France



Introduction:&lt;br/&gt;Nowadays, with the rapid development of the computer science, numerical methods have been widely used during all the design stages of an electrical machine, such as the electromagnetic design, mechanical structure optimization, thermal estimation etc. We may select the main dimension of the motor, according to the existing electromagnetic design scheme of the induction motor with the same power level. This approach is suitable for the conventional induction motor design, because the main performance is highly determined by the main dimension [1]. However, different from traditional induction motors, the water friction losses of wet submersible motors are much greater than the wind mill losses of air-cooled induction motors. As shown in Fig 1, unlike traditional industrial motors, submersible motors have a larger ratio of diameter to shaft Length The water wear of the water-filled submersible motor accounts for a large proportion of the overall losses, so how to reduce the water wear of the submersible motor has become the key to improving the efficiency of the submersible motor.&lt;br/&gt;Many scholars have put forward the numerical calculation method of water wear of water-filled submersible motor, which are shown in Formula (1)-(4) in Figure 2 [2-3]. It can be seen that the main factors affecting the water wear of submersible motors are the surface roughness of the rotor, rotor speed, outer diameter of the rotor and motor shaft length. The literature [4] verified the influence of surface roughness on water wear. For a submersible motor with a given output power, the speed and surface roughness are constant. In this paper, the diameter and shaft length ratio of the motor are optimized to achieve the purpose of reducing the water wear in the design stage.&lt;br/&gt;&lt;br/&gt;Optimization Method:&lt;br/&gt;It can be known from the main relation formula of AC motor that the motor power with constant effective volume of rotor is also approximate. Therefore, keeping the effective volume of the rotor constant, reducing the outer diameter of the rotor and increasing the shaft length can ensure the output power and reduce the water wear of the motor.&lt;br/&gt;However, reducing the water wear through the above methods will also increase the electrical losses of the motor. In this paper, the electrical losses of a series of size motors are solved by electromagnetic simulation, and the curve of electrical losses as a function of the rotor outer diameter is fitted by the cubic spline interpolation. A new curve is obtained by adding the water wear and electrical losses of the motor, and the minimum of the curve is the optimal rotor outer diameter.&lt;br/&gt;&lt;br/&gt;Results:&lt;br/&gt;As shown at point M in Fig.2, when the rotor outer diameter is 0.183 m, the sum of electrical losses and water wear of the motor are the minimum. Compared with the loss when the outer diameter of the rotor is 0.225, the loss is reduced by 360 W. This method realizes the optimization of the diameter-axle-length ratio of the submersible motor and reduces the water wear of the submersible motor in the design stage. Detailed results and discussion will be given in the full text.

**References:**

[1] J. Pyrhonen, T. Jokinen, and V. Hrabovcova. Design of Rotating Electrical Machines, 2nd ed. Hoboken, NJ, USA; wiley, (2014).&lt;br/&gt;[2] S. Li and S. Liu, Pump Technol., vol. 33, pp. 21–25(1988).&lt;br/&gt;[3] H. Liu, M. Tan, and S. Yuan, Trans. Chin. Soc. Agricult. Eng., vol. 22, pp. 107–109(2006).&lt;br/&gt;[4] X. He , W. Jiao , C. Wang , et al. IEEE Access, vol. 7, pp. 105331-105341(2019).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/4e584412cd93d4f18a9970cc97483c8a.jpg)
Fig. 1 A submersible motor with large ratio of diameter to shaft length.

![](https://assets.underline.io/uploads/markdown_image/1/image/ec1237c7417ea9ffc06e457d88d0505b.jpg)
Fig. 2 Losses at different rotor outer diameters.

INTERMAG 2021

 Efficiency Improvement for Submersible Motors by Optimizing the Ratio of Diameter to Shaft Length

INTERMAG 2021 Welcome Video



	
<figure class="video_container">
 <iframe src="https://screencast-o-matic.com/player/crflqFVnUpZ?v=6&ff=1&title=0&controls=1" width=640 height=360 frameborder="0" allowfullscreen="true"> </iframe>
</figure>

Want to buy a ticket? 

Register for INTERMAG 2021 here

[![](https://assets.underline.io/uploads/markdown_image/1/image/17ce76e7960db633258024eef8d6da7f.png)](https://intermag.org/register)

Got your ticket, but still can’t access the event?

Contact us and our team will look into it.

Introduction: Nowadays, with the rapid development of the computer science, numerical methods have been widely used during all the design stages of an electrical machine, such as the electromagnetic design, mechanical structure optimization, thermal estimation etc. We may select the main dimension of the motor, according to the existing electromagnetic design scheme of the induction motor with the same power level. This approach is suitable for the conventional induction motor design, because the main performance is highly determined by the main dimension [1]. However, different from traditional induction motors, the water friction losses of wet submersible motors are much greater than the wind mill losses of air-cooled induction motors. As shown in Fig 1, unlike traditional industrial motors, submersible motors have a larger ratio of diameter to shaft Length The water wear of the water-filled submersible motor accounts for a large proportion of the overall losses, so how to reduce the water wear of the submersible motor has become the key to improving the efficiency of the submersible motor. Many scholars have put forward the numerical calculation method of water wear of water-filled submersible motor, which are shown in Formula (1)-(4) in Figure 2 [2-3]. It can be seen that the main factors affecting the water wear of submersible motors are the surface roughness of the rotor, rotor speed, outer diameter of the rotor and motor shaft length. The literature [4] verified the influence of surface roughness on water wear. For a submersible motor with a given output power, the speed and surface roughness are constant. In this paper, the diameter and shaft length ratio of the motor are optimized to achieve the purpose of reducing the water wear in the design stage. Optimization Method: It can be known from the main relation formula of AC motor that the motor power with constant effective volume of rotor is also approximate. Therefore, keeping the effective volume of the rotor constant, reducing the outer diameter of the rotor and increasing the shaft length can ensure the output power and reduce the water wear of the motor. However, reducing the water wear through the above methods will also increase the electrical losses of the motor. In this paper, the electrical losses of a series of size motors are solved by electromagnetic simulation, and the curve of electrical losses as a function of the rotor outer diameter is fitted by the cubic spline interpolation. A new curve is obtained by adding the water wear and electrical losses of the motor, and the minimum of the curve is the optimal rotor outer diameter. Results: As shown at point M in Fig.2, when the rotor outer diameter is 0.183 m, the sum of electrical losses and water wear of the motor are the minimum. Compared with the loss when the outer diameter of the rotor is 0.225, the loss is reduced by 360 W. This method realizes the optimization of the diameter-axle-length ratio of the submersible motor and reduces the water wear of the submersible motor in the design stage. Detailed results and discussion will be given in the full text.

