PLL (AG-PLL) is proposed for PSC of PMSM drives. The gains of the loop filter in the proposed AG-PLL are adaptively adjusted with the estimation error in order to find a compromise between the estimation performance under motor acceleration and deceleration conditions and the noise sensitivity. Moreover, the proposed scheme avoids increasing the order of the PLL, so its dynamic performance is also guaranteed. The proposed scheme is tested based on the hardware-in-the-loop platform.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1254-1265"},"PeriodicalIF":1.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12474","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
An analytical and optimisation method is presented to improve the air-gap magnetic field of the surface-mounted permanent magnet machine with multi-level array magnets, which can reduce air-gap magnetic field harmonics and torque ripple. Different from the conventional analytical method (AM) around the entire single-magnet pole, the modelling method of multi-level equal-thickness ferrite magnets with different remanences for improving the air-gap flux density is investigated. Considering the influence of air-gap relative permeability by stator slots and multi-level magnet remanences on the air-gap flux density, the proposed AM for improving air-gap flux density is derived by analysing the slotless air-gap flux density and slotted air-gap relative permeability. The cogging torque is predicted with energy method by analysing the tangential magnetic field distribution at stator slots. Then, the back electromotive force is predicted by analysing the winding distribution and radial air-gap flux density. Based on the proposed AM, the simulated annealing particle swarm optimisation algorithm is used by optimising the widths and thicknesses of the multi-level array magnets to further reduce torque ripple and increase output torque. Finally, the accuracy of the proposed AM is verified by comparing with the finite element method.
本文提出了一种分析和优化方法,用于改善采用多级阵列磁体的表面贴装式永磁机械的气隙磁场,从而降低气隙磁场谐波和转矩纹波。与围绕整个单磁极的传统分析方法(AM)不同,研究了具有不同剩磁的多级等厚铁氧体磁体的建模方法,以改善气隙磁通密度。考虑到定子槽和多级磁体剩磁对气隙磁通密度的影响,通过分析无槽气隙磁通密度和有槽气隙相对磁导率,得出了用于改善气隙磁通密度的拟议 AM。通过分析定子槽的切向磁场分布,用能量法预测了齿槽转矩。然后,通过分析绕组分布和径向气隙磁通密度来预测反向电动势。在所提出的 AM 基础上,使用模拟退火粒子群优化算法优化多级阵列磁体的宽度和厚度,以进一步降低扭矩纹波并增加输出扭矩。最后,通过与有限元法进行比较,验证了所提出的 AM 的准确性。
{"title":"Modelling and optimisation of the surface-mounted permanent magnet machine with multi-level array magnets","authors":"Longxuan Li, Zhaoliang Chen, Wenliang Zhao, Chengwu Diao, Byung-il Kwon","doi":"10.1049/elp2.12478","DOIUrl":"10.1049/elp2.12478","url":null,"abstract":"<p>An analytical and optimisation method is presented to improve the air-gap magnetic field of the surface-mounted permanent magnet machine with multi-level array magnets, which can reduce air-gap magnetic field harmonics and torque ripple. Different from the conventional analytical method (AM) around the entire single-magnet pole, the modelling method of multi-level equal-thickness ferrite magnets with different remanences for improving the air-gap flux density is investigated. Considering the influence of air-gap relative permeability by stator slots and multi-level magnet remanences on the air-gap flux density, the proposed AM for improving air-gap flux density is derived by analysing the slotless air-gap flux density and slotted air-gap relative permeability. The cogging torque is predicted with energy method by analysing the tangential magnetic field distribution at stator slots. Then, the back electromotive force is predicted by analysing the winding distribution and radial air-gap flux density. Based on the proposed AM, the simulated annealing particle swarm optimisation algorithm is used by optimising the widths and thicknesses of the multi-level array magnets to further reduce torque ripple and increase output torque. Finally, the accuracy of the proposed AM is verified by comparing with the finite element method.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1293-1304"},"PeriodicalIF":1.5,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12478","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141832136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haikun Shang, Zixuan Zhao, Ranzhe Zhang, Zhiming Wang, Jiawen Li
Insulation deterioration, which is mainly caused by partial discharge (PD) occurring inside power transformers, is one of the prime reasons to cause transformer faults. Therefore, an effective diagnosis of PD is crucial to ensure the safe and stable operation of transformers. To extract more effective features that characterise transformers PD signals and enhance the recognition accuracy, a novel transformer PD fault diagnosis model based on improved adaptive local iterative filtering (ALIF) and bidirectional long short-term memory (BILSTM) neural network is proposed. Addressing the issue of predetermined decomposition levels and accuracy in ALIF decomposition, the golden jackal optimisation (GJO) algorithm is introduced to optimise the parameters. The proposed fault diagnostic model extracts dominant PD features employing the improved ALIF and Refined Composite Multi-Scale Dispersion Entropy and improves the diagnostic accuracy with the optimised BILSTM by introducing GJO. Experimental data evaluates the performance of support vector machine, long short-term memory and BILSTM. The results verify the effectiveness and superiority of the proposed model.
