Dianhai Zhang

Study on air friction loss of high speed PM machine

Air friction loss of rotor surface for a high speed machine is quite large and difficult to be determined accurately. In this paper, the rotor friction loss for a high speed permanent magnet machine with rated speed of 60000rpm was studied theoretically and experimentally. The friction losses for different rotor speeds were calculated based on the 3D finite element analysis of fluid field. The experimental friction losses were obtained by loss separation based on the tested total losses of the machine for different rotor speeds. The calculated friction losses are accorded with the tested results which show the validity and feasibility of the calculation method of friction loss.

Multi-objective worst-case scenario robust optimal design of switched reluctance motor incorporated with FEM and Kriging

In this paper, one multi-objective robust optimization algorithm is applied to the optimal design of switched reluctance motor. The performance robustness against uncertainty in design variables is evaluated utilizing the first order sensitivity assisted-worst case scenario approximation. In order to reduce the computing cost required by the finite element analysis, the Kriging surrogate model is used to predict performance of switched reluctance motor during optimization process. With the help of multi-objective particle warm optimization algorithm, a set of robust optimal designs are obtained through making a balance between maximizing average torque and minimizing torque tipple.

A Possibility-Based Robust Optimal Design Algorithm in Preliminary Design Stage of Electromagnetic Devices

In the early design stage of an electromagnetic device, sufficient information on uncertainties of design variables is not available. Therefore, a reliable optimal design cannot be achieved by the conventional reliability analysis, in which the probabilistic method is applied. This paper, considering the insufficient uncertainty data, proposes a possibility-based optimal design algorithm to get a robust and reliable optimal design of electromagnetic devices. The suggested algorithm adopts a possibility analysis utilizing the fuzzy set theory. In addition, to mitigate the expensive performance analysis during possibility analysis, the design sensitivity analysis is employed to construct a surrogate model. Finally, the developed algorithm is validated through applications to several examples.

Multi-Objective Optimal Design of a NEMA Design D Three-phase Induction Machine Utilizing Gaussian-MOPSO Algorithm

This paper presents a multi-objective optimization approach to design rotor slot geometry of three-phase squirrel cage induction machine to achieve NEMA design D torque-speed (T-S) characteristics with high efficiency. The multi-objective Particle Swarm Optimization (MOPSO) algorithm combined with the adaptive response surface method and Latin hypercube sampling strategy is applied to obtain the Pareto optimal designs. In order to demonstrate the validity of the suggested optimal algorithm, an application to rotor slot design of three-phase induction motor is presented.

Study on core loss of high speed PM machine

Mathematics model of core loss for high speed machine is discussed. A measuring approach of core loss coefficients for different frequencies is proposed. Calculation method of core loss based on finite element analysis is introduced. Experiment results of core losses for a high speed permanent magnet machine are presented. The consistency of the calculated data with the experimental result shows the validity and feasibility of the core loss calculation method for high speed machine.

Magnetostriction of Silicon Steel Sheets Under Different Magnetization Conditions

The magnetostriction of electrical steel is one of the main sources causing deformation and vibration in rotational machine and transformer cores. The presence of dc bias or higher harmonics of magnetic field in the electrical apparatus cores makes the vibration and noise of cores more serious. Therefore, it is necessary to identify how different magnetization patterns contribute to the magnetostriction noise. This paper performs the measurement of magnetostrictive strain in non-oriented and grain-oriented electrical steel sheets under sinusoidal excitation, one with a dc bias and the other with a third harmonic component, respectively. An investigation of the effect of dc biased magnetic field on the magnetostrictive property is carried out. The influences of a third harmonic of magnetic field with a variety of amplitudes and phase delay on magnetostriction are studied and the acoustic noise level is calculated due to the presence of the second (100 Hz) and fourth (200 Hz) harmonics of magnetostrictive strain. The research results are important for evaluating the noise of electrical machine and transformer core effectively.

A Novel Subdivision-Based Optimal Design Algorithm for Multidimensional Electromagnetic Problems

For the large-scale electromagnetic problems, the existing optimization methods normally cannot search for a global optimal solution in the design space accurately and have a lower numerical efficiency. In order to mitigate these problems, this paper presents a novel optimal design algorithm based on the subdivision strategy. In the proposed algorithm, first, the whole design space is decomposed into a set number of subregions. Correspondingly, the problem is optimized simultaneously by applying any global optimizer to each subregion. The utilization of subregion strategy in the global optimizers can guarantee a faster convergence and a wider diversity of solutions. The implementation of parallel optimization will effectively reduce the expensive computational cost, especially for the design of the large-scale/multidimensional electromagnetic problems. Finally, the numerical efficiency and the searching ability of the proposed algorithm are validated through applications to two multidimensional electromagnetic problems. One is the design of a superconducting magnetic energy storage (SMES) system, and the other is the design of a Thomson-coil actuator used in the arc eliminator system.

Optimal Design of Powder-Aligning and Magnetizing Fixtures for an Anisotropic-Bonded NdFeB Permanent Magnet

This paper presents a systematical optimal design method for powder aligning fixture during forming process and magnetizing fixture during magnetizing process for an anisotropic-bonded NdFeB magnet. Before the forming process, the mixture ratio of magnet powder and resin, molding tool temperature, and filling density are selected to improve the magnetic performance. During the forming process, a newly multiobjective optimization model is proposed to obtain the required orientation and maximum aligning field. Thus, in the magnetizing process, an anisotropic-bonded NdFeB magnet with required orientation and high residual magnetic flux density is obtained by applying a single-objective optimization process. To accurately predict the residual magnetic flux density, the transient finite element method combined with the Jiles-Atherton hysteresis model, taking the aligning field into account.

Modeling of anisotropic magnetostriction under alternating magnetization based on neural network-FFT model

Purpose This paper aims to investigate the magnetostrictive phenomenon in a single electrical steel sheet, which may cause vibration and noise in the cores of transformers and induction motors. A measurement system of magnetostriction is created and the principal strain of magnetostriction is modeled. Furthermore, the magnetostriction property along arbitrary alternating magnetization directions is modeled. Design/methodology/approach A measurement system with a triaxial strain gauge is developed to obtain the magnetostrictive waveform, and the principal strain is computed in terms of the in-plane strain formula. A three-layer feed-forward neural network model is proposed to model the measured magnetostriction property of the electrical steel sheet. Findings The principal strain of magnetostriction of the non-oriented electrical steel has strong anisotropy. The proposed estimation model can be effectively used to model the anisotropic magnetostriction with an acceptable prediction time. Originality/value This paper develops the neural network combined with fast Fourier transform (FFT) to model the principal strain property of magnetostriction under alternating magnetizations, and its validation has been verified.

Residual Magnetic Flux Density Distribution Calculation Considering Effect of Aligning Field for Anisotropic Bonded NdFeB Magnets

This paper presents a calculation method of residual magnetic flux density distribution for a four-pole anisotropic bonded NdFeB permanent magnet (PM) considering the effect of aligning magnetic field during the forming process. To manufacture the anisotropic bonded NdFeB magnet, the magnet powder needs to be aligned with a proper aligning field before magnetizing. Therefore, it is necessary to analyze the magnetizing process based on the aligning field analysis to determine accurate distribution of residual magnetic flux density (B r ) for the anisotropic bonded NdFeB PM. In order to estimate the B r distribution of the anisotropic bonded NdFeB magnet, an analysis method by combining the external electric circuit equation coupled with the transient finite element method and the scalar Jiles-Atherton hysteresis model is proposed.