**References:**

[1] J. Pyrhonen, T. Jokinen, and V. Hrabovcova. Design of Rotating Electrical Machines, 2nd ed. Hoboken, NJ, USA; wiley, (2014). [2] S. Li and S. Liu, Pump Technol., vol. 33, pp. 21–25(1988). [3] H. Liu, M. Tan, and S. Yuan, Trans. Chin. Soc. Agricult. Eng., vol. 22, pp. 107–109(2006). [4] X. He , W. Jiao , C. Wang , et al. IEEE Access, vol. 7, pp. 105331-105341(2019).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/4e584412cd93d4f18a9970cc97483c8a.jpg)
Fig. 1 A submersible motor with large ratio of diameter to shaft length.

![](https://assets.underline.io/uploads/markdown_image/1/image/ec1237c7417ea9ffc06e457d88d0505b.jpg)
Fig. 2 Losses at different rotor outer diameters.

poster

Introduction: Winding loss generally takes a great proportion of the total loss of electrical machines. In many cases, e.g., the high-speed machines excited with high-frequency currents, the effect of the AC loss increases further[1]. Hence, the precise computation of the winding loss is critical in the design optimization process of electrical machines. In a traditional finite element model, the refined mesh is required for each strand, which results in a huge computation burden. To overcome this difficulty, this paper proposed a domain decomposition (DD) type of finite element approach based on the Mortar element method. The linear and nonlinear computation for the inside and outside slot domain is separated and coupled through the interface potentials by the Mortar element method. Therefore, even though a set of uniform refined mesh is generated for each slot domain, the dimension of the nonlinear system is not increased. Then the whole system can be solved efficiently without losing detailed information in each slot. A 37kW permanent magnet assisted synchronous reluctance motor (PM-assisted SynRM) is investigated by the proposed method. The comparison results with traditional FEM proves the feasibility of the presented method for efficient winding loss computation. The proposed DD approach: Fig. 1 (a) and (b) illustrate the topology of the example with divided linear and nonlinear domains, which can be formulated as equations (1) and (2) in Fig. 2. According to Faraday's law of electromagnetic induction, the circuit equation in jth stranded conductor equation is obtained as (3) in Fig. 2. Then the relationship between the stator circuit and the external power supply has the formulation expressed as (4) in Fig. 2 [2]. By Galerkin discretization, the weak formulas (1), (2), (3), and (4) are formed into a strong formulation (5) with non-conforming boundary conditions. Fig. 1 (c) demonstrates the domain division with one single set of slot and tooth in the stator, while other symmetrical stator segments are divided by the same rule. Note that the rotor and air gap of the model belong to the nonlinear domain. The linear domain Ωa and nonlinear domain Ωb mesh independently with non-conforming grids, which means the grids on the boundary are discontinuous. The Mortar element method is adopted to couple the separated domains in the field computation through the information processing on the interface Γ [3]. The node vector potentials belonging to the divide subdomains on Γ have a relationship (6) in Fig. 2 where H and D are line integral of the shape functions over Γ. The unknown potential vector in (5) can be represented in matrix form (9) in Fig. 2 or with a compact form (10). Substitute (10) into the equation (5), i.e., SA=F, the system formula can be expressed as (11) in Fig. 2. We rewrite (11) in the matrix form (12) in Fig. 2. Considering the linear domain in the model, the following relations can be obtained when decoupling the third and fourth rows from the system matrix (13) in Fig. 2. Due to the linearity, the product of left two matrices in the subproblem can be pre-calculated directly. Then (13) is simplified into (14) in Fig. 2. Where the left constant K matrix is the obtained product. Substitute relation (14) into the first row, second row, and fifth row of (12), the matrix or vectors of the system are finally simplified as (15), (16), (17) in Fig. 2, and the final compact system matrix is set up as (18). Finally, since the stiffness matrix in the linear domain can be pre-calculated as a constant, we obtain the values of aout, abnd1, i through the compact system (18) with the Newton Raphson method. The compact system (18) is generally of a lower dimension than the full problem, which means less effort is required for the nonlinear computation. Next, abnd2, ain, ustr are solved from (6) and (13) by using the solutions of the system (18). Although the system (18) matrix is very dense, it is still much faster than solving the whole problem, which is verified from the following simulation case. Numerical example: Fig. 1 (d) and (e) illustrate the mesh diagrams for the traditional FE model (conforming mesh) and DD FE model (non-conforming mesh), respectively. The time-step simulation is performed at speed of 3000 rpm and the motor is power by a sinusoidal voltage source with 350V RMS line voltage and -28.3 load angle. Two simulation models run in Matlab on the same workstation. The total elements in Fig. 1 (d) and (e) are 96234 and 105153, while the nodes, i.e., the unknown node potential amount are 48612 and 53778. By adopting the model reduction process presented above, the number of magnetic vector potentials required for the nonlinear computation is reduced to the node amount in the nonlinear region. For this case, the magnetic potential number of the DD FE model in the nonlinear system is reduced from 53778 to 3506, which is 13 times less than the number (48612) in the traditional model. The computation time of the traditional model and DD model are 38376s and 2834s. The proposed method was more than 13 times faster than the traditional FE. The AC current density map used in the simulations is shown in Fig. 1 (f). Fig. 1 (g) illustrates the AC loss comparison. The good agreement demonstrates the accuracy of the proposed method. Conclusion: The effectiveness of the proposed DD method is verified by the example. Moreover, due to the universality of the model derivation, the proposed method is also applicable to other electrical machines.

**References:**

[1] Pavel Ponomarev, Ilya Petrov, and Nicola Bianchi, “Losses in Stator Slot Windings of Permanent Magnet Synchronous Machines, ” doi:10.13140/RG.2.1.2081.9368, 2015. [2] A. Lehikoinen, N. Chiodetto, and E. Lantto, “Monte Carlo Analysis of Circulating Currents in Random-Wound Electrical Machines,” IEEE Trans. Magn., vol.52, pp.1-12,2016. [3] Orlando Jose Antunes, and J. P. A. Bastos, “Using Hierarchic Interpolation with Mortar Element Method for Electrical Machines Analysis,” IEEE Trans. Magn., vol. 41, pp. 1472-1475, 2005.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/00206775246b05e4a839be2a4dc73dc5.png)
Fig. 1

![](https://assets.underline.io/uploads/markdown_image/1/image/042e81d15cdaf336adcaf2dada7c2d14.png)
Fig. 2

 A Mortar Method Based Domain Decomposition Approach for Winding Loss Computation of Electrical Machines

