1. Introduction
The design and performance analysis of large-scale electrical products such as motors and transformers usually involve multi-physics coupling calculations, such as electricity, magnetism, heat, and force. During the calculation process, the electro-magnetic properties of electrical materials used in electrical equipment need to be described and measured by experimental methods. The accuracy of the electro-magnetic performance data is directly related to the accuracy and validity of the data analysis results.
The electro-magnetic characteristic parameters such as saturation magnetic induction intensity, magnetic permeability, specific loss, remanence, and coercive force of electrical steel sheets are closely related to temperature. At present, many scholars have done much research on the influence of temperature on the magnetic properties of electrical steel sheets. Norio et al. studied the effect of high temperature on the magnetic properties of non-oriented electrical steel sheets. The study showed that when the temperature is higher than 500 °C, the magnetic permeability will change sharply, and the iron loss will decrease with the increase in temperature [
1]. Andreas et al. studied the influence of motor operating temperature on the stator core loss and magnetic properties of small permanent magnet synchronous motors [
2]. M.Z. et al. studied and analyzed the crystal structure and magnetic properties of 2.6% ferrosilicon materials under cold rolling and different annealing temperatures [
3]. M.L. et al. proposed an Epstein measurement device adapted to high temperature conditions, and measured ferromagnetic materials at a high temperature of 600 °C and different frequencies. The results showed that temperature has a certain effect on the stack loss and magnetic properties of grain-oriented silicon steel [
4]. Sajid and Abdelkader proposed a Jiles–Atherton hysteresis model for non-oriented electrical steel sheets considering temperature factors [
5]. Shuhong et al. investigated the magneto-thermal coupling analysis of the resonant reset forward converter and considered the effect of temperature on the core permeability and copper winding conductivity in the building of the multi-physics field coupling model [
6].
In addition, related scholars have also done much research on the temperature rise caused by thermal effects. Yunyan et al. studied and analyzed the effect of heat generated during the starting process of a high-power-density and high-voltage induction motor on the temperature field [
7]. Shuye et al. analyzed the temperature rise distribution of a permanent magnet wind turbine by establishing different solution domain models [
8]. Longnv used the convection heat transfer coefficient as the boundary condition of the finite element magneto-thermal coupling analysis and proposed a new method to calculate the hot spot temperature rise of the structural components of an ODFS-334 MVA/500kV single-phase autotransformer [
9]. Yongjian et al. established a 3D magneto-fluid-thermal coupled model to calculate the temperature rise of a transformer [
10]. Mingyang tested the temperature rise of a single-phase four-column autotransformer under DC bias and established the calculation model for transformer loss and temperature rise [
11].
At the same time, scholars have also performed numerous research studies on multiphysics coupling and established various coupling relationships. Kurt et al. established a strong coupling relationship between the thermal equation and the magnetic equation of the transformer by considering the temperature-dependent heat transfer coefficient and electrical conductivity [
12]. Fabrizio et al. studied the thermal behavior of axial-flux synchronous permanent magnet motors based on coupled electromagnetic and thermo-hydrodynamic models [
13]. At the University of Lyon, Alaa and others proposed a nonlinear dynamic model of magnetic components by coupling the magnetic model and the thermal model to consider the thermal effect [
14]. Haoming calculated the temperature rise of the transformer core tie-plate (TCTP) by the magneto-thermal-fluid weak coupling method [
15]. Bo et al. conducted a corresponding study on the bucking of transformer windings by using the electromagnetic thermal structure coupling method, and simulated the temperature rise and deformation of transformer windings by the finite element method [
16]. Chengcheng proposed a magnetocaloric coupling model based on a 3D magnetic and thermal network to calculate the electromagnetic characteristics and thermal distribution of a permanent magnet claw pole machine. The model has the advantages of fast calculation speed and tight coupling and has been verified [
17]. Mehmet et al. proposed a magneto-thermal coupling analysis method for an axial-flux (AF) permanent-magnet-assisted (PMA) eddy-current brakes (ECB) under high temperature conditions. This method has the advantages of accurately predicting the maximum temperature rise and braking torque changes [
18]. At present, researchers mostly use the one-way coupling method in the calculation of magneto-thermal coupling. This traditional coupling method ignores the temperature influence of the electromagnetic properties of ferromagnetic materials. In the magneto-thermal co-simulation of electrical equipment, the permeability and loss characteristics of electrical steel sheets are closely related to the operating temperature, which in turn will affect the temperature rise distribution of the transformer or motor core. Therefore, the analysis of the magnetic field and the temperature field affects each other, and a coupled calculation is required.
