We analytically solve Poisson’s equation for the magnetic scalar potential generated by a uniformly magnetized rectangular prism and determine a closed-form solution for the magnetic scalar potential given only in terms of arctan and natural logarithmic functions. We show that the magnetic scalar potential can be written as a demagnetization vector, containing all the geometric information, multiplied with the magnetization, analogous to demagnetization tensors. We validate the derived analytical expression for the magnetic scalar potential by comparing it with a finite element simulation and show that these agree perfectly. We finally extend the concept of the demagnetization vector and tensor, which contains the geometric information for the source generating the potential, to gravitational objects.
{"title":"The Magnetic Scalar Potential for a Rectangular Prism","authors":"Berian James;Stefan Pollok;Jes Frellsen;Rasmus Bjørk","doi":"10.1109/TMAG.2025.3632626","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3632626","url":null,"abstract":"We analytically solve Poisson’s equation for the magnetic scalar potential generated by a uniformly magnetized rectangular prism and determine a closed-form solution for the magnetic scalar potential given only in terms of arctan and natural logarithmic functions. We show that the magnetic scalar potential can be written as a demagnetization vector, containing all the geometric information, multiplied with the magnetization, analogous to demagnetization tensors. We validate the derived analytical expression for the magnetic scalar potential by comparing it with a finite element simulation and show that these agree perfectly. We finally extend the concept of the demagnetization vector and tensor, which contains the geometric information for the source generating the potential, to gravitational objects.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 1","pages":"1-6"},"PeriodicalIF":1.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-13DOI: 10.1109/TMAG.2025.3632479
Juan Manuel Conde Garrido;Jone Ugarte Valdivielso;Jose I. Aizpurua;Manex Barrenetxea Iñarra;Josefina María Silveyra
We introduce a novel blind optimization method for determining the parameters of the Jiles–Atherton model of hysteresis, eliminating the need for user-provided initial guesses or search spaces. A carefully designed initialization procedure combined with a standard optimizer yields a high-performing, practical method for parameter estimation. Validation against a theoretical benchmark recovers ground-truth parameters in under half a minute with negligible error (relative error < 4 $times$ 10−8). When applied to the TEAM32 electrical steel experimental benchmark, our method achieved superior accuracy than previously reported fittings, also converging in under half a minute. Consistently robust performance is further demonstrated across diverse systems, including soft ferrites, nanocrystalline alloys, and magnetostrictive compounds. The presented blind approach offers new insights into magnetic material characterization and is deployed as an automated tool for hysteresis analysis. It advances both fundamental understanding and practical applications by demonstrating the Jiles–Atherton model’s capability to describe anisotropic materials and by revealing its inherent limitations.
{"title":"Blind Efficient Method for Optimizing Jiles–Atherton Model Parameters","authors":"Juan Manuel Conde Garrido;Jone Ugarte Valdivielso;Jose I. Aizpurua;Manex Barrenetxea Iñarra;Josefina María Silveyra","doi":"10.1109/TMAG.2025.3632479","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3632479","url":null,"abstract":"We introduce a novel blind optimization method for determining the parameters of the Jiles–Atherton model of hysteresis, eliminating the need for user-provided initial guesses or search spaces. A carefully designed initialization procedure combined with a standard optimizer yields a high-performing, practical method for parameter estimation. Validation against a theoretical benchmark recovers ground-truth parameters in under half a minute with negligible error (relative error < 4 <inline-formula> <tex-math>$times$ </tex-math></inline-formula> 10−8). When applied to the TEAM32 electrical steel experimental benchmark, our method achieved superior accuracy than previously reported fittings, also converging in under half a minute. Consistently robust performance is further demonstrated across diverse systems, including soft ferrites, nanocrystalline alloys, and magnetostrictive compounds. The presented blind approach offers new insights into magnetic material characterization and is deployed as an automated tool for hysteresis analysis. It advances both fundamental understanding and practical applications by demonstrating the Jiles–Atherton model’s capability to describe anisotropic materials and by revealing its inherent limitations.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 1","pages":"1-11"},"PeriodicalIF":1.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1109/TMAG.2025.3631371
Chong Di;Rongze Li;Junhao Wang;Xiaohua Bao
In this article, a novel computationally efficient finite element method for electromagnetic modeling of permanent magnet synchronous machines (PMSMs) has been proposed, of which the main idea is based on the time–space symmetrical property of the electromagnetic field of the PMSM. Using the proposed approach, the steady-state finite element analysis (FEA) has been further accelerated and only 1/6 electrical time period is needed for the computation. The scalar quantities, e.g., flux linkage waveforms in a full time period, can be further stitched by the three-phase signal in 1/6 electrical time period. Meanwhile, the whole geometry domain of a PMSM modeled in FEA has been divided into three parts, so that the field quantities, e.g., flux density waveforms, can be obtained at the symmetric mesh nodes using a reconstructed structured mesh with sector elements. Therefore, the flux density distribution and waveform in the full time period can also be predicted using the time–space symmetrical property of the electromagnetic field. The proposed method proves to be capable of providing electromagnetic performances as accurate as the traditional FEA, including flux linkage, electromagnetic torque, core losses, and efficiency. Finally, the proposed computationally efficient FEA has been verified by detailed comparisons to both the traditional FEA and experimental results.
