NUMERICAL STUDY OF A TIME-DOMAIN FINITE ELEMENT METHOD FOR NONLINEAR MAGNETIC PROBLEMS IN THREE DIMENSIONS (Invited Paper)

Yan, Su; Jin, Jian‐Ming; Wang, Chao‐Fu; Kotulski, Joseph D.

doi:10.2528/pier15091006

Cited by 15 publications

(3 citation statements)

References 21 publications

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“…In the NR method, the BH-curve should be monotonic and may be linearly extended for higher values of the field. The NR method is especially valuable for time-domain problems [26], where the computational time becomes more critical. Additionally, to further enhance the convergence speed, relaxation methods [27,28] or hybrid methods [29] can be considered.…”

Section: Newton-raphsonmentioning

confidence: 99%

High-Order Methods Applied to Nonlinear Magnetostatic Problems

Friedrich

Curti

Gysen

et al. 2019

MCA

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This paper presents a comparison between two high-order modeling methods for solving magnetostatic problems under magnetic saturation, focused on the extraction of machine parameters. Two formulations are compared, the first is based on the Newton-Raphson approach, and the second successively iterates the local remanent magnetization and the incremental reluctivity of the nonlinear soft-magnetic material. The latter approach is more robust than the Newton-Raphson method, and uncovers useful properties for the fast and accurate calculation of incremental inductance. A novel estimate for the incremental inductance relying on a single additional computation is proposed to avoid multiple nonlinear simulations which are traditionally operated with finite difference linearization or spline interpolation techniques. Fast convergence and high accuracy of the presented methods are demonstrated for the force calculation, which demonstrates their applicability for the design and analysis of electromagnetic devices.

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Section: Newton-raphsonmentioning

confidence: 99%

High-Order Methods Applied to Nonlinear Magnetostatic Problems

Friedrich

Curti

Gysen

et al. 2019

MCA

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“…Electrical machines, power and electronic transformers and inductors are composed of cores of non-linear magnetic materials. Magnetic hysteresis is a fundamental property of non-linear magnetic materials (Yan et al , 2015; Yan and Jin, 2015). In order that these widely used devices (from the power system to the telecommunication systems) get designed and analyzed better, it is necessary to model the hysteresis loop of the non-linear material of which the core is composed.…”

Section: Introductionmentioning

confidence: 99%

Parameter identification of Jiles–Atherton model using the chaotic optimization method

Rubežić

Lazović

Jovanović

2018

COMPEL

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Purpose The purpose of this paper is to propose a chaotic optimization method for identifying the parameters of the Jiles–Atherton (J-A) hysteresis model. Design/methodology/approach The J-A model has five parameters which are assigned with physical meaning and whose determination is demanding. To determine these parameters, the fitness function, which represents the difference between the measured and the modeled hysteresis loop, is formed. Optimal parameter values are the values that minimize the fitness function. Findings The parameters of J-A model for three magnetic materials are determined. The model with the optimal parameters is validated using measured data and comparison with particle swarm optimization algorithm, genetic algorithm, pattern search and simulated annealing algorithm. The results show that the proposed method provides better agreement between measured and modeled hysteresis loop than other methods used for comparison. The proposed method is also suitable for simultaneous optimization of multiple hysteresis loops. Originality/value Chaotic optimization method is implemented for the first time for J-A model parameter identification. Numerical comparisons with results obtained with other optimization algorithms demonstrate that this method is a suitable alternative in parameters identification of J-A hysteresis model. Furthermore, this method is easy to implement and set up.

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“…This choice allows engineers to analyze the dynamic system including the nonlinear materials, permanent magnets and induced eddy currents under a variety of conditions, under various excitations including the pulsed waveform. This procedure is usually very time-consuming since it requires N t · N e matrix solutions, where N t is the number of time steps and N e is the average number of nonlinear iterations [1][2][3][4][5][6]. Provided that an algorithm (or method) can be made parallel, parallel computing can cut down simulation time for a nonlinear transient problem.…”

Section: Introductionmentioning

confidence: 99%

Time Decomposition Method for the General Transient Simulation of Low-Frequency Electromagnetics

He¹,

Lu²,

Chen³

et al. 2017

PIER

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Abstract-This paper describes a highly robust and efficient parallel computing method for the transient simulation of low-frequency electromagnetics with nonlinear materials and/or permanent magnets. In this method, time subdivisions are introduced to control the memory usage and nonlinear convergence. A direct block triangular matrix solver is applied to solve the formulated block matrix for each subdivision. This method has been implemented using the Message Passing Interface (MPI) for distributed memory parallel processing. Depending on the number of available MPI processes and physical memory, the entire nonlinear transient simulation can be divided into several subdivisions along the time-axis such that each MPI process handles only the computation for one time-step. Application examples are presented to demonstrate that this method can achieve excellent scalability of speedup.

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NUMERICAL STUDY OF A TIME-DOMAIN FINITE ELEMENT METHOD FOR NONLINEAR MAGNETIC PROBLEMS IN THREE DIMENSIONS (Invited Paper)

Cited by 15 publications

References 21 publications

High-Order Methods Applied to Nonlinear Magnetostatic Problems

High-Order Methods Applied to Nonlinear Magnetostatic Problems

Parameter identification of Jiles–Atherton model using the chaotic optimization method

Time Decomposition Method for the General Transient Simulation of Low-Frequency Electromagnetics

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