In this paper, the influence of temperature on the permeability and magnetic losses of an electrical steel sheet is measured and analyzed, the anisotropy of an electrical steel sheet considering temperature effect is studied. The magneto-thermal iterative coupling method considering the temperature effect of electrical steel sheets is proposed. The influence of the temperature effect of electrical steel sheets on electromagnetic field and the thermal field coupling simulation results of electrical equipment is discussed.
3. Magneto-Thermal Iterative Coupling Simulation
Coupling field analysis is the analysis of the interaction between two or more engineering physical fields, considering the interaction between different physical fields. The coupling analysis to be discussed in this paper considers the interaction between the electromagnetic field and the temperature field in electromagnetic equipment.
3.1. Iterative Coupling Simulation Method Implementation for the Magnetic Field and Temperature Field
Usually, the coupling analysis of magnetic field and temperature field of a motor or transformer includes the following two steps: first, establish the electromagnetic field analysis model, carry out the magnetic field finite element simulation analysis, and calculate the corresponding loss value; secondly, the loss value obtained through electromagnetic calculation is used as the heat source input of temperature field analysis, and the distribution of temperature field is analyzed. This method is called the traditional magneto-thermal coupling method in this paper. In order to realize fast and accurate temperature rise calculations in engineering practice, the method of electromagnetic field and temperature field coupling simulation proposed in this paper can be summarized as the iterative coupling flow chart shown in
Figure 5.
The magneto-thermal coupling analysis process given in
Figure 5 is an iterative process; that is, in the coupling process of a magnetic field and temperature field, each time the magnetic field calculation is carried out, the relevant properties of the material need to be updated according to the current temperature until the error between the current temperature value and the temperature value calculated in the previous iteration is less than the set value. Electromagnetic loss will affect the distribution of temperature, and temperature changes will change the power loss by affecting the properties of materials. The above iterative coupling system can reflect the coupling effect between the solution results of an electromagnetic field and thermal field. The influence of corresponding temperature on material parameters such as conductivity and permeability can be considered in the next iteration.
In the process of practical problem analysis, there are great difficulties in using experimental research and design calculations. Calculations made according to empirical formulas often cannot meet the needs of temperature rise distribution and local hot spot observation. Therefore, in order to make the calculation results closer to the actual situation, when conducting the coupling analysis of electromagnetic fields and temperature fields for the temperature rise and local overheating of a motor’s or transformer’s structural parts, using relatively mature commercial finite element software has become an analysis method widely used by researchers. In this paper, the ThermNet temperature field simulation software produced by the Infolytica company is used, which can be easily combined with Magnet magnetic field analysis software to realize magnetic thermal coupling analysis.
In the traditional magneto-thermal coupling analysis process without considering the temperature effect, it is generally believed that the magnetic properties of the core material do not change with the temperature change, and the measured B-H, B-P values at 20 °C are given to the core material. The magnetic core model was established by Magnet, and was coupled with ThermNet for calculation and analysis. The distribution results of the magnetic field and temperature field of the core were obtained through simulation.
In the actual operation process, the electromagnetic properties of ferromagnetic materials will change with the change in working temperature. In the process of magneto-thermal coupling, the influence of the change in the magnetic property of the electric steel sheet with temperature shall be considered. The B-H and B-P value measured at different temperatures of 20–200 °C shall be input into the material of core. In this way, during the coupling analysis, the material properties at the corresponding temperatures will be updated according to the calculated different temperatures; that is, the magnetic properties of the core material will be updated continuously during the temperature change process so that the influence of temperature on the magnetic properties of electrical steel plate can be considered during the coupling analysis.