I. INTRODUCTION Differential evolution (DE) is a powerful evolutionary algorithm that is widely used to solve global optimization problems because of its ease of use, simple structure, efficiency, and robustness. It has been pointed out that the optimization methods, especially of electrical machine designs, are shifting from response surface method toward varieties of DE algorithm [1]–[4]. However, some previous work indicated that DE faces significant difficulty particularly with problems that are not linearly separable [5]. It has been observed that DE sometimes has a limited ability to move its population through large distances across the search space if the population is clustered in a limited portion of it, and in such cases it also has a tendency to find the local rather than global optima due to this lack of movement abilities. Sutton et al. found strong evidence that DE becomes more reliant on differential mutation, and less so on orthogonal steps produced by crossover when the function is non-separable. This paper proposes a hybrid multi-objective optimization method for electrical machines with directed graph (or digraph, DiG) and DE. The proposed method, called DiG-DE, is able to keep the balance of exploration and exploitation in search. The operation of the proposed method is verified, and its performance is compared with that of the standard DE method, for electric machine optimization problem. According to the results, the proposed DiG-DE can solve the problem faster than classic DE. Additionally, for the same computing time, the DiG-DE can always find better candidate designs than classic DE. II. APPLICATION TO ELECTRICAL MACHINE OPTIMIZATION To verify its superiority in terms of optimization for electrical machine design, the proposed DiG-DE is applied to the optimal design of a special modular external rotor switched reluctance motor and compared with classic DE. Fig. 1 displays the fitness of all designs found by classic DE and DiG-DE. From the distribution point of view, the designs found by DiG-DE are more densely distributed near the target Pareto front. All the designs are found by classic DE, but DiG-DE would select those designs that are closer to Pareto front. With the accumulation of selection preferences over time, there is a difference in evolutionary speed. This indicates that the DiG-DE is able to provide higher selective pressure than classic DE. It has been noted that the selective pressure will lead to the loss of diversity. In DiG-DE, the population size of parents is increasing in every generation, and the population grows exponentially, which compensates for this loss of diversity. Fig. 2 shows the candidate designs found by DiG-DE and classic DE for four different solution times. It may be observed that DiG-DE’s solutions are closer to the target Pareto front as compared with the classic DE’s. After a long solution times, the results obtained by the two methods tend to be close. Therefore, there is sufficient evidence to show that the proposed DiG-DE has faster convergence and higher search efficiency than classic DE. III. CONCLUSION In this work, a new algorithm, DiG-DE, based on differential evolution, which uses a digraph to rank candidate designs is proposed and compared with classical DE for electric machine optimization. In contrast with the classic DE approach in which the parents produce the same number of children in every generation, the DiG-DE method shows features that are closer to natural evolution. Under the pressure of selection, the individuals with higher rankings in DiG-DE are more likely to be selected, resulting in more offspring. The conduced comparative studies show that this unique selective scheme gives DiG-DE faster convergence and higher search efficiency than classic DE.

**References:**

[1] Y. Duan, and D.M. Ionel, IEEE Trans. Ind. Appl., vol. 49, p. 1268–1275 (2013). [2] C.T. Krasopoulos, I.P. Armouti, A.G. Kladas, IEEE Trans Magn., vol. 53 (2017). [3] Y. Wang, D. Ionel, D.G. Dorrell, and S. Stretz, IEEE Trans. Magn., vol. 51 (2015). [4] M.E. Beniakar, A.G. Sarigiannidis, P.E. kakosimos, and A.G. Kladas, IEEE Trans. Magn., vol. 50 (2014). [5] S. Das, and P.N. Suganthan, IEEE Trans. Evol. Comput., vol. 15, p. 4–31 (2011).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/bf9eb36c051fe04dc836b61a6297562f.jpg)
Fig. 1 All designs by classic DE and DiG-DE.

![](https://assets.underline.io/uploads/markdown_image/1/image/ba11a4241f17cf8f61d112cfd47d29ce.jpg)
Fig. 2 Solutions of classic DE and DiG-DE computed within (a) 4 hours, (b) 6 hours, (c) 10 hours, and (d) 17 hours.

 A Novel DiG-DE Algorithm for Multi-Objective Design Optimization of Electrical Machine

Urban air mobility (UAM) motors must be designed for light weight and high power density. This is because reducing an aircraft's curb weight increases the aircraft's efficiency and cruising range. UAM motors are basically high torque low speed machines, so they are designed with high poles [1]. The fractional slot structure allows for higher pole numbers with fewer slots and provides a concentrated slot winding, thus reducing the weight of the stator. In addition, the Halbach array rotor can reduce or eliminate back iron cores, thus reducing the weight of the rotor. Therefore, the fractional slot Halbach motor can reduce weight, making it a very suitable for UAM applications. Fig. 1 (a) shows the basic layout of UAM motor, and the design target specifications are as follows: 40-pole 48-slot, DC voltage 600 V, maximum power 50 kW, maximum torque 180 Nm, maximum speed 3 krpm, power density 4 kW/kg. The rotor has a two-segment Halbach array, so only two kinds of magnetization are used: radial and circumferential. The wider the radial magnet, the higher the field density. For this, radial magnets are designed wide and circumferential magnets are narrow. Then the height of the circumferential magnet is not enough to provide complete flux return in the back. The design shown in Fig. 1 (a) has a shallow back iron core at the bottom of permanent magnets (PMs). It supports flux return that is not managed by circumferential PM. Therefore, it is necessary to efficiently determine the ratio of radial to circumferential PMs, and the ratio of magnet to back iron. There are three design variables for optimal design of the rotor. One is the radial magnet coverage ratio α=τr/τp, the other is the PM height ratio δ=hm/hr, the other is the rotor height ratio γ=hr/τp, where τr is the angle for radial magnets, τp is the pole pitch angle, hm is the magnet height, and hr is the rotor height. The design goal is to minimize the weight of the rotor while meeting the output torque requirements. To meet the design requirements in the proposed two-segment Halbach motor, three design variables α, δ, and γ must be found that ensure that wr(γ) is mimimized at the same time Te(α,δ,γ)&gt;180 Nm. Te is the electromagnetic torque and wr is the weight of the rotor. In finite element analysis (FEA)-based design, the number of models to be analyzed increases exponentially as the number of design variables increases. Therefore, FEA design is not suitable for such multivariate optimization. The subdomain can find the optimal design much faster because the result can be obtained by simply changing the design variables. In this paper, the subdomain method was combined with the magnetic equivalent circuit (MEC) analysis to account for the core saturation occurring under load conditions [2]. Fig. 1 (b) shows the domain setup of the subdomain analysis, and (c) shows the MEC model [3]. Fig. 1 (d) shows the airgap flux density compared to the FEA results. It more accurately matches the FEA results when saturation is considered through the MEC. With the combined method, we can find the minimum rotor height ratio γ(α,δ) that satisfies the torque specification Te≥180 Nm, which is shown as dots in Fig. 2 (a). Furthermore, γ(α,δ) can be approximated as a concave function with minimum values at a certain point (α*,δ*) and is: γLSM(α,δ)=p00+p10α+p20α2+p01δ+p11αδ+p02δ2, where pxy is the coefficient of αxδy in γLSM. Be applying the least square method (LSM), we can find the best fitting coefficients. γ≈XP, where P is the matrix of coefficients pxy and X is the matrix of variables α and δ. Let the cost be defined by J=1/2*(γ−XP)T(γ−XP). Then, the cost minimizing solution is obtained as P=(XTX)-1XTγ. The resulting function γLSM(α,δ) with the fitted coefficients are depicted as planes shown in Fig. 2 (a). The minimum point can be found by solving ∂γLSM/∂α=0 and ∂γLSM/∂δ=0, and is obtained such that α*=(2p10p02-p01p11)/(p112-4p20p02), δ*=(2p20p01–p10p11)/(p112-4p20p02). While satisfying the required torque, the minimum rotor height is obtained as γ*=0.37 when α*=0.61 and δ*=0.85. That is, when the rotor height is hr=0.37τp=6.5 mm, the desired torque can be achieved with the minimum rotor weight. Fig. 2 (b) shows rotor weights, and (d) shows an optimized design using the proposed method. To verify the optimized design algorithm, the proposed Halbach motor is compared with SPMSM and a coreless Halbach motor without rotor back irons. For comparison, SPMSM uses the same amount of magnets as the proposed Halbach motor and raises the height of the back iron until it meets the torque specification. For coreless Halbach motors, radial and circumferential magnets are designed to have the same arc according to the existing design. Note that the stator remains the same for accurate comparison. Fig. 2 (d) shows the torque waveform through FEA when Iph=90 Arms. The torque of the proposed Halbach motor is 187.4 Nm, and it has the highest torque. At this time, the rotor weight is 2.54 kg, which has a high power density of 4.17 kW/kg. The SPMSM and coreless Halbach motors have similar torque, but for SPMSM, the rotor height must be increased to 10.5 mm to achieve similar torque levels. Thus, the power density decreases to 3.71 kW/kg.