{"title":"A Computationally Efficient Method for Electromagnetic Modeling of Permanent Magnet Synchronous Machines Based on Time–Space Symmetrical Finite Element Analysis","authors":"Chong Di;Rongze Li;Junhao Wang;Xiaohua Bao","doi":"10.1109/TMAG.2025.3631371","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3631371","url":null,"abstract":"In this article, a novel computationally efficient finite element method for electromagnetic modeling of permanent magnet synchronous machines (PMSMs) has been proposed, of which the main idea is based on the time–space symmetrical property of the electromagnetic field of the PMSM. Using the proposed approach, the steady-state finite element analysis (FEA) has been further accelerated and only 1/6 electrical time period is needed for the computation. The scalar quantities, e.g., flux linkage waveforms in a full time period, can be further stitched by the three-phase signal in 1/6 electrical time period. Meanwhile, the whole geometry domain of a PMSM modeled in FEA has been divided into three parts, so that the field quantities, e.g., flux density waveforms, can be obtained at the symmetric mesh nodes using a reconstructed structured mesh with sector elements. Therefore, the flux density distribution and waveform in the full time period can also be predicted using the time–space symmetrical property of the electromagnetic field. The proposed method proves to be capable of providing electromagnetic performances as accurate as the traditional FEA, including flux linkage, electromagnetic torque, core losses, and efficiency. Finally, the proposed computationally efficient FEA has been verified by detailed comparisons to both the traditional FEA and experimental results.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 1","pages":"1-10"},"PeriodicalIF":1.9,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-10DOI: 10.1109/TMAG.2025.3631022
Qinhong Zhong;Qinfeng Hu;Shushu Zhu;Chuang Liu
Optimizing permanent magnet (PM) and slot shapes improves surface-mounted PM motor thrust performance. However, this optimization complicates air-gap boundary conditions, creating electromagnetic analysis challenges. To address this, this article proposes a hybrid analytical method integrating equivalent magnetic network (EMN) and sub-domain approaches. Two key innovations enable its application in motors with nonuniform air-gap length. First, arc-shaped PMs are converted into rectangular equivalents. This geometric transformation achieves planar interfaces between PMs and air-gap regions, thereby reducing the computational complexity of magnetic vector potential solutions. Second, extending the EMN into the air-gap region decouples the core from the boundary. This eliminates repeated EMN discretization during slot shape optimization. The hybrid analytical model (HAM) is employed to predict back electromotive force, detent force, and load thrust, which are validated by the finite element analysis (FEA). During motor optimization, the HAM achieves an 89% computation time reduction compared to finite element method (FEM). Experimental results align with both the FEM and hybrid model predictions, confirming the method's applicability for rapid surfacemounted PM motor design.
{"title":"A Hybrid Analysis Method for SPMLSMs With Non-Uniform Air-Gap Length","authors":"Qinhong Zhong;Qinfeng Hu;Shushu Zhu;Chuang Liu","doi":"10.1109/TMAG.2025.3631022","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3631022","url":null,"abstract":"Optimizing permanent magnet (PM) and slot shapes improves surface-mounted PM motor thrust performance. However, this optimization complicates air-gap boundary conditions, creating electromagnetic analysis challenges. To address this, this article proposes a hybrid analytical method integrating equivalent magnetic network (EMN) and sub-domain approaches. Two key innovations enable its application in motors with nonuniform air-gap length. First, arc-shaped PMs are converted into rectangular equivalents. This geometric transformation achieves planar interfaces between PMs and air-gap regions, thereby reducing the computational complexity of magnetic vector potential solutions. Second, extending the EMN into the air-gap region decouples the core from the boundary. This eliminates repeated EMN discretization during slot shape optimization. The hybrid analytical model (HAM) is employed to predict back electromotive force, detent force, and load thrust, which are validated by the finite element analysis (FEA). During motor optimization, the HAM achieves an 89% computation time reduction compared to finite element method (FEM). Experimental results align with both the FEM and hybrid model predictions, confirming the method's applicability for rapid surfacemounted PM motor design.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 2","pages":"1-11"},"PeriodicalIF":1.9,"publicationDate":"2025-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-07DOI: 10.1109/TMAG.2025.3630487
Sofiane Ben Mbarek;Selma Amara;Gianluca Setti
Magnetic tags offer a compelling alternative to other identification and sensing techniques due to their distinctive combination of durability, potential for miniaturization, and compatibility with non-line-of-sight detection. These tags can generate a multitude of unique codes, identifiable through remote decoding via magnetic measurements. To date, no prior research has specifically addressed the approach of recognizing and identifying magnetic tags through far-field magnetic flux measurements. In this article, we present an innovative study that addresses the inverse problem of recognizing the configuration of a planar 2 × 2 array of N52 grade neodymium permanent magnets using far-field magnetic measurements. The Euler deconvolution method was employed to resolve a linear system derived from the spatial and vertical derivatives of the field. Concurrently, a brute-force matching method was used to compare the normalized measurement data with the forward-simulated fields of all possible configurations to identify the closest match. The results presented herein demonstrate that the proposed algorithm is capable of identifying distinct magnetic tag signatures, particularly when magnetic configurations are arranged in complex designs, with a mean squared error (mse) of less than 12%.