{"title":"Transformer partial discharge fault diagnosis based on improved adaptive local iterative filtering-bidirectional long short-term memory","authors":"Haikun Shang, Zixuan Zhao, Ranzhe Zhang, Zhiming Wang, Jiawen Li","doi":"10.1049/elp2.12471","DOIUrl":"10.1049/elp2.12471","url":null,"abstract":"<p>Insulation deterioration, which is mainly caused by partial discharge (PD) occurring inside power transformers, is one of the prime reasons to cause transformer faults. Therefore, an effective diagnosis of PD is crucial to ensure the safe and stable operation of transformers. To extract more effective features that characterise transformers PD signals and enhance the recognition accuracy, a novel transformer PD fault diagnosis model based on improved adaptive local iterative filtering (ALIF) and bidirectional long short-term memory (BILSTM) neural network is proposed. Addressing the issue of predetermined decomposition levels and accuracy in ALIF decomposition, the golden jackal optimisation (GJO) algorithm is introduced to optimise the parameters. The proposed fault diagnostic model extracts dominant PD features employing the improved ALIF and Refined Composite Multi-Scale Dispersion Entropy and improves the diagnostic accuracy with the optimised BILSTM by introducing GJO. Experimental data evaluates the performance of support vector machine, long short-term memory and BILSTM. The results verify the effectiveness and superiority of the proposed model.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1214-1232"},"PeriodicalIF":1.5,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12471","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141644467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jinghua Ji, Chen Jia, Wenxiang Zhao, Zhijian Ling, Yu Zeng, Zongwang Li
The authors present a low-loss dual-permanent-magnet-excited vernier (DPMEV) machine with segmented stator design to meet the requirements of low iron loss of electric aircraft based on the field modulation theory. The stator topology features and losses of both the original and segmented DPMEV machines are comparatively investigated. Then, the armature air-gap flux density is deduced by the magnetic motive force-permeance model, and the influence of each harmonic on the losses are analysed. It is found that the harmonic which produces losses in the original machine reduced greatly after introducing the segmented structure. Furthermore, the electromagnetic performances of two DPMEV machines are comparatively analysed by finite element analysis. Finally, two prototypes of the original and segmented DPMEV machines are built and tested to verify the theoretical analysis.
{"title":"Reduction of losses in dual-permanent-magnet-excited Vernier machine by segmented stator for electric aircraft","authors":"Jinghua Ji, Chen Jia, Wenxiang Zhao, Zhijian Ling, Yu Zeng, Zongwang Li","doi":"10.1049/elp2.12476","DOIUrl":"10.1049/elp2.12476","url":null,"abstract":"<p>The authors present a low-loss dual-permanent-magnet-excited vernier (DPMEV) machine with segmented stator design to meet the requirements of low iron loss of electric aircraft based on the field modulation theory. The stator topology features and losses of both the original and segmented DPMEV machines are comparatively investigated. Then, the armature air-gap flux density is deduced by the magnetic motive force-permeance model, and the influence of each harmonic on the losses are analysed. It is found that the harmonic which produces losses in the original machine reduced greatly after introducing the segmented structure. Furthermore, the electromagnetic performances of two DPMEV machines are comparatively analysed by finite element analysis. Finally, two prototypes of the original and segmented DPMEV machines are built and tested to verify the theoretical analysis.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 12","pages":"1740-1751"},"PeriodicalIF":1.5,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12476","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141646947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The authors propose an analytical modelling approach for the linear transverse flux permanent magnet motor using the magnetic equivalent circuit method. The main focus of this study is to predict the phase flux-linkage characteristic of the motor. Essential equations required for implementation of the model and how to solve it are described clearly so that someone can use it easily. A typical motor is selected to apply the proposed model and simulation results, including static characteristics of flux-linkage and thrust, are presented. To validate the developed analytical model, the discussed motor is also analysed with 3D finite element method using MAXWELL software and the obtained simulation results are compared to each other.
{"title":"Analytical modelling of the linear transverse flux permanent magnet motor using magnetic equivalent circuit method","authors":"Morteza Akhlaqi, Babak Ganji, Payam Vahedi","doi":"10.1049/elp2.12475","DOIUrl":"10.1049/elp2.12475","url":null,"abstract":"<p>The authors propose an analytical modelling approach for the linear transverse flux permanent magnet motor using the magnetic equivalent circuit method. The main focus of this study is to predict the phase flux-linkage characteristic of the motor. Essential equations required for implementation of the model and how to solve it are described clearly so that someone can use it easily. A typical motor is selected to apply the proposed model and simulation results, including static characteristics of flux-linkage and thrust, are presented. To validate the developed analytical model, the discussed motor is also analysed with 3D finite element method using MAXWELL software and the obtained simulation results are compared to each other.</p>","PeriodicalId":13352,"journal":{"name":"Iet Electric Power Applications","volume":"18 10","pages":"1266-1278"},"PeriodicalIF":1.5,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/elp2.12475","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141648405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}