**References:**

[1] T. F. Tallerico, Z. A. Cameron, and H. Hasseeb, "Outer Stator Magnetically-Geared Motors for Electrified Urban Air Mobility Vehicles," AIAA/IEEE Electric Aircraft Technologies Symposium (EATS), pp. 1-25 (2020) [2] M. Lee, B. Koo and K. Nam, "Analytic Optimization of Halbach Array Slotless Motor Considering Stator Yoke Saturation," in IEEE Trans. on Magn., (2020) [3] S. Wu, X. Zhao, and C. Jiu, "Multi-Objective Optimal Design of a Toroidally Wound Radial-Flux Halbach Permanent Magnet Array Limited Angle Torque Motor," in IEEE Trans. on Ind. Electron., vol. 64, no. 4, pp. 2962-2971 (2017)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/d1fa395a5fcb12da14a7c867c6af6d30.jpg)
(a) A pole pair of Halbach motor model, (b) simplified subdomain model, (c) MEC model, and (d) comparison of airgap flux density.

![](https://assets.underline.io/uploads/markdown_image/1/image/29ff00ba04ee4b43adae646d5bd993fe.jpg)
(a) γ(α,δ) that satisfies Te>180 Nm and fitted curve γLSM(α,δ) using LSM, (b) rotor weights versus δ for different α, (c) flux density of the optimized motor, and (d) torque comparison when Iph=90 Arms.

 Low Weight Halbach UAM Motor Design Based on Subdomain Analysis

1. Induction: The accurate estimation of the harmonic losses caused by the zig-zag leakage flux which occupies a high proportion of stray losses is of great significance in the efficiency calculation as well as the optimization design for the wet submersible induction machine [1]. To precise estimate the zig-zag leakage flux losses at the nominal load, it is necessary to determine losses induced by a particular order of the air-gap flux density harmonic. 2. Analysis and Calculation: In this paper, a two-dimensional finite element method is presented to separate zig-zag leakage flux losses produced by the stator slot harmonic, rotor slot harmonic and interaction harmonic between them, respectively. The air-gap magnetic flux density is decomposed by the two-dimensional fast Fourier transform at a sampling frequency of 5000 Hz. The hybrid excited virtual permanent magnet harmonic machine model is applied to reconstruct the air-gap magnetic field and excited the stator and rotor separately, in which the iron core node magnetic flux density is extracted and decomposed [2]. Each node harmonic iron loss is acquired through the modified Bertotti’s iron loss model with the consideration of high frequency power losses as a function of the magnetic flux density. The losses caused by a single harmonic are obtained by subtracting the losses resulted from the hybrid excitation [3]. Fig. 1(a) shows rotor iron losses density distribution induced by the -17th harmonic, which denotes the first order stator slot harmonic. The rotor is equipped with the closed slot because of the machine’s water-filled operating environment, where the mixed mesh subdivision through triangular mesh and rectangular mesh are employed. It can be seen in Fig. 1(a) that the -17th harmonic penetrates into the rotor surface where the mapped mesh exists. Meanwhile, Fig. 1(b) and Fig. 1(c) display rotor bar and stator winding eddy-current density distributions respectively, where the current density engendered by the -17th harmonic close to the air gap is higher than the rest in other positions. 3. Results: The zig-zag leakage flux losses calculated includes the surface and pulsation losses in the stator and rotor as well as eddy-current losses in the stator winding and squirrel cage. Different proportion of losses caused by corresponding harmonics have important reference for the optimization of the power density of the machine. Table I displays the losses caused by the first and second order stator slot harmonics, together with the first order rotor slot harmonic (-20th and 22nd). In Table I, ‘Nan’ expresses that the corresponding values are small or approach zero. It can be represented that the losses reduce with the order of harmonic, therefore, the iron losses in the stator can be neglected. Meanwhile, the rotor losses generated by the rotor slot harmonic is not listed in the table, because the rotor slot harmonic rotates synchronously with the rotor itself. It can be concluded that the eddy-current losses in the squirrel cage caused by -17th harmonic account for the largest proportion among the overall zig-zag leakage flux losses. Hence, to improve the power density of the machine, effective measures (e.g. rotor skew, semimagnetic wedge) can be taken to reduce the -17th harmonic. The method shown in this paper separates the zig-zag leakage flux harmonic losses and lays a fundamental for the machine design as well as the optimization.

**References:**

[1] R. Hagen, T. Knopik, and A. Binder, IEEE Int. Elect. Mach & Drives Conf., p. 1325-1330 (2009) [2] C. Di, I. Petrov, and J. J. Pyrhönen, IEEE Trans. Magn., Vol. 54, p. 1-12 (2018) [3] C. Di, I. Petrov, and J. J. Pyrhönen, IEEE Access, Vol. 7, p. 27746–27755 (2019)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/c851afdc272d06b04905972692e636a5.jpg)
Fig. 1 Losses density and current density distributions produced by -17th harmonic at the nominal load. (a) Rotor iron losses. (b) Rotor bar eddy-current. (c) Stator winding eddy-current.