{"title":"Magnetic Dipole-Based Tag Recognition From Far-Field Measurements via Euler Deconvolution","authors":"Sofiane Ben Mbarek;Selma Amara;Gianluca Setti","doi":"10.1109/TMAG.2025.3630487","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3630487","url":null,"abstract":"Magnetic tags offer a compelling alternative to other identification and sensing techniques due to their distinctive combination of durability, potential for miniaturization, and compatibility with non-line-of-sight detection. These tags can generate a multitude of unique codes, identifiable through remote decoding via magnetic measurements. To date, no prior research has specifically addressed the approach of recognizing and identifying magnetic tags through far-field magnetic flux measurements. In this article, we present an innovative study that addresses the inverse problem of recognizing the configuration of a planar 2 × 2 array of N52 grade neodymium permanent magnets using far-field magnetic measurements. The Euler deconvolution method was employed to resolve a linear system derived from the spatial and vertical derivatives of the field. Concurrently, a brute-force matching method was used to compare the normalized measurement data with the forward-simulated fields of all possible configurations to identify the closest match. The results presented herein demonstrate that the proposed algorithm is capable of identifying distinct magnetic tag signatures, particularly when magnetic configurations are arranged in complex designs, with a mean squared error (mse) of less than 12%.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 1","pages":"1-6"},"PeriodicalIF":1.9,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11232512","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-05DOI: 10.1109/TMAG.2025.3627379
{"title":"TechRxiv: Share Your Preprint Research with the World!","authors":"","doi":"10.1109/TMAG.2025.3627379","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3627379","url":null,"abstract":"","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 11","pages":"1-1"},"PeriodicalIF":1.9,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11230195","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-05DOI: 10.1109/TMAG.2025.3625119
{"title":"IEEE Magnetics Society Information","authors":"","doi":"10.1109/TMAG.2025.3625119","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3625119","url":null,"abstract":"","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"61 11","pages":"C2-C2"},"PeriodicalIF":1.9,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11230197","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145455799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-03DOI: 10.1109/TMAG.2025.3628163
Brandon E. Carroll;Jacob L. B. Aman;Shad Roundy;Jake J. Abbott
Radial (also known as radial-flux) magnetic torque couplers (MTCs) enable the transfer of torque between an inner rotor (IR) and an outer rotor (OR), each equipped with a set of permanent magnets. In a previous article, we used dimensional analysis to find the minimum set of nondimensional parameters required to characterize an MTC, and then performed a parametric optimization to maximize the synchronous torque (i.e., the torque required to cog the IR with respect to the OR) in a given package size. However, we only explicitly optimized an MTC with 16 IR magnets and 16 OR magnets, which results in eight stable magnetic equilibria. In this addendum, we applied the same methodology to consider MTCs with 1, 2, 4, 8, 16, and 32 stable equilibria. We observe clear trends in the optimal values of the various MTC parameters as we change the number of magnets. We also find that the maximum synchronous torque grows asymptotically with the number of stable equilibria, with a diminishing return beyond 16.
{"title":"Addendum to “Optimal Parametric Design of Radial Magnetic Torque Couplers via Dimensional Analysis”","authors":"Brandon E. Carroll;Jacob L. B. Aman;Shad Roundy;Jake J. Abbott","doi":"10.1109/TMAG.2025.3628163","DOIUrl":"https://doi.org/10.1109/TMAG.2025.3628163","url":null,"abstract":"Radial (also known as radial-flux) magnetic torque couplers (MTCs) enable the transfer of torque between an inner rotor (IR) and an outer rotor (OR), each equipped with a set of permanent magnets. In a previous article, we used dimensional analysis to find the minimum set of nondimensional parameters required to characterize an MTC, and then performed a parametric optimization to maximize the synchronous torque (i.e., the torque required to cog the IR with respect to the OR) in a given package size. However, we only explicitly optimized an MTC with 16 IR magnets and 16 OR magnets, which results in eight stable magnetic equilibria. In this addendum, we applied the same methodology to consider MTCs with 1, 2, 4, 8, 16, and 32 stable equilibria. We observe clear trends in the optimal values of the various MTC parameters as we change the number of magnets. We also find that the maximum synchronous torque grows asymptotically with the number of stable equilibria, with a diminishing return beyond 16.","PeriodicalId":13405,"journal":{"name":"IEEE Transactions on Magnetics","volume":"62 1","pages":"1-3"},"PeriodicalIF":1.9,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145847764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：