3.2. Coupling Analysis of the Magnetic Field and Temperature Field in a Transformer Core
With the continuous increase in power consumption, the capacity of a single transformer is getting larger and larger. In recent years, ultra-high voltage and large-capacity large power transformers have been put into operation, but the volume and core size of large and extra-large power transformers cannot be increased indefinitely. A single-phase three-limb yoke-pressing transformer is a transformer with a special structure that was developed due to the limitations in transportation conditions. The single-phase transformer has a rated capacity of 241 MVA and a rated voltage of 500/18 kV. The dimensions of the transformer model are 3650 mm × 3850 mm.
Figure 6 shows the main view and side view of this transformer. The upper and lower yokes and side yokes of the yoke-pressing transformer are narrower than those of the ordinary transformer, and the change in the core structure will inevitably affect the relevant performance parameters of the transformer. Therefore, it is necessary to analyze the magnetic field and temperature field of the transformer core. A three-dimensional finite element analysis model was established based on the actual transformer model provided by the transformer manufacturer, as shown in
Figure 7. The coupling analysis of the magnetic field and temperature field was carried out for this yoke-pressing transformer.
When solving the electromagnetic field, because the current of the coil is determined by the voltage applied by the external circuit and the line impedance, the field circuit coupling method of establishing the external circuit of the transformer is also used to calculate the distribution of the magnetic field and loss in the core. The boundary of the temperature field calculation is set in ThermNet, and the heat dissipation boundary is set to 20 W/(m2·°C). The radiation heat dissipation is zero. According to the air convection heat dissipation, the heat dissipation coefficient is assigned to each heat dissipation surface of the core and winding. During the simulation, the transient field is set to 7200 s and a time step of 20 s.
In order to compare and study the influence of the coupling analysis considering the temperature effect of the magnetic properties of the electrical steel sheets on the temperature distribution of the core, this paper uses the traditional magneto-thermal coupling analysis method, and then compares the results with the results obtained by the magneto-thermal bidirectional iterative coupling analysis method.
Figure 8a,b respectively shows the simulation results of the magnetic flux density distribution and temperature distribution of the iron core of the yoke-pressing transformer calculated by the traditional magnetic thermal coupling method without considering the change of the magnetic characteristics of the electrical steel sheet with temperature when the transformer operates under no-load conditions.
From the cloud diagram of magnetic flux density distribution, the maximum value of the magnetic flux density of the one-way yoke-pressing transformer is concentrated at the corner of the yoke, and the distribution of the magnetic flux density is consistent with the actual operation of the transformer. The change in iron core structure makes the magnetic density of iron yoke higher than that of an ordinary transformer, up to 1.72 T, which indicates that after the iron yoke of the transformer is squeezed and narrowed, the effective cross-sectional area of magnetic flux passing through the magnetic circuit becomes smaller, and the size of the magnetic flux flowing through the yoke does not change, so the magnetic flux or magnetic flux density per unit area becomes larger. From the distribution results of the core temperature cloud diagram in
Figure 8b, the parts with higher core temperature are the middle of the core column and the corners of the upper and lower yokes. The temperature of the hottest spot on the core column is about 74 °C, and the temperature of the hottest spot on the upper and lower yokes is about 60 °C.
Figure 9b shows the temperature distribution of the iron core of the yoke-pressing transformer obtained by the simulation calculation considering the magnetic characteristics of the electrical steel sheet changing with temperature. From the cloud diagram of the core temperature distribution given in
Figure 8b, it can be seen that the hottest spot temperature on the core column is about 43 °C, and the hottest spot temperature on the upper and lower yoke is about 38 °C. Compared with the simulation calculation results without considering the temperature effect of the magnetic properties of ferromagnetic materials, the hottest spot temperature of the transformer core is significantly reduced.
Table 2 compares the temperatures in different areas of the core based on the traditional method and the magneto-thermal iterative coupling calculation method, and selects four points, located in the core column and yoke, as shown in
Figure 10.
Because the B-H and B-P curve of electrical steel sheets will change with temperature, bidirectional coupling can continuously update the material properties that change with temperature in the analysis process. The magnetic properties of oriented electrical steel sheets change more obviously with temperature when B is higher than 1 T, and the magnetic flux density of this transformer is up to 1.73 T. Therefore, the temperature change obtained by iterative coupling analysis considering the temperature effect of the magnetic properties of electrical steel sheets is obvious.