![](https://assets.underline.io/uploads/markdown_image/1/image/44204e85ef9b8db76828a38e27b94f87.jpg)
Table I 
Main Harmonic Amplitude and Zig-Zag Leakage Losses

 Calculation and Decomposition of Zig-Zag Leakage Flux Losses in a Wet Submersible Induction Machine by the Virtual Permanent Magnet Harmonic Machine Model

I. INTRODUCTION In recent years, due to the merits of easy thermal management, alleviated torque ripple and robust rotor, flux reversal permanent magnet (FRPM) machines have attracted more and more attention [1]. However, since the large leakage flux leads to the limitation of its output, a series of novel topologies are proposed, such as the consequent-pole FRPM machine [2], the FRPM machine with asymmetric-stator pole configuration [1] and the FRPM machine with Halbach array magnets in rotor slot (HAM-FRPM) [3], etc. This study presents an analytical sub-domain model for the characteristic evaluation of the HAM-FRPM machine. By dividing the HAM-FRPM machine into seven sub-domains and solving the Maxwell equations in polar coordinate for each region according to the boundary conditions, the vector magnetic potential can be obtained. Subsequently, the radial and tangential flux density can be calculated. Finally, the analytical results are compared with the finite element method (FEM) to verify the accuracy. II. ANALYTICAL SUB-DOMAIN MODEL One 12-stator slot/17-rotor tooth HAM-FRPM machine with double-layer winding is investigated in this paper to verify the proposed method. As shown in Fig.1, the permanent magnet (PM) arrangement in the stator of the HAM-FRPM machine is identical to that of the consequent-pole FRPM machine. In addition, the PMs in each rotor slot are the same, which contain a radially magnetized middle PM and two tangentially magnetized side PMs. In this analytical sub-domain modeling, some essential assumptions have been made in advance: (1) The permeability of iron is regarded as infinite. Also, the relative permeability of PMs and coils is assumed to be 1; (2) The end effect and the magnetic field component on the axial direction are neglected; (3) The geometrical structure side of the HAM-FRPM machine is parallel to either r or θ direction in polar coordinate. As shown in Fig. 2, the HAM-FRPM machine is divided into several regions: stator slot (Region i), stator slot opening (Region l and Region u), PM (Region s and Region g), air gap (Region I) and rotor slot (Region j). Maxwell equation is satisfied in each region as equation (1), which can be expressed as a Poisson equation or a Laplace equation and further solved by the separation of variables method. According to the law of magnetic flux continuity and Neumann condition, the unknown coefficients can de derived. Finally, the radial flux density Br and tangential flux density Bθ can be obtained by (2). where J and M are the current density vector and magnetization vector of magnets, respectively. μ0 is the magnetic permeability of vacuum. III. RESULTS AND DISCUSSION The air gap flux density comparisons between the analytical prediction and FEM results are exhibited in Fig.3-4, which present a good agreement between the analytical results and FEM solution for both radial and tangential air gap flux density. Hence, the proposed analytical model is verified to be used to predict the performances of the HAM-FRPM machines. Fig.5-6 show the back-EMF and torque waveforms, which validate the correctness of analytical model. More detailed derivation and analysis will be shown in the full paper.

**References:**

[1] H. Yang, H. Lin, Z. Q. Zhu, S. Lyu, and Y. Liu, "Design and Analysis of Novel Asymmetric-Stator-Pole Flux Reversal PM Machine," IEEE Transactions on Industrial Electronics, vol. 67, no. 1, pp. 101-114, 2020. [2] Y. Gao, R. Qu, D. Li, J. Li, and G. Zhou, "Consequent-Pole Flux-Reversal Permanent-Magnet Machine for Electric Vehicle Propulsion," IEEE Transactions on Applied Superconductivity, vol. 26, no. 4, pp. 1-5, 2016. [3] K. Yang, F. Zhao, Y. Wang, and Z. Bao, "Consequent-Pole Flux Reversal Permanent Magnet Machine with Halbach Array Magnets in Rotor Slot," IEEE Transactions on Magnetics, pp. 1-1, 2020.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/df027abcb712ed2aa1b4402da9ebc363.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/f005d0617e40bdc8495de330aa1bb659.jpg)

 Analytical Modeling for the Flux Reversal Permanent Magnet Machine with Halbach Array Magnets in Rotor Slot

Permanent magnet synchronous motors have become necessary in several industries that develop home appliances, industrial tools, and electrical vehicles; in addition, there is a growing interest in resolving motor malfunctions. Data provided in [1] show that 41% of motor faults are bearing faults, 37% are stator faults, 10% are rotor faults, and 12% are other faults. One of the main causes of malfunction is rotor eccentricity, wherein the center of the rotor axis deviates from the center of the stator, so that the air gap is not uniform. Static eccentricity, a type of rotor eccentricity, is a condition where the position of the minimum radial air gap is fixed [2]. This can be caused by stator core ovality, incorrect positioning of the stator core, or bearing at commissioning or following a repair, and its level does not change over time [3]. As the magnetic flux density in the air gap is an important characteristic of the machine performance [4] [5], the characteristics of the permanent magnet machine and the impact of rotor eccentricity on the magnetic field distribution must be analyzed. Finite element and analytical methods are employed to design a permanent magnet synchronous motor or perform characteristic analysis. The finite element method (FEM) is a numerical process that can be performed using a commercial tool. However, it is necessary to learn to use each commercial tool and have a disadvantage depending on the experience of the designer for accurate analysis. The analytical method analyzed the electromagnetic field characteristics using Maxwell's equation. Magnetization modeling is applied to the design of the machine using the Fourier series and partial differential equations derived using the magnetic vector potential. It must be preceded by deriving a solution that considers various boundary conditions. Several studies are being conducted because the analytical method can quickly predict the characteristic variation according to the design parameters. This study compared electromagnetic characteristics based on rotor eccentricity using the analytical method. Magnetic flux density, induced voltage, and unbalanced magnetic force were derived using the analytical models. The results were verified by experiments and the FEM. Figure 1(a) shows the experimental setup, and Fig. 1(b) shows the manufactured test motors. An experimental setting was constructed to control rotor eccentricity. To measure the back-EMF at the rated speed, a back-to-back system was constructed, wherein one servo motor and one test motor were arranged successively. In addition, the rotor eccentricity was precisely controlled using two gap sensors. The analysis model was simplified based on several assumptions obtained from the analytical method. Based on the electromagnetic field and perturbation theories, the governing equations of the air-gap region were derived. Furthermore, the relationship between the magnetic vector potential in each region and appropriate boundary conditions was used to obtain undefined coefficients to derive magnetic flux density characteristics in each region. Figures 2(a) and (b) exhibit the magnetic flux density derived using the analytical method and the radial and tangential components with a 25% eccentricity ratio. The induced voltage was derived using the magnetic flux density, and Figs. 2(c) and (d) show the comparison of the induced voltages of the 8-pole 12-slot and 8-pole 9-slot models. The induced voltage of the 8-pole 12-slot model was expressed by each branch of winding because of the symmetry of the winding distribution. The induced voltage of the 8-pole 9-slot model differs in magnitude for each of the three phases owing to the asymmetry of the winding distribution. These no-load characteristics affect the load and reduce the life of the machine. The analytical results were validated by comparing the FEM and experimental results. Detailed results, discussions, and desired effects will be presented in the main paper.

**References:**

[1] J. R. Cameron, W. T. Thomson, and A. B. Dow, “Vibration and current monitoring for detecting airgap eccentricity in large induction motors,” Proc. IEE Electr. Power Appl. B, vol. 133, no. 3, pp. 155–163, May 1986. [2] Q. Zhu, D. Howe, E. Blote, and B. Ackermann, “Instantaneous magnetic field distribution in brushless permanent magnet DC motors, Part I: Open-circuit field”, IEEE Trans. Magn., vol 29, pp. 124-135, Jan. 1993. [3] U. Kim and D. K. Lieu, “Magnetic field calculation in permanent magnet motors with rotor eccentricity: Without slotting effect”, IEEE Trans. Magn., vol. 34, no. 4, pp. 2242-2252, Jul. 1998. [4] A. Rahideh and T. Korakianitis, “Analytical open-circuit magnetic field distribution of slotless brushless permanent magnet machines with rotor eccentricity”, IEEE Trans Magn., vol 47, no. 12, pp. 4791-4808, Jun. 2011. [5] U. Kim and D. K. Lieu, “Effects of magnetically induced vibration force in brushless permanent magnet motors ”, IEEE Trans. Magn., vol. 41, no. 6, pp. 2164-2172, Jun. 2005.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2d03b030413a889b83baf91d5cbce4f7.jpg)
Fig. 2. Electromagnetic characteristic according to rotor eccentricity: (a) radial flux density, (b) tangential flux density, (c) induced voltage of 8-pole 12-slot model, and (d) induced voltage of 8-pole 9-slot model.

![](https://assets.underline.io/uploads/markdown_image/1/image/635b8854d507f44663db24dca5394364.jpg)
Figs. 1. (a) Experimental setup, and (b) manufactured test motor.

 Analytical Study and Comparison of Electromagnetic Characteristics of 8-Pole 9-Slot and 8-Pole 12-Slot Permanent Magnet Synchronous Machines According to Rotor Eccentricity

Permanent magnet machines are now-a-days very popular in electric traction applications requiring a wide constant-power speed range. However, the field weakening action, necessary in higher speeds creates important air gap field distribution distortion and increased losses leading to particular configurations search, such as conjunction with variable reluctance rotors [1], pole shoe configurations [2], flat embedded magnet topologies [3], convenient stator windings and permanent magnet arrangements [4], axial flux topologies [5]. In the present paper a convenient configuration of stator windings in permanent magnet motors is proposed involving appropriate additional end winding magnetic circuits in order to achieve inductance management. Such a technique can be applied in all permanent magnet motor configuration cases and enables increased flux weakening capability in high rotor speeds, resulting in substantial efficiency improvements. The optimal design of these extra iron cores can be modeled by adopting a particular reduced scalar potential formulation and the resulting finite element model can be facilitated considering appropriate two dimensional configurations. The overall analysis is performed through co-simulation of the additional magnetic circuits simultaneously with the permanent magnet synchronous machine active part. The proposed methodology enables appropriate handling of increased flux weakening effects in traditional surface mounted permanent magnet motors. It exploits the end zone part of the windings, which does not contribute in the machine torque and performance. The main concept involves introduction of convenient magnetic circuits in the end zone parts of stator coils. These magnetic circuits enable magnetic coupling with auxiliary windings which are connected to appropriate varistors and are energized in desired electromotive force values developed at specific speed ranges through convenient selection of turns ratios. The magnetic material proposed for the additional magnetic circuits is a particular Ferrite ensuring low losses in order not to compromise the machine efficiency. Moreover, the increase of the stator windings leakage inductance is reduced when the auxiliary windings are not energized and is greatly increased when the varistors are activating them. The representation of such configurations necessitates in general a 3D finite element modeling of the whole machine, which is very demanding in computational means. However, an important reduction in computation requirements can be achieved by adopting an appropriate reduced scalar potential formulation, involving one unknown per node. A further calculation simplification can be obtained by implementing an appropriate two dimensional axisymmetric representation for the additional magnetic circuits in conjunction with a two dimensional Cartesian representation of the motor active part and by adopting a direct coupling of field and circuit equations [6]. The methodology developed has been applied in a permanent magnet synchronous machine case with surface permanent magnet rotor configuration and rated power of 100 kW. The motor end winding geometry for one pole part illustrating the additional ferrite toroidal magnetic circuits positioning is shown in Fig. 1. The obtained efficiency maps in cases without and with the additional magnetic circuits are shown in Figs. 2a and 2b, respectively, illustrating the important efficiency improvement resulting in high speed ranges. It may be noted that the proposed technique can offer great services in field weakening action and respective efficiency improvements at high speed ranges of all permanent magnet machine configurations implemented in electric traction applications.

**References:**

 [1] C. Tang, W.L. Soong, T.M. Jahns, et al., IEEE Transactions on Industry Applications, Vol. 51, p.3761 (2015) [2] N. Zhao and N. Schofield, IEEE Transactions on Magnetics, Vol. 53, p. 8112607 (2017) [3] S. Chaithongsuk, B. Nahid-Mobarakeh, J.P. Caron et al., IEEE Transactions on Industrial Electronics. Vol. 59, p.2484 (2012) [4] M.S. Toulabi, J. Salmon and A.M. Knight, IEEE Transactions on Industry Applications, Vol. 53, p.1892 (2015) [5] A. Hemeida, M. Taha, A. Abdallh, et al., IEEE Transactions on Energy Conversion, Vol. 32, p.111 (2017) [6] E. Karamanis and A. Kladas, 2020 International Conference on Electrical Machines (ICEM), p.332 (2020).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/f741435f33fa0354a4568d7a094b7f78.jpg)
Fig. 1 Stator windings end zone geometry of one pole part of the machine illustrating the additional magnetic circuits positioning.

![](https://assets.underline.io/uploads/markdown_image/1/image/df6370cc71b7cdd695a934844fa86ae8.jpg)
Fig. 2 Efficiency maps of the permanent magnet motor in cases (a) without additional end winding magnetic circuits (b) with additional end winding magnetic circuits.

 Particular Reduced Scalar Potential Formulation for End Winding Magnetic Circuits modeling enabling increased Field Weakening in PM motors

Introduction: Time-step finite element method is widely used in the transient simulation because the harmonic of magnetic fields and the nonlinear characteristics of the material can be processed simultaneously [1]. However, the steady-state solution of the transient simulation convergence slowly due to the time constant characteristic in field-circuit coupling computation [2-3]. Aiming at this problem, this paper proposes an acceleration method based on the estimation of initial values in time step simulation by time harmonic analysis. With the precalculated initial solution, the iteration steps for each point calculation and time for convergence to the steady state are effectively saved. Meanwhile, the advantages of the traditional time step method are well retained. A permanent magnet assisted synchronous reluctance motor (PM-assisted SynRM) is investigated by the proposed method. The comparison results with traditional FEM demonstrate the effectiveness of the proposed method in reducing the iterations step for searching a steady-state solution in the transient simulation. The proposed approach: Firstly, the governing equation for the electromagnetic field can be formulated as equation (1) in Fig. 1. The problem formula also includes the following two equations (2) and (3) in Fig. 1, which describe the connection of the circuit. We can establish field-circuit coupling equations through (1), (2), and (3). Secondly, in time-harmonic analysis, time dependence can be eliminated from the equations by using complex field quantities (4) in Fig. 1. By Galerkin discretization in time-harmonic, the weak formulas (1) and (3) are formed into (5) and (6) in Fig.1. The complex system of equations can be written in the matrix form (7), (8), (9), and (10) in Fig.1. Newton's method is adapted for the nonlinear solution. Taylor expansion is applied to the Jacobian matrix as (11) and (12) in Fig.1 to satisfy the Cauchy-Riemann differential equations. The unknown vector in the time-harmonic simulation is then solved by (13) in Fig. 1 iteratively and only a small number of steps is required for convergence. In the harmonic analysis, the vector potential a can be described as a periodic function in Fig1. (14). The achieved time-harmonic solution is then transferred into the time domain system (16) according to (15) as the initial value at t =0s. Since the time-harmonic simulation results are very close to the steady-state solution in the transient simulation, the iteration for each time-stepping solution can be fast with fewer steps than the traditional method. Also, the time step required for convergence to the steady-state is shortened further. Thereby the total calculation time significantly reduced. The effectiveness of the presented method is verified by the following simulation case. Numerical example: Fig. 2 (a) illustrates the mesh diagrams for the FE model of the PM-assisted SynRM. The time-step simulation is performed at a frequency of 100Hz, and the motor is power by a sinusoidal voltage source with 350V RMS line voltage and -28.3 load angle. Two simulation models run in Matlab on the same workstation. The total cost for the 0.3s simulation of the traditional time-stepping method and the proposed method is 58 mins and 16 mins, respectively. As shown in Fig. 2 (b), the simulation convergence to steady-state at 0.15s, and the corresponding computation cost is 8.5 mins, which means the proposed method is 6 time faster. The good agreement of both methods in steady-state torque calculation in Fig. 2 (b) also demonstrates the accuracy of the proposed method. Conclusion: The effectiveness of the proposed method is verified by the PM-assisted SynRM example. Moreover, due to the universality of the model derivation, it is also applicable to other electrical machines e.g. induction machines.

**References:**

[1] Shinji Wakao, Masato Tokuhisa, and Atsushi Maeda, “ Acceleration of convergence characteristics of time-stepping FE analysis for rotating machines,” IEEE Trans. Magn., vol.37, no.5, pp. 3558–3561, 2001. [2] W. N. Fu, S. L. Ho, and Ping Zhou, “Reduction of computing time for steady-state solutions of magnetic field and circuit coupled problems using time-domain finite-element method,” IEEE Trans. Magn., vol. 48, no. 11, pp. 3363–3366, 2012. [3] Oszkár Bíró and Kurt Preis, “An efficient time-domain method for nonlinear periodic eddy current problems,” IEEE Trans. Magn., vol. 42, no. 4, pp. 695–698, 2006.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/bf560494131098c95568658e4ce25e3f.png)
Fig. 1

![](https://assets.underline.io/uploads/markdown_image/1/image/e07e77a8a3291152aeff66b33318b170.jpg)
Fig. 2

 An Acceleration Method for Reaching Steady-State Performance in Time-stepping Finite Element Analysis

I. Introduction Axial flux permanent magnet (AFPM) machines are getting popularity in various applications. Due to the complex structure of the AFPM machine, 3 dimensional finite element analysis (3D FEA) is normally employed [1]. In order to save the computation time, several 2D FE modelling approaches have been adopted and studied by researchers. 2D linear motor approach (LMMA) is commonly used not only in the performance calculation but also in the analytical study [2]. 2D inner rotor modelling approach (IRMA) and 2D outer rotor modelling approach (ORMA) are proposed and compared with LMMA in [3]. Generally, 2D FE modelling approaches use the geometrical parameters at the average radius of the machine. Considering the variation of geometrical parameters along radial direction, geometrical parameters at different radius are taken into account by the multi-layer 2D FE modelling approaches [3, 4]. However, errors are still existed between the results gotten by 2D FEA and 3D FEA. In order to shorten the computation time and to ensure the accuracy, a 3D FE modeling approach based on scaling air gap method is proposed in this paper. II. The Principle of the Scaling Air Gap Method Basing on the expression of reluctance, the changing of geometrical parameters of an element can be balanced by the adjustment of its relative permeability. In the 3D FE modelling of an AFPM machine, the resizing of the air gap has no influence on the sizes of the other parts. It provides an opportunity to customize the air gap with equivalent relative permeability. If the air gap length is scaled to k (k＞1) times, its relative permeability in axial direction should be adjust to k times and its relative permeability in circumferential and radial direction should be adjust to 1/k times. The electromechanical energy conversion happens in the air gap, so the meshing of the air gap region is very important. Sometimes the air gap may be over meshed due to its small dimension. At this time, the scaling air gap method provides a way to reduce the number of meshes and to refine the meshing quality. III. Comparison among FEA Approaches and Experiments All the 2D and 3D FEA approaches for AFPM machines are implemented to a double-stator single-rotor AFPM machine. In this paper, we focus on the computation time and accuracy of motor performance including back electromotive force (EMF), torque output, and torque ripple. All the 2D FEA is based on multi-layer model to consider the variation of geometrical parameters at different radii. In order to make the study comprehensive, motors with different slot-pole combinations and magnet shapes are employed. Taking a 30-pole 36-slot motor with fan-shape magnets as an example, the comparison based on mesh profile and computation time are presented in Table 1. The comparison of motor performance is shown in Figure 1. It illustrates that all the 2D FEA approaches have advantages in the computation time, but there is a decrease in accuracy. The proposed 3D FEA approach based on scaling air gap method can reduce the computation time with good accuracy compared with the traditional 3D FEA approach. For further verification of the proposed method, a prototype is manufactured and tested. IV. Conclusions A 3D FE modelling approach for calculating AFPM machines based on scaling air gap method is proposed in this paper. The axial length and relative permeability of the air gap can be changed based on the scaling air gap method. In this way, the mesh setting for the air gap will be more flexible and the mesh of the whole machine can be adjusted to be more reasonable. The proposed approach is proved to have shorter computation time than the traditional 3D FEA approach and to be more accurate than 2D FEA approaches. The accuracy of the proposed approach is also verified by experiments.

**References:**

[1] S. H. Won, J. Choi, and J. Lee, "Axial-Gap Type Permanent Magnet Motor Modeling for Transient Analysis," IEEE Trans. Magn., vol. 44, no. 11, pp. 4085-4088, Nov. 2008. [2] F. Zhao, T. A. Lipo, and B. Kwon, "A Novel Dual-Stator Axial-Flux Spoke-Type Permanent Magnet Vernier Machine for Direct-Drive Applications," IEEE Trans Magn., vol. 50, no. 11, pp. 1-4, Nov. 2014. [3] M. Gulec, M. Aydin, "Implementation of different 2D finite element modelling approaches in axial flux permanent magnet disc machines," IET Electr. Power Appl., vol. 12, no.2, pp. 195-202, 2018. [4] C. Bianchini, F. Immovilli, E. Lorenzani, etc., "Axial flux permanent magnet machine desing and optimization using multi-layer 2-D simulation," in Proc. Ann. Conf. Ind. Electron. Soc., 2013, pp. 2620-2625.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2dc32f60a9d925a176112f4245eb869d.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/6097f8bf03832bd974868f3cf2ed1994.jpg)

 A Novel 3D Finite Element Modelling Approach for Calculating Axial Flux Permanent Magnet Machines Based on Scaling Air Gap Method

This paper proposes an equivalent magnetic network (EMN) model for predicting the electromagnetic performances of hybrid excitation machines. In addition to the influence of flux leakage and iron saturation, the proposed EMN model also takes the change of rotor position into consideration. A new node connection method is proposed to make the dynamic analysis easier. Moreover, the reasonable simplification of stator yoke and teeth further reduces the calculation time and ensures the accuracy of the proposed EMN model.In addition, the proposed model in the motor hybrid excitation part can consider the electromagnetic characteristics under different DC excitation conditions. Finally, the prototype is manufactured, and the effectiveness of the EMN model is verified by comparison with the finite-element analysis (FEA) and experimental tests. I.Introduction Hybrid excitation machines not only has many advantages of permanent magnet machine, but also has the advantages of smooth and adjustable air gap magnetic field, wide speed range in electric operation, and wide voltage regulation ability in power generation operation [1]. Therefore, it has received a lot of attention from scholars. In order to analyze the performance of the machine, the finite-element analysis (FEA) method is usually used [2]. However, the hybrid excitation machine is a three-dimensional magnetic circuit structure, which requires a large number of grids, which is very time-consuming. In order to reduce the calculation time, the analytical method is also used to reveal the machine performance [3]. However, the effect of iron saturation is mostly considered, resulting in low accuracy. The equivalent magnetic network method has attracted more and more attention due to its short calculation time and moderate accuracy. In this paper, a dynamic magnetic network analysis model is proposed to predict the electromagnetic performance of consequent pole hybrid excitation machines. The EMN model considers the magnetic flux leakage, the nonlinearity saturation of iron materials and the magnetic bridge, which has high calculation accuracy. The calculated results are compared with the FEA and experimental test results. II.PROPOSED EMN MODEL FOR HYBRID EXCITATION MACHINES Generally, the yoke and tooth magnetic circuit of the machine is regular, and the Simplified EMN modeling method can be used to establish the model. However, the tooth tip, air gap and magnetic bridge magnetic circuit are irregular, and complex magnetic network needs to be established to improve the accuracy and be used for dynamic analysis. At the same time, the DC excitation source should be considered when the hybrid excitation motor is built for three-dimensional magnetic circuit. Figure 1 shows the topology of the machine. The following is a brief introduction to the modeling process: A.Simplified Stator EMN Model The magnetic circuit of the yoke and teeth of the stator is regular. Therefore, a simplified stator EMN model can be used to reduce the calculation time without affecting the accuracy requirements. B. Air Gap EMN Model and Dynamic Analysis The tooth tip of the machine is seriously saturated due to the quasi-closed slot. It is necessary to consider the influence of saturation in order to establish the cross-shaped mesh model. The air gap is the key part of the model, which connects the stator and the rotor. In the dynamic analysis, the stator and rotor depend on the air gap EMN model node connection. It is important to consider the rotor position change with time for the dynamic analysis. Therefore, it is necessary to build cross-shaped mesh model in the air gap. This makes dynamic analysis more effective and faster. C. EMN Model of Rotor and Hybrid Excitation Part When modeling the rotor part, the saturation of the magnetic bridge part is serious, and the cross-shaped mesh model needs to be established. Under the influence of DC excitation, the iron-pole generates magnetic field in the hybrid excitation section of the machine. The permanent magnet and DC magnetic source can be considered separately in the modeling to avoid the complex situation caused by two magnetic sources in the model. It should be noted that the alternating existence of permanent magnet and iron-pole also makes the modeling difficult. III.Results Verification In order to verify the effectiveness of the proposed EMN model, a hybrid excitation machine prototype is developed. The experimental test platform is shown in Fig. 2. The electromagnetic performances, such as the air-gap field distribution, phase flux linkage and back-electromotive force (EMF), d-axis and q-axis inductances, and electromagnetic torque, are predicted by the proposed EMN method. Finally, the results obtained from the EMN method are the compared with those obtained by the FEA and experimental tests. IV.CONCLUSIONS In this paper, an equivalent magnetic network analysis model is proposed to predict the electromagnetic performance of hybrid excitation machine. The new node connection form is established in the tooth tip and air gap for considering dynamic analysis. The proposed EMN model considers the influence of flux leakage and Nonlinear saturation of iron materials. The calculated results are compared with the FEA and experimental test results, which proves the effectiveness of the proposed EMN model. The detailed modeling process and calculation results will be given in the full paper.

**References:**

 [1] Z. Q. Zhu, I. A. A. Afinowi, and Y. Guan, “Hybrid-Excited Stator Slot Permanent Magnet Machines—Influence of Stator and Rotor Pole Combinations,” in IEEE Transactions on Magnetics, vol. 52, no. 2, pp. 1-10, Feb. 2016, Art no. 8100710. [2] K. Wang, J. Li, and C. Liu, “Novel hybrid-pole rotors for consequent-pole PM machines without unipolar leakage flux,” IEEE Trans. Ind. Electron., vol. 66, no. 9, pp. 6811–6823, Sep. 2019. [3] S. G. Min, and B. Sarlioglu, “Fast and systematic design optimization of surface-mounted PM machines using advanced analytical models and subharmonic elimination methods,”IEEE Trans. Magn., vol. 55, no. 1, Jan. 2019, Art. no. 8100216.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b80f9b7b361e759844d752bbbfdd52dc.jpg)
Fig. 1. Topology of hybrid excitation machine. (a) Topology of stator. (b) Topology of rotor.

![](https://assets.underline.io/uploads/markdown_image/1/image/bb6ec34b1f0fdd2d048e55985615523c.jpg)
Fig.2.Test platform of a hybrid excitation prototype.

Efficiency Improvement for Submersible Motors by Optimizing the Ratio of Diameter to Shaft Length

Next from INTERMAG 2021

A Mortar Method Based Domain Decomposition Approach for Winding Loss Computation of Electrical Machines

Similar lecture

Crossover of magnetization reversal mode with thickness and diameter in shape-anisotropy magnetic tunnel junctions

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES