France



I.Introduction&lt;br/&gt;Switched reluctance motors (SRMs) inherently have the advantages of simple structure, no mechanical friction, flexible control and long service life so that they have a good application prospect in hybrid electric vehicle, military and rail transit. Bearingless switched reluctance motors (BSRMs) combine the merits of SRMs and magnetic bearings. However, in the traditional BSRMs, double windings are wound on the stator poles to produce suspension force and torque at the same time. It leads to a problem of nonlinear strong coupling between the torque flux and suspension flux. Therefore, a novel three-pole BSRM is presented, which produces torque and radial controllable suspension force. Each torque pole is designed to be two poles in the axial direction, and suspension poles can be designed larger. The torque poles take up less radial space of the stator in order to increase the radial suspension force density. Firstly, the configuration and suspension principle of the novel BSRM are introduced. Then, the mathematical model of radial suspension force calculation is presented by means of equivalent magnetic circuit. Finally, according to the main parameters of the BSRM, the air-gap magnetic fields and radial suspension forces are analyzed by MagNet 3D. The research results verify the performance of the proposed BSRM.&lt;br/&gt;II.Configuration and Suspension Principle&lt;br/&gt;According to Fig.1, the proposed BSRM consists of two pieces of stator cores with six stator poles, two rotor cores with six rotor poles and two radial magnetized permanent magnets. The stator poles can be divided into torque poles and suspension poles. Different from conventional BSRM, the torque poles are designed to place axially, the width of rotor pole and torque pole is designed to be equal, the width of suspension pole is designed to be larger than that of the rotor pole. Therefore, there is always a rotor pole under the suspension pole when the rotor is rotating. Radial suspension control flux is generated by radial control current, and the bias flux is generated by two permanent magnets, which form a close path through two stator cores and two rotor cores. Torque flux passes through the torque poles, air gaps and rotor poles, which is separated from the control flux. The paths of suspension flux and torque flux are separated. The torque and suspension force are decoupling naturally.&lt;br/&gt;Based on the equivalent magnetic circuit analysis, the mathematical models of suspension force are deduced. The radial suspension force can be written as&lt;br/&gt;&lt;i&gt;F&lt;sub&gt;j&lt;/sub&gt;&lt;/i&gt;=&lt;i&gt;F&lt;sub&gt;pm&lt;/sub&gt;&lt;/i&gt;+&lt;i&gt;k&lt;sub&gt;ij&lt;/sub&gt;&lt;/i&gt;×&lt;i&gt;ij&lt;/i&gt;&lt;br/&gt;where the subscript “&lt;i&gt;j&lt;/i&gt;” denotes A, B and C. &lt;i&gt;F&lt;sub&gt;pm&lt;/sub&gt; &lt;/i&gt;is the magnetic attraction force produced by the bias flux at the equilibrium position. &lt;i&gt;k&lt;sub&gt;ij&lt;/sub&gt;&lt;/i&gt; is the radial force-current stiffness.&lt;i&gt; F&lt;sub&gt;m&lt;/sub&gt;&lt;/i&gt; and &lt;i&gt;k&lt;sub&gt;ij&lt;/sub&gt; &lt;/i&gt;can be given as&lt;br/&gt;&lt;i&gt;F&lt;sub&gt;pm&lt;/sub&gt;&lt;/i&gt;=&lt;i&gt;S&lt;/i&gt;×&lt;i&gt;μ&lt;sub&gt;0&lt;/sub&gt;&lt;/i&gt;×&lt;i&gt;F&lt;sub&gt;m&lt;/sub&gt;&lt;/i&gt;×&lt;i&gt;F&lt;sub&gt;m&lt;/sub&gt;&lt;/i&gt;÷(4&lt;i&gt;g&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;)&lt;br/&gt;&lt;i&gt;K&lt;sub&gt;ij&lt;/sub&gt;&lt;/i&gt;=&lt;i&gt;S&lt;/i&gt;×&lt;i&gt;μ&lt;sub&gt;0&lt;/sub&gt;&lt;/i&gt;×&lt;i&gt;F&lt;sub&gt;m&lt;/sub&gt;&lt;/i&gt;×&lt;i&gt;N&lt;/i&gt;÷(2&lt;i&gt;g&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt;)&lt;br/&gt;where &lt;i&gt;μ&lt;/i&gt;&lt;sub&gt;0&lt;/sub&gt; is vacuum permeability. &lt;i&gt;S&lt;/i&gt; is radial magnetic pole area. &lt;i&gt;g &lt;/i&gt;is radial air gap length. &lt;i&gt;N&lt;/i&gt; is number of radial control coils.&lt;br/&gt;III.Models, Design and Analysis&lt;br/&gt;To analyze the electromagnetic performance of the proposed three-pole BSRM, including magnetic flux distribution and the force-current relationships, the software MagNet is used to build the finite element model. The simulation results are shown in Fig. 2. Fig. 2(a) shows the bias flux distribution of the proposed BSRM. When the rotor is located in the balance position, the air gap bias flux density under three suspension poles is equal. Fig. 2(b) shows the control flux distribution when the maximum suspension force in the X direction is generated .The reluctant flux distribution is shown in Fig. 2(c) and Fig. 2(d). In Fig. 2(c), it can be seen that the air gap flux density increases under pole A and decreases under pole B and pole C, resulting in a suspension force pointing to the positive X direction. Fig. 2(d) shows another case of the reluctant flux distribution. The air gap density increases under pole B and decreases under pole C. It leads to the suspension force pointed to the positive Y direction. Therefore, the correctness of magnetic circuit and suspension mechanism is proved.&lt;br/&gt;The relationship between the control current and radial suspension force &lt;i&gt;F&lt;sub&gt;x&lt;/sub&gt; &lt;/i&gt;and &lt;i&gt;F&lt;sub&gt;y&lt;/sub&gt;&lt;/i&gt; can be calculated. Comparison between the simulation value and theoretical value is shown in Fig. 2(e) and Fig. 2(f). In Fig. 2(e), the suspension force in the X direction is produced, when the current changes from 0 to 3 A. When the control current changes from 0 to 3 A, the force-current relationship is shown in Fig. 2(f). Based on the above analysis, the correctness of the mathematical model is proved. Fig. 2(g) shows the fluctuation suspension force &lt;i&gt;F&lt;sub&gt;x&lt;/sub&gt; &lt;/i&gt;and &lt;i&gt;F&lt;sub&gt;y&lt;/sub&gt;&lt;/i&gt;. It can be seen that the force is stable in the rotating condition.&lt;br/&gt;IV.Conclusion&lt;br/&gt;This paper presents a novel three-pole BSRM with independent torque and suspension force magnetic circuit. The theory analysis and simulation results are verified the electromagnetic performance of the proposed BSRM.

**References:**

[1]J. Ju, H. Zhu and C. Zhao, &quot;Radial Force-Current Characteristic Analysis of Three-Pole Radial-Axial HMB,&quot; &lt;i&gt;2016 IEEE Vehicle Power and Propulsion Conference (VPPC)&lt;/i&gt;, Hangzhou, 2016, pp. 1-6.&lt;br/&gt;[2]R. Zhu, W. Xu, C. Ye, J. Zhu, G. Lei and X. Li, &quot;Design Optimization of a Novel Heteropolar Radial Hybrid Magnetic Bearing Using Magnetic Circuit Model,&quot; in &lt;i&gt;IEEE Transactions on Magnetics&lt;/i&gt;, vol. 54, no. 3, pp. 1-5, March 2018, Art no. 8201105.

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INTERMAG 2021

 Suspension Characteristics for a Novel Three-pole Bearingless Switched Reluctance Motor

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I.Introduction Switched reluctance motors (SRMs) inherently have the advantages of simple structure, no mechanical friction, flexible control and long service life so that they have a good application prospect in hybrid electric vehicle, military and rail transit. Bearingless switched reluctance motors (BSRMs) combine the merits of SRMs and magnetic bearings. However, in the traditional BSRMs, double windings are wound on the stator poles to produce suspension force and torque at the same time. It leads to a problem of nonlinear strong coupling between the torque flux and suspension flux. Therefore, a novel three-pole BSRM is presented, which produces torque and radial controllable suspension force. Each torque pole is designed to be two poles in the axial direction, and suspension poles can be designed larger. The torque poles take up less radial space of the stator in order to increase the radial suspension force density. Firstly, the configuration and suspension principle of the novel BSRM are introduced. Then, the mathematical model of radial suspension force calculation is presented by means of equivalent magnetic circuit. Finally, according to the main parameters of the BSRM, the air-gap magnetic fields and radial suspension forces are analyzed by MagNet 3D. The research results verify the performance of the proposed BSRM. II.Configuration and Suspension Principle According to Fig.1, the proposed BSRM consists of two pieces of stator cores with six stator poles, two rotor cores with six rotor poles and two radial magnetized permanent magnets. The stator poles can be divided into torque poles and suspension poles. Different from conventional BSRM, the torque poles are designed to place axially, the width of rotor pole and torque pole is designed to be equal, the width of suspension pole is designed to be larger than that of the rotor pole. Therefore, there is always a rotor pole under the suspension pole when the rotor is rotating. Radial suspension control flux is generated by radial control current, and the bias flux is generated by two permanent magnets, which form a close path through two stator cores and two rotor cores. Torque flux passes through the torque poles, air gaps and rotor poles, which is separated from the control flux. The paths of suspension flux and torque flux are separated. The torque and suspension force are decoupling naturally. Based on the equivalent magnetic circuit analysis, the mathematical models of suspension force are deduced. The radial suspension force can be written as Fj=Fpm+kij×ij where the subscript “j” denotes A, B and C. Fpm is the magnetic attraction force produced by the bias flux at the equilibrium position. kij is the radial force-current stiffness. Fm and kij can be given as Fpm=S×μ0×Fm×Fm÷(4g2) Kij=S×μ0×Fm×N÷(2g2) where μ0 is vacuum permeability. S is radial magnetic pole area. g is radial air gap length. N is number of radial control coils. III.Models, Design and Analysis To analyze the electromagnetic performance of the proposed three-pole BSRM, including magnetic flux distribution and the force-current relationships, the software MagNet is used to build the finite element model. The simulation results are shown in Fig. 2. Fig. 2(a) shows the bias flux distribution of the proposed BSRM. When the rotor is located in the balance position, the air gap bias flux density under three suspension poles is equal. Fig. 2(b) shows the control flux distribution when the maximum suspension force in the X direction is generated .The reluctant flux distribution is shown in Fig. 2(c) and Fig. 2(d). In Fig. 2(c), it can be seen that the air gap flux density increases under pole A and decreases under pole B and pole C, resulting in a suspension force pointing to the positive X direction. Fig. 2(d) shows another case of the reluctant flux distribution. The air gap density increases under pole B and decreases under pole C. It leads to the suspension force pointed to the positive Y direction. Therefore, the correctness of magnetic circuit and suspension mechanism is proved. The relationship between the control current and radial suspension force Fx and Fy can be calculated. Comparison between the simulation value and theoretical value is shown in Fig. 2(e) and Fig. 2(f). In Fig. 2(e), the suspension force in the X direction is produced, when the current changes from 0 to 3 A. When the control current changes from 0 to 3 A, the force-current relationship is shown in Fig. 2(f). Based on the above analysis, the correctness of the mathematical model is proved. Fig. 2(g) shows the fluctuation suspension force Fx and Fy. It can be seen that the force is stable in the rotating condition. IV.Conclusion This paper presents a novel three-pole BSRM with independent torque and suspension force magnetic circuit. The theory analysis and simulation results are verified the electromagnetic performance of the proposed BSRM.

**References:**

[1]J. Ju, H. Zhu and C. Zhao, "Radial Force-Current Characteristic Analysis of Three-Pole Radial-Axial HMB," 2016 IEEE Vehicle Power and Propulsion Conference (VPPC), Hangzhou, 2016, pp. 1-6. [2]R. Zhu, W. Xu, C. Ye, J. Zhu, G. Lei and X. Li, "Design Optimization of a Novel Heteropolar Radial Hybrid Magnetic Bearing Using Magnetic Circuit Model," in IEEE Transactions on Magnetics, vol. 54, no. 3, pp. 1-5, March 2018, Art no. 8201105.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2ebd4d829e367720548b33bc78b6d169.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/d10611797b80ff80963b76415555085a.jpg)

poster

1.Introduction In recent years, the demand for highly efficient motors is increasing to reduce energy consumption due to the increase in energy cost. Synchronous reluctance motor (SynRM) without magnet on the rotor is regarded as an ideal substitute for permanent magnet synchronous motor to obtain high efficiency, but SynRM has the disadvantages of low power factor and high torque ripple [1]. By insetting PMs within the flux barriers of SynRM, permanent magnet assisted synchronous reluctance motor (PMaSynRM) shows better performance in many aspects including torque, efficiency, and power factor [2]. The main challenge for an optimal design of PMaSynRM is to optimize the multiple design variables while ensuring the reliability of the rotor structure [3]. A novel multi-objective optimization method for PMaSynRM is proposed in this paper to realize high efficiency and low torque ripple. Based on the sensitivity analysis results of design variables, a sequential subspace optimization method (SSOM) [4] is implemented. Meanwhile, artificial neural network (ANN) [5] and multi-objective article swarm optimization (MOPSO) are used to train surrogate models and perform multi-objective optimization about electromagnetic and structural fields to reduce the required number of the time-consuming finite element analysis (FEA). 2. Winding Configurations and Comparison High torque ripple is a major disadvantage that limits the application of reluctance motors. Fractional-slot windings can obtain the relatively lower torque ripple by reducing the high-order torque harmonics generated by slot harmonics, but PMaSynRM rotors associated with fractional-slot windings cannot maintain the expected reluctance torque contribution since the difference between d-axis and q-axis flux distribution and rotor pole spacing. The windings with an odd number of slots per pole pair are the exception, which can reduce torque ripple while maintaining the saliency ratios of PMaSynRM. Therefore, six typical slot-pole number combinations are compared under the same 4-poles rotor, thermal constraints and main dimensions in this paper to investigate the performance of PMaSynRM. Compared to the integer-slot winding, the fractional-slot winding has more harmonic content, which will result in greater iron loss. At the same time, the high harmonic content also produces a great harmonic leakage that reduces the power factor of the motor. The analysis result is verified by FEA as shown in Tab.1. Fractional-slot concentrated-winding of 6-slot 4-pole can get minimum copper loss but the lowest torque and power factor due to its low winding factor and high harmonics. The efficiency and power factor are improved as the number of slots increases except for the 21-slot 4-pole motor whose harmonic content is the highest among the motors with similar slots. Integer-slot distributed-winding of 36-slot 4-pole motor has a maximum efficiency and power factor, but its torque ripple is quite high. Considering all performances of the motor, the 30-slot 4-pole motor was chosen to be the optimal solution. 3. Multi-objective Optimization It is difficult to get optimal solutions if more than 10 structural variables are optimized simultaneously. To solve multi-parameter optimization problem and reduce the computational cost, a multilevel design optimization method based on sequential subspace is proposed. Firstly, 15 design variables are selected for the optimization. Analysis of variance techniques based on the design of experiment (DOE) method is used to carry out a sensitivity analysis of parameters and the optimization variables are divided into two subspaces: the significant parameter subspace X1 and the minor parameter subspace X2. The specific multilevel optimization flowchart is given in Fig.1. The convergence error is set as 1%. Then, a surrogate model that can replace both the electromagnetic field and structural field FEA of the motor is trained by the ANN to improve optimization efficiency. To further reduce the required number of FEA simulations, the orthogonal experimental design method is adopted to generate a training set for the surrogate model. Ultimately, a multi-objective optimization is performed using the MOPSO algorithm to search for an optimal design that yields high efficiency and low torque ripple. 4.Conclusion The surrogate model successfully converges after three subspace optimizations, and its results are in good agreement with the FEA. Compared to the initial design, the optimal design yields a much higher efficiency (increased by 1.5%) and lower torque ripple (decreased by 65%) with the same volume, and the maximum stress of the rotor is about 180MPa at rated load condition. The proposed multilevel optimization method can significantly alleviate the computing burden and is suitable for the high-dimensional optimization of the PMaSynRM.

**References:**

1. N. Bianchi, M. Degano and E. Fomasiero, "Sensitivity Analysis of Torque Ripple Reduction of Synchronous Reluctance and Interior PM Motors", IEEE Transactions on Industry Applications, vol. 51, pp. 187-195(2015). 2. S. Ooi, S. Morimoto and Y. Inoue, "Performance Evaluation of a High-Power-Density PMASynRM With Ferrite Magnets", IEEE Transactions on Industry Applications, vol. 49, pp. 1308-1315(2013). 3. S. S. R. Bonthu, S. Choi and J. Baek, "Design Optimization With Multiphysics Analysis on External Rotor Permanent Magnet-Assisted Synchronous Reluctance Motors", IEEE Transactions on Energy Conversion, vol. 33, pp. 290-298( 2018). 4. G. Lei, C. Liu and Y. Guo, "Techniques for Multilevel Design Optimization of Permanent Magnet Motors", IEEE Transactions on Energy Conversion, vol. 30, pp. 1574-1584(2015). 5. J. Song, F. Dong and L. Wang, "An Efficient Multiobjective Design Optimization Method for a PMSLM Based on an Extreme Learning Machine", IEEE Transactions on Industrial Electronics, vol. 66, pp. 1001-1011(2019).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/7b9404c935dc088ecba0b6ccd8aeac6c.jpg)
Table.1 Performance of machines with different slots

![](https://assets.underline.io/uploads/markdown_image/1/image/c4651860507cd70d4a65deb4c8e351ac.jpg)
Fig. 1 Multilevel optimization framework for PMaSynRM design

 Multi-physic Fields Surrogate-assisted Optimization of a Permanent Magnet Assisted Synchronous Reluctance Motor

—In this paper, an improved direct instantaneous torque control (DITC) with sliding mode control and gray wolf optimization algorithm (GWOA) is proposed suppress torque ripple and enhance the anti-interference ability. First, the sliding mode speed controller based on a novel reaching law is designed to reduce torque ripple and startup time. Second, an anti-disturbance sliding mode observer is presented and combined with the SMSC to build up an anti-disturbance composite speed control strategy. Then, the GWOA is employed to automatically tune the parameters including the turn-on angle, turn-off angle, and coefficient in speed controller and observer for better comprehensive performance. Finally, the simulation and experimental results indicate that the proposed control method behaves well in aspects of the dynamic response and robustness, anti-interference ability, and torque ripple suppression. Introduction Due to many inherent features such as robust structure, no windings and PMs on the rotor, wide speed regulating range and high reliability, switched reluctance motors (SRMs) are becoming one potential candidate for hybrid electric vehicle (HEV) applications [1],[2]. However, SRM suffers from high torque ripple owing to the salient structure and nonlinear magnetization characteristics, which limits further development [3]. Direct instantaneous torque control The structure diagram of the DITC system combining speed controller and disturbance observer is shown in Fig. 1. The instantaneous torque obtained by the look-up table method is taken as the control quantity and then sent to torque controller after comparing with reference torque. Design of speed controller Based on conventional reaching law, an improved adaptive law is established as: ds/dt=-[k1s/[δ+(1-δ)e-α|s|]+k2|s|β]sgn(s), k1 &gt;0, k2 &gt;0, 0 &lt; δ &lt; 1, α &gt; 0, 1 &lt; β &lt; 2. The adaptive law is introduced into the speed controller to further suppress the chattering and increase convergence speed correspondingly. Design of disturbance observer based on modified STA In order to improve the anti-interference ability, the disturbance observer based on modified STA was employed in DITC system. The modified STA is defined as: du/dt=-λ1|u|1/2+lsgn(u)+u1, du1/dt=-λ2|u|2l sgn(u). Gray wolf optimization algorithm for auto-tuning The GWOA mimics the strict hierarchy and predatory behaviour of gray wolves in nature, which has been widely used in some specific applications. In the social hierarchy, gray wolves are divided into the wolf α, β, δ, and θ from high to low, which represent the best solution, the second-best solution, the third-best solution, and candidate solution, respectively. The mathematical model of the encircling behaviour of gray wolf can be expressed as follows: D=｜CXp-X｜ X(t+1)=｜Xp-A×D｜ where t is the current iteration number, D is the distance between the gray wolf and prey, X and Xp represent the position vector of the gray wolf and prey. The coefficient vectors C and A can be calculated as A=2a×r1-a C=2r2 where r1 and r2 are random vectors in [0, 1], and a is linearly decreased from 2 to 0 over the course of iterations. The mathematical model of the hunting behavior of gray wolf are shown as follows: Dp=｜CXp-X｜ Xn=｜Xp-A×Dp X(t+1)=(X1+X2+X3)/3 where the subscript p denotes α, β and δ, respectively, n denotes 1, 2 and 3, respectively, and Xn is the movement instructions given by α, β and γ, respectively. Compared with other algorithms, the GWOA stands out due to the feature of strong local search capability and high convergence rate. However, GWOA is hard to achieve a satisfactory result in solving complex optimization problems, which is likely to fall into a local solution. Simulation and experimental validation Simulations and experiments using DITC system with conventional PI and proposed sliding mode control method are compared to verify the accuracy and effectiveness. The test devices and platform for the dynamic characteristics is shown in Fig. 2.

**References:**

[1] X. Sun, K. Diao, G. Lei, Y. Guo, and J. Zhu, "Real-Time HIL Emulation for a Segmented-Rotor Switched Reluctance Motor Using a New Magnetic Equivalent Circuit," IEEE Transactions on Power Electronics, vol. 35, no. 4, pp. 3841-3849, 2020. [2] W. Ding, G. Liu, and P. Li, "A Hybrid Control Strategy of Hybrid-Excitation Switched Reluctance Motor for Torque Ripple Reduction and Constant Power Extension," IEEE Transactions on Industrial Electronics, 2019. [3] N. Yan, X. Cao, and Z. Deng, "Direct Torque Control for Switched Reluctance Motor to Obtain High Torque–Ampere Ratio," IEEE Transactions on Industrial Electronics, vol. 66, no. 7, pp. 5144-5152, 2019.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/79aee5419adcc98c0bc3c2c5d3d44f95.jpg)
Fig. 1. Block diagram of DITC system.

![](https://assets.underline.io/uploads/markdown_image/1/image/a3f52b982b68d7134611f6ffa97e78dc.jpg)
Fig. 2. Devices and platform for testing dynamic characteristics.

 Research on Sliding Mode DITC Based on Gray Wolf Optimization Algorithm for SRM

This paper presents an optimization method considering both electromagnetic and thermal performance, and a novel strategy to construct an approximate model considering multi-fidelity finite element models (FEMs) is proposed. The electromagnetic and thermal FEMs are established in ANSYS/Maxwell and Fluent, respectively. Finally, both simulation and experimental results are given and discussed. Compared with the initial design, the optimal solution exhibits lower housing temperature, higher torque, lower torque ripple and less loss. 1. Introduction Tradition optimization mainly considers electromagnetic performance and the approximate model is constructed only with the 2D FEMs [1]. In the optimization, the multiphysics performance is considered, and the 3D FEMs are predicted by 2D FEMs and the errors between 2D and 3D FEMs. The temperature of the housing, output torque, torque ripple and total loss are taken into consideration. The objective function and constraints can be defined as Function: min f1(TEMhousing), f2(-Tout), f3(Tripple), f4(Ploss) Constraints:1.10-Tout≤0, Jc-5≤0 (1) where TEMhoursing, Tout, Tripple, Ploss and Jc are housing temperature, output torque, torque ripple, loss, and allowable current density. 2. Electromagnetic and thermal FEA The 2D and 3D electromagnetic FEMs are established in Maxwell, and the 2D and 3D thermal FEMs are established in Fluent. The 2D housing thermal model in Fluent for the initial design is shown in Fig.1. 3. Two-step multi-fidelity strategy The flowchart of this optimization process is presented in Fig.1. In the first step, the initial sample points are generated by the design of experiment (DoE) and the errors between 2D and 3D FEMs are utilized to create response surface (RES). In the second step, additional sample points are generated and radial basis function (RBF) is constructed by 2D models. Then, the result of 3D FEM is predicted by the errors between 2D and 3D FEMs and the results of 2D FEMs. The βjRES(x) and δjRES is the ratio and variance between 2D and 3D FEMs 4. Results The proposed method can reduce the computational burden and improve the performance of the motor. The number of 3D and 2D FEMs are 96 and 512, respectively. The computational time duration is about 149h, which is much shorter than only use 3D FEMs. The accuracy of the approximate model in the proposed method is 1.70% and 1.06% for the 3D electromagnetic and thermal FEA, which is much more accurate than the approximate model only constructed by 2D FEMs. For the initial design, the TEMhousing, Tout, Tripple and Ploss is 371.53°C, 0.96 Nm，0.31 and 227.18W, respectively. After the optimization, the TEMhousing, Tout, Tripple and Ploss is 337.51°C, 1.18 Nm, 0.23 and 207.83 W. 5. Conclusion In this paper, a multiphysics optimization method, which can improve the performance of the switched reluctance motor, is proposed. At the same time, the two-step multi-fidelity strategy can greatly improve the accuracy of the approximate model and reduce the computational cost.

**References:**

[1] G. Y. Sizov, P. Zhang, D. M. Ionel, N. A. O. Demerdash, and M. Rosu, “Automated Multi-Objective Design Optimization of PM AC Machines Using Computationally Efficient FEA and Differential Evolution,” IEEE Trans. Ind. Appl., vol. 49, no. 5, pp. 2086-2096, 2013.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2cecec84f943298f55bf45248d022757.jpg)
Fig. 1. Flowchart of this optimization.

![](https://assets.underline.io/uploads/markdown_image/1/image/8bdd2e77ffbfec8d72dc3e18cfc53cf4.jpg)
Fig. 2. 2D housing thermal model in fluent for the initial design.

 Multiphysics and Two-step Multi-fidelity Optimization for a Switched Reluctance Motor

In this paper, a novel system level sequential design optimization method is presented for switched reluctance motor (SRM) drive systems. First, the multiobjective optimization problem for the SRM drive systems is defined. Then, all parameters of the drive systems, including the motor level and control level are divided into two subspaces according to their influences on the objectives. Finally, the optimization of each subspace is performed sequentially until a convergence criterion is met. The sensitivity analysis, the approximate models, and the genetic algorithm are employed for the implementation. Besides, the space reduction method is introduced to reduce the computational cost. The step size of each control factor will be halved in the next iterative process. To verify the effectiveness of the proposed method, An SRM drive system with a 12/10 configuration and angle position method, is investigated. I. Introduction Due to the absence of any windings and magnets in the rotor, the switched reluctance motors (SRMs) provides the best alternatives for the other machines under harsh environments of extremely high temperatures and pressures [1]. The trade-offs to the overall consideration and the implementation of multiobjective optimization are necessary to meet the requirements for different applications. Previous works are mostly on component level rather than the system level [2]. Theoretically, assembling individually optimized components into a system cannot guarantee the optimal system performance as each part is coupled to each other. Thus, the perfect cooperation of motor and control levels should be optimized simultaneously. The main problem in the system level optimization is the computation burden due to the abundant optimization variables. In this paper, the space reduction strategy will be integrated into the system level optimization flowchart. II. System-Level Sequential Subspace Design Optimization An SRM drive system with a 12/10 configuration and angle position method, will be investigated, as shown in Fig. 1. The optimization flowchart is presented in Fig. 2, and it can be divided into the following steps. Step 1: Define the system level optimization model, including objective function, constraints, and design parameters. The optimization problem can be defined as min: f(xs) s.t. gi(xs)≤0, i=1,2,…,n (1) xsl≤xs≤xsu where xs, f, gi are the design parameter vector, objective and constraints of motor, respectively, xs consists of motor parameter vector and control parameter vector, xsl and xsu are the lower boundary and upper boundary, respectively. Step 2: Divide all the parameters in motor and control aspects into two subspaces. X1 and X2 represent the significant and non-significant subspaces, respectively. Step 3: Optimize X1. Generate samples and simulate their response by using the orthogonal array (OA) [1]. An OA with a higher level with 5 levels can be assigned to X1. The Kriging model [2] is developed based on the data. Then, conduct the optimization by using non-dominated sorting genetic algorithm (NSGA) II. The optimal solution is selected for the next subspace. Step 4: Optimize X2. In this step, an OA with 3 levels is assigned to X2. The optimal solution is selected by the same implementation in step 3. Step 5: Termination judgement. Compute the motor performance with the obtained optimal design and compare it with the last objective. If the relative error is less than a given value, terminate the optimization process and output the optimal design. Otherwise, go to the next step. Step 6: Reduce the design space of the design parameters in X1 and X2, respectively. Assume the initial design space of an optimization variable is [a, b], and the optimal value of this variable is x0. For X1 in which there are 5 levels for each design parameter with a step size 2d, the next design space and new levels are [a, a+d, a+2d, a+3d, a+4d ], x0–2d&lt;a ; [b-4d, b-3d, b-2d, b-d, b ], x0+d&gt;b ; (2) [x0-2d, x0-d, x0, x0+d, x0+2d ], others For X2 in which there are 3 levels for each design parameter with a step size 2d, the next design space and new levels are [a, a+d, a+2d ], x0-d&lt;a ; [b-2d, b-d, b ], x0+d&gt;b ; (3) [x0-d, x0, x0+d ], others It can be found that the step size is halved during the space reduction.

**References:**

[1] G. Lei, C. Liu, Y. Li, D. Chen, Y. Guo, and J. Zhu, “Robust Design Optimization of a High-Temperature Superconducting Linear Synchronous Motor Based on Taguchi Method,” IEEE Trans. Appl. Supercond., vol. 29, no. 2, pp. 1-6, 2019. [2] K. Diao, X. Sun, G. Lei, Y. Guo, and J. Zhu, “Multiobjective System Level Optimization Method for Switched Reluctance Motor Drive Systems Using Finite Element Model,” IEEE Trans. Ind. Electron., 2020.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/049f17176bb7e82372435001c0f56fc3.png)
Fig. 1. Experimental platform.

![](https://assets.underline.io/uploads/markdown_image/1/image/a8eae6d01509bb9f93443b74ef2e21d0.jpg)
Fig. 2. Flowchart of the optimization strategy.

 System Level Sequential Subspace Design Optimization of Switched Reluctance Motor Drive Systems Based on Space Reduction Strategy

This paper proposes a unified control method to improve the ability of switched reluctance motors (SRM) to cope with variable operating conditions. The traditional single control method has obvious defects. The control method proposed in this paper is based on a 12/10 pole SRM. In the three-phase SRM (TSRM) mode, direct instantaneous torque control (DITC) is utilized to reduce torque ripple at low speed. In the six-phase SRM (SSRM) mode, A current-adjusted angular position control is used to increase the speed range and reduce torque ripple in high speed. The principle of dynamic coordinated control is utilized to implement switching between different modes to improve the performance of SRM. 1. Introduction A novel unified control method is proposed, which uses DITC and current control in the overlapped phase area to reduce torque ripple and obtain a wider speed range [1]. Compared with the traditional control method, the method has obvious advantages, but the speed adjustment range needs to be further expanded. Multi-objective optimization function and finite element method (FEA) are used to determine the motor parameters [2]. Experimental results prove that an SRM with 12/10 pole can be used not only as a three-phase motor but also as a six-phase motor. However, the paper does not propose a control method for switching between different modes. A unified control method is proposed for SRM in different modes. 2. The proposed method The multimode switched reluctance motor (MMSRM) is mainly composed of stator, rotor and coils. The electromagnetic performance of the TSRM and SSRM are analyzed via FEA. The flux distribution of the TSRM when one phase is excited is shown in Fig. 1 (a). MMSRM is utilized as a six-phase motor. When phase A is excited, the magnetic flux distribution at the aligned position is shown in Fig. 1(b). Compared with SSRM, TSRM has a higher instantaneous torque [2]. But the torque ripple also increases. In the low-speed range, MMSRM is used as TSRM. The direct instantaneous torque control can effectively reduce torque ripple. At the same time, the load capacity range of SRM is expanded. As the speed increases, the back electromotive force (EMF) voltage of the machine increases, which limits the ability of the controller to adjust the current. SRM enters the single pulse mode, and it is impossible to accurately track the reference current. Current-adjusted angular position control is used to reduce torque ripple in high speed. A paper confirms that the turn-off angle increases with increasing speed [1]. The calculation of the turn-off angle can be expressed as equation (1). Θd=180°+aIactual+bω+cI2actual+dωIactual +eI3actual +fωI3actual (1) where a, b, c, d, e, and f are the machine-specific coefficients, Iactual is the actual phase, and ω is the operating speed. For switching under different modes, the principle of dynamic coordinated control is utilized. Establishing the corresponding optimization objective function can greatly improve the overall efficiency of the motor. The unified control principle is shown in Fig. 2. The input parameters of the dynamic coordinated control principle are obtained through the input of working condition parameters and SRM state feedback. The unified control principle is shown in Figure 2. The input of the dynamic coordinated control principle is obtained through the input of working condition parameters and SRM state feedback. Equation (2) is used to establish the principle of SRM mode switching. Q1={x∈x1│(v&lt;vs) and (ω=0)} Q1'={x∈x1│(v&gt;vs) and (ω&gt;0)} Q2={x∈x2 } Q3={x∈x1, x∈x2 } (2) where Q, x1 and x2 respectively represent the mode judgment code, the trigger condition of TSRM and the trigger condition of SSRM. v, vs and ω respectively represent the vehicle speed, threshold of vehicle speed and motor speed.

**References:**

[1] Y. Hu, W. Ding, T. Wang, S. Li, S. Yang, and Z. Yin, "Investigation on a Multimode Switched Reluctance Motor: Design, Optimization, Electromagnetic Analysis, and Experiment," IEEE Trans. Ind. Electron., vol. 64, no. 12, pp. 9886-9895, 2017. [2] T. Husain, A. Elrayyah, Y. Sozer, and I. Husain, "Unified Control for Switched Reluctance Motors for Wide Speed Operation," IEEE Trans. Ind. Electron., vol. 66, no. 5, pp. 3401-3411, 2019.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/1428014bbed5c4ef46e91dfe58bf6b13.jpg)
Fig. 1. Topology of the SRM. (a) Excitation state of TSRM. (b) Excitation state of SSRM.

![](https://assets.underline.io/uploads/markdown_image/1/image/32ccbb86e7142e3f2cfd1c85cc387baf.jpg)
Fig.2. Schematic diagram of the unified control.

 Unified Control for Switched Reluctance Motors for Electric Vehicles

— Reluctance machines with DC field coil in stator is a competitive candidate for electric vehicle propulsion due to the elimination of rare-earth permanent magnets (PM), robust structures and controllable excitation. But with the increasing of DC field current, it is exposed to the risk of extra DC saturation in stator core. As a consequence, the torque density is constrained. To solve this problem, based on the comprehensive consideration of production cost and torque performance, this paper proposes a new type of hybrid reluctance machine with dual ferrite permanent magnets (PMs) in stator slots. The inner ferrite PM is magnetized tangentially, which can effectively achieve the DC-saturation-relieving (DCSR) effect, while the outer ferrite PM is magnetized radially to increase the motor torque density through flux modulation effect. Based on finite element analysis, machine torque density can be improved by 20% while the efficiency boosts up by 5%, respectively. Index Terms— hybrid reluctance machine (HRM), ferrite, DC-saturation-relieving (DCSR), flux modulation I.Introduction Permanent magnet (PM) machines are widely used in electrical vehicles and more electric aircraft propulsion systems. However, this rare-earth material is a nonrenewable resource, which is desired to be reduced in the machines. Switched reluctance motor (SRM) can be seen as a potential non-PM solution[1]. However, it can be only operated in the first quadrant of BH curve, and its torque density is poorer than that of PM machine. In addition, the torque ripple is serious because of half-cycle conducting. Doubly-fed doubly salient motor (DF-DSM) and SRM have similar rotor and stator structure. The difference is that the space of the stator slot is shared by DC and AC coils, which allows DF-DSM to be driven by a universal inverter[2], but meanwhile, its torque density is lower than that of SRM. Another structure named as variable flux reluctance machine (VFRM) can be designed with flexible number of the rotor teeth and the stator teeth. With the help of symmetrical magnetic circuit and odd rotor pole pairs design, the even-order flux harmonics are cancelled. Consequently, higher torque density and lower cogging torque can be acquired[3]. Unfortunately, the torque density of VFRM is still lower than that of SRM and quite lower than that of PM machine. In addition, due to the existence of DC field windings, the stator slot is prone to magnetic circuit saturation. This problem is especially obvious under high load conditions, which will seriously affect torque performance and increase core loss. To solve this problem, an innovative DC-saturation-relieving (DCSR) method using tangential PMs embedded in the slots was proposed in a previous study[4]. PMs are applied to create a magnetic field in the opposite direction to weaken the magnetic circuit saturation caused by the DC field windings. This paper conducted a study on HRM using ferrite PMs. To begin with, as a man-made material, ferrite PMs can effectively replace rare-earth PMs and greatly save motor costs[5]. Furthermore, this paper adopts the design of auxiliary excitation of dual ferrite PMs. On the one hand, the inner ferrite PMs are used to release the saturation of the magnetic circuit and do not produce the flux deviation. On the other hand, the magnetic field generated by the outer ferrite PMs and the DC excitation windings can improve through flux modulation effect. The finite element analysis is discussed as follows, and prototype experiments are going to be conducted. II.Configuration of HRM The structure of the proposed HRM is shown in Fig .1(a). It consists of DC field windings, AC armature windings, outer ferrite PMs, inner ferrite PMs, 12 stator teeth and 11 rotor teeth. It is noticeable that dual ferrite PMs play different roles in this machine. On the one hand, as shown in Fig .1(b), the inner ferrite PMs are tangentially magnetized to generate a magnetic flux opposite to that of DC field windings, so the saturation of the magnetic circuit can be decreased by the effect of DCSR. It is worth noting that the inner ferrite PMs only adjust the deviation degree of the flux linkage, but have no influence on the phase of the flux linkage. On the other hand, in Fig. 1(c), the outer ferrite PMs, magnetized radially, only affects the magnitude of the flux linkage. The emerging flux modulation principle also contributes to the improvement of torque density and efficiency. III.Performance analysis When the HRM is excited by DC only, the magnetic circuit distribution under no load condition is shown in Fig .2(a). In the case of high current density, the magnetic circuit in the rotor teeth is severely saturated, which will seriously affect the torque performance. With the help of dual ferrite PMs, the magnetic circuit saturation in the stator slots and teeth are effectively released by the DCSR effect which can be found in Fig .2(b). At the same time, as can be seen in Fig .2(c), the torque density of the motor has been significantly improved by about 20%. Conclusion A dual-ferrite-assisted DCSR hybrid reluctance machine is proposed in this paper. With the help of flux modulation effect and DCSR effect, the torque density and the efficiency can be increased by 20% and 5%, respectively.

**References:**

 [1] Y. Hu, L. Xiao and C. Pan, IEEE Trans. Power Electron., Vol. 35, p. 9563-9573 (2020) [2] Y. Wang, Z. Zhang and R. Liang, IEEE Trans. Ind. Electron., Vol. 63, p. 7434-7443 (2016) [3] Z. Q. Zhu, B. Lee and X. Liu, IEEE Trans. Ind. Appl., vol. 52, p. 1519-1529 (2016) [4] X. Zhao, S. Niu, and X. Zhang, IEEE Trans. Ind. Electron., Vol. 67, p. 9571-9581 (2020) [5] A. Fasolo, L. Alberti and N. Bianchi, IEEE Trans. Ind. Appl., Vol. 50, p. 3708-3716 (2014)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/429377183c605dd13a1b06eba7a00f05.png)
Fig. 1. (a) Configuration of HRM. (b) Flux linkage of inner ferrite PMs. (c) Flux linkage of outer ferrite PMs.

![](https://assets.underline.io/uploads/markdown_image/1/image/e26f244fd2b7681e1440d620fe24bb1b.jpg)
Fig. 2. (a) Magnetic field distribution of DC only. (b) Magnetic field distribution of DC and dual ferrite PMs. (c) Steady torque curves.

 Development of a Dual-Ferrite-Assisted DC-Saturation-Relieving Hybrid Reluctance Machine for Electric Propulsion

I. Introduction Axial-field switched reluctance machine (AFSRM) inherits the advantages of switched reluctance machine (SRM) such as simple and rugged construction, low cost, and fault-tolerant operation [1]. The unique feature of axial-field topology also makes AFSRM suitable for applications with low length-diameter ratio, such as vehicle wheels. In our previous studies, a novel AFSRM, namely axial-field dual-rotor segmented switched reluctance machine (ADS-SRM), is developed and investigated [2], [3]. However, the emphases are laid on its design methodology and torque ripple reduction. For electrical machines in automobile use, it is also necessary to reduce their weights [4]. In this paper, the optimization of stator construction for the weight minimization of ADS-SRM is implemented. After optimization, the weight of whole machine, including iron cores and coils, is reduced by roughly 25%, while the torque production capability is maintained. II. Optimization of Stator Construction Fig. 1(a) shows the discussed three-phase 12/8 ADS-SRM [2]. The motor consists of a single internal stator and two external rotors. The stator consists of twelve excitation poles, the outer and inner flux-conductive rings. The rotor consists of eight rotor segments at each side. Figs. 1(b) and 1(c) show the measuring points and operating points of flux density in the stator of ADS-SRM, respectively. It is observed that the iron-core saturation in the outer and inner flux-conductive rings is much smaller than that in the excitation pole. It is indicated that the utilizations of the iron core in the outer and inner flux-conductive rings are relatively low. To improve their utilizations, the geometries of the outer and inner flux-conductive rings should be modified. In this paper, the proposal is given in Figs. 2(a) and 2(b). As shown in Figs. 2(a) and 2(b), the runway-shaped grooves are considered on the flux-conductive rings. In Figs. 2(a) and 2(b), d is the distance between the upper/lower edge of the groove and the end surface of the flux-conductive ring, So and Si are respectively the cross-sectional areas of each flux path in the outer and inner flux-conductive rings after modification, Sm is the cross-sectional area of the excitation pole, the coefficient k is the ratio between Sm and So(Si). Here, So=Si. After the optimization of k and d, the weights of iron core and whole machine are 3.9 kg and 6.4 kg, respectively. The corresponding optimal values of k and d are 9 and 3 mm, respectively. Fig. 2(c) shows the motor geometry after optimization, and Fig. 2(d) shows the iron-core operating points in the optimized three-phase 12/8 ADS-SRM. Figs. 2(e) and 2(f) show the magnetic field distributions at unaligned and aligned rotor positions, respectively. The static torque characteristics of ADS-SRM before and after optimization are shown in Figs. 2(g) and 2(h), respectively. The modification of the stator construction is thus proved to have significant improvement in the utilization of the iron core, while there is roughly no degradation in the motor's torque-production capability. III. Conclusion This paper addresses the way to improve the utilization of the iron core at the stator part of ADS-SRM. An effective flux-conductive ring shape feature by having runway-shaped grooves is proposed and its optimal design delivered by optimizing the groove parameters shows significant improvement in the iron-core utilization at the stator part. Through the optimization of the groove parameters, the weight of whole machine is reduced by about 25%, from 8.5 kg to 6.4 kg, while there is roughly no degradation in the motor's torque-production capability.

**References:**

[1] R. Krishnan, "Switched reluctance motor drives: modeling, simulation, analysis, design and applications," Boca Raton, FL: CRC Press, Jun., (2001). [2] W. Sun, Q. Li, L. Sun and L. Li, "Development and investigation of novel axial-field dual-rotor segmented switched reluctance machine," IEEE Transactions on Transportation Electrification, doi: 10.1109/TTE.2020.3033668, (2020). [3] Q. Li, W. Sun, L. Sun and L. Li, "Rotor segment split and its optimization of axial-field dual-rotor segmented switched reluctance machine," Energy Reports, vol. 6, suppl. 9, pp. 1144-1150, (2020). [4] T. Takahashi, M. Takemoto, S. Ogasawara, etc., "Size and weight reduction of an in-wheel axial-gap motor using ferrite permanent magnets for electric commuter cars," IEEE Transactions on Industry Applications, vol. 53, no. 4, pp. 3927-3935, July-Aug., (2017).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/2ca1195c6bab75610d6302510c1d3335.jpg)
Fig. 1. (a) Motor geometry of three-phase 12/8 ADS-SRM. (b) Measuring points and (c) operating points of flux density in stator.

![](https://assets.underline.io/uploads/markdown_image/1/image/f52469706e5b80eaffe89069971b15a3.jpg)
Fig. 2. (a) Front view and (b) section A-A of modified flux-conductive rings. (c) Motor geometry, (d) operating points, and magnetic field distributions at (e) unaligned and (f) aligned rotor positions after optimization. Static torque characteristics (g) before and (h) after optimization.

 Optimization of Stator Construction for Weight Reduction of Axial-Field Dual-Rotor Segmented Switched Reluctance Machine

—The starting characteristics of a three-phase line-start synchronous reluctance motor(LS-SynRM) is introduced, and the main factors that affect the starting capability of the LS-SynRM are analyzed, and the optimization points for improving the starting capacity of the LS-SynRM are summarized. Under the condition that the efficiency of the motor keeps unchanged, a new rotor structure is proposed to improve the starting capacity of the LS-SynRM, and the effectiveness of the proposed rotor structure is verified by finite element analysis (FEA) and experimentation. 1.Introduction Compared with three-phase squirrel cage induction motors （SCIMs）, three-phase line-start synchronous reluctance motors have the advantages of low cost, high efficiency, and constant speed, and have achieved a good development in recent years. The design method, efficiency optimization, and test method of the LS-SynRMs are studied in [1]-[4], but the research of starting characteristics of LS-SynRMs are few. In this paper, the starting capability of a 1.1kW six-pole LS-SynRM are analyzed and optimized to effectively improve the starting capability of the LS-SynRM. 2.The starting principle and characteristics During the starting process of a LS-SynRM, there are asynchronous torque Ta, negative-sequence asynchronous torque Tb, and reluctance pulsating torque Tc. Due to the magnetic field of rotor has serious imbalance(Xd≠Xq, Xd and Xq are the dq-axis reactance respectively), the rotor conductor bars induce positive and negative rotating magnetic fields; The positive rotating magnetic field induced by the rotor conductor bars interacts with the rotating magnetic field generated by the stator winding to generate the asynchronous torque Ta. the negative rotating magnetic field induced by the rotor conductor bars interacts with the rotating magnetic field generated by the stator winding to generate the negative-sequence asynchronous torque Tb; When s&lt;0.5（s is the slip rate）, Tb&lt;0, which acts as a brake and affects the ability of the motor to pull into synchronization. In addition, the interaction of the rotating magnetic fields generated by stator and rotor respectively with different speeds produces a reluctance pulsating torque Tc with an average value of zero. When the inertia is small, the reluctance pulsating torque affects the pull in torque of the LS-SynRM. It can be seen that the starting capability of the LS-SynRM is related to the asynchronous torque Ta, the negative-sequence asynchronous torque Tb, and the reluctance pulsating torque Tc. 3.Optimization and design of starting capability of LS-SynRM Starting from three aspects of the asynchronous torque Ta, the negative-sequence asynchronous torque Tb, and the reluctance pulsating torque Tc, the starting capacity of a 1.1kW six-pole LS-SynRM are analyzed and optimized. Fig.1a shows the initial rotor structure of the LS-SynRM. The effects of rotor conductor bars structure, filling rate of conductor bars, flux barrier layers, and rotor inertia on the torque during the starting process are analyzed by finite element simulation, and a new rotor structure is proposed（Fig.1b）. Without reducing the efficiency of the motor, the starting capacity of the improved motor has increased by 89%, and the effect is extremely obvious. Fig.2 shows the load torque, torque and speed curves of the initial LS-SynRM and the improved LS-SynRM when starting up with a under load (same inertia). The maximum pull-in torque of the initial LS-SynRM is 6.4Nm, and the maximum pull-in torque of the improved LS-SynRM is 12.1Nm, which is 89% higher than that of the initial LS-SynRM, and the starting capability of the improved LS-SynRM is significantly improved. 4.Experimental verification In order to further verify the improvement effect of the starting capability of the improved LS-SynRM, the initial LS-SynRM and the improved LS-SynRM were made and tested. The pull-in torque of the initial LS-SynRM is 6.2Nm, and the pull-in torque of the improved LS-SynRM is 11.8Nm. The pull-in torque of the improved LS-SynRM is 90.3% higher than that of the initial LS-SynRM, and the improvement effect of the improved LS-SynRM is verified.Since the actual temperature of the motor during the test is slightly higher than the temperature given during the simulation, the resistance increases, the pull-in torque of the motor test is slightly smaller than the simulated pull-in torque. 5.Conclusion The starting characteristics of a three-phase line-start synchronous reluctance motor is introduced; The starting capacity of a 1.1kW six-pole LS-SynRM are analyzed ,and the results show that the asynchronous torque at high speed is small, and the negative sequence asynchronous torque (braking torque) is large, resulting in a small pull-in torque and poor starting ability. For this reason,a new rotor structure is proposed，the simulated pull-in torque of improved LS-SynRM is improved by 89% than that of the initial LS-SynRM;Then the improvement effect of the starting capability of the improved LS-SynRM was further verified by the test for prototype.

**References:**

[1] H. Liu and J. Lee, "Optimum Design of an IE4 Line-Start Synchronous Reluctance Motor Considering Manufacturing Process Loss Effect," in IEEE Transactions on Industrial Electronics, vol. 65, no. 4, pp. 3104-3114, April 2018. [2] Y. Hu, Y. Xiao, B. Chen and J. Shi, "Effect of Direction and Shape of Rotor Conductor Bars on Parameters of Line-Start Synchronous Reluctance Motor," 2018 21st International Conference on Electrical Machines and Systems (ICEMS), Jeju, 2018, pp. 634-639. [3] S. T. Boroujeni, N. Bianchi and L. Alberti, "Fast Estimation of Line-Start Reluctance Machine Parameters by Finite Element Analysis," in IEEE Transactions on Energy Conversion, vol. 26, no. 1, pp. 1-8, March 2011. [4] H. Kärkkäinen et al., "Direct-On-Line Synchronous Reluctance Motor Efficiency Verification with Calorimetric Measurements," 2018 XIII International Conference on Electrical Machines (ICEM), Alexandroupoli, 2018, pp. 171-177.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/003a58e133722e82d66770978e144e7a.jpg)
Fig.1. The initial and improved rotors of LS-SynRM

![](https://assets.underline.io/uploads/markdown_image/1/image/0bacdc294419fda8c12a7afb8f7d2b7a.jpg)
Fig.2. The load torque, torque, and speed curves of the initial and improved LS-SynRM

 Design and Optimization of Starting Capability of a Line-start Synchronous Reluctance Motor

1. According to IEC 60034-1, as the industrial applications, not only efficiency but also power factor are important performance index. As a direct on line motor to replace induction motor (IM), a line-start synchronous reluctance motor (LS-SynRM) have a high efficiency but a low power factor than that of IM. Therefore, in this paper, the optimal design of LS-SynRM is proposed considering the efficiency, power factor, and mechanical stress using rotor slot opening and bridges. Based finite element analysis (FEA), the performances of LS-SynRM are analyzed according to the slot opening and the number of bridges. The initial model is selected considering the efficiency, power factor, and mechanical reliability. Then, based on the initial model, the optimal design is performed to improve the efficiency, power factor, and mechanical stress. Finally, the optimal design result is verified through the manufacture and experiment. 2. Introduction As the consumption of electric energy is increased, the efficiency of electrical motor is important. According to IEC 60034-1, the efficiency of motor is defined from IE1 to IE4. Recently, the industrial motors have been required to satisfy the IE4 class efficiency. A line-start synchronous reluctance motor (LS-SynRM) have been studied as an alternative to induction motor because LS-SynRM can have IE4 class efficiency. However, because of the saliency characteristic, LS-SynRM have a limited power factor [1]. In the industrial motors, the power factor is also an important factor according to IEC 60034-1 [2]. Therefore, the power factor of LS-SynRM must be improve for industrial application. In this paper, the optimal design of LS-SynRM is performed considering the efficiency, power factor and mechanical stress. The efficiency and power factor improve through reduction of leakage flux of the outer rib. In order to reduce the leakage flux, the rotor slot opening of outer rib is used, but the mechanical stress increases. Therefore, the bridges and rotor slot opening are used to improve the efficiency, the power factor, and mechanical reliability. First, based on finite element analysis (FEA), the performances of LS-SynRM are analyzed according to the number of bridges. Considering the performances of LS-SynRM, the initial model is selected. Furthermore, the optimal design is performed to maximize the efficiency, the power factor, and mechanical reliability. To verify FEA result, the optimal model of LS-SynRM is manufactured, and the experiment of LS-SynRM is performed. 3. Design of LS-SynRM LS-SynRM must be operated at synchronous speed. Moreover, LS-SynRM at synchronous speed have same performance with SynRM. Therefore, the performance of LS-SynRM at synchronous speed is as follow Eq. (1). Te = Pn(Ld-Lq)idiq , PF=(Ld -Lq)/(Ld+Lq) (1) Where Te is torque, Pn is pole pair, Ld is d-axis inductance, Lq is q-axis inductance, id is d-axis current, iq is q-axis current, and PF is power factor. From Eq. (1), the torque and power factor is function of the dq-axis inductance. In particular, the power factor is determined by the saliency ratio (Ld/Lq). Therefore, to improve power factor, the saliency ratio must be increased. From the relationship of the inductance and magnetic resistance as follows Eq. (2), the power factor is also function of the magnetic resistance ratio (Rq/Rd). L=N2/R (2) Where L is inductance, N is turn of winding, and R is the magnetic resistance. Therefore, the power factor of LS-SynRM are determined the design parameters design parameters affecting the dq-axis magnetic resistance. Based on the magnetic equivalent circuit [3], the q-axis magnetic resistance is increased by the rotor slot opening, but the mechanical stress of rotor is increased. In order to decrease the mechanical stress, the bridge is applied to the rotor. However, the d-axis magnetic resistance is increased by the bridges. Therefore, the design of rotor slot opening and bridge is relationship of trade off for motor performance. Considering the objective function, the optimal design is performed to improve the efficiency, power factor, and mechanical reliability. Fig. 1 shows the motor performance according to the two design parameters. As a result of the optimal design, the thickness of slot opening and bridge are designed to be 0.5[mm] and 0.5[mm], respectively. Fig. 2 shows the manufactured optimal LS-SynRM to verify FEA result. In the future, the detail the magnetic equivalent circuit will be discussed considering the slot opening and bridges. Furthermore, the optimal design method will be discussed considering the efficiency, power factor and mechanical stress. 4. Conclusion In this paper, the performances of LS-SynRM are analyzed according to the rotor slot opening and bridges based on the magnetic equivalent circuit and FEA. Furthermore, the optimal design is performed to improve the efficiency, power factor, and the mechanical reliability. As a result, the rotor slot opening and bridges are designed to improve the efficiency and power factor considering the mechanical reliability. In the future, the detail magnetic equivalent circuit will be discussed according to the rotor slot opening and bridges. Moreover, the detail optimal design considering the mechanical reliability will be discussed. Finally, FEA and experiment result of manufactured LS-SynRM will be added to verify the optimal design result.

**References:**

[1] K.-J. Joo, I.-G. Kim, and J. Lee, IEEE Trans. Magnetics, Vol. 53, Art no. 8102604 (2017) [2] A.T.D. Almeida, F.J.T.E. Ferreira, and A.Q. Duarte, IEEE Trans. Ind. Appl. Vol. 50, pp. 1274-1285 (2014) [3] J.-K. Lee, D.-H. Jung, and J. Lim, IEEE Trans. Magnetics, Vol. 54, Art no. 8103005 (2018)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/0a5530827f9d5a8cb51a92acec2ff4ec.jpg)
Fig. 1 Performance map of LS-SynRM according to design parameters (a) efficiency (b) power factor

![](https://assets.underline.io/uploads/markdown_image/1/image/7b044fd573e31506c1c39b0f73b67939.jpg)
Fig. 2 Manufacture of optimal LS-SynRM

 A Study on Analysis and Design of Line-Start Synchronous Reluctance Motor Considering Rotor Slot Opening and Bridges

INTRODUCTION Since Nicholas Tesla proposed the concept of wireless power transfer (WPT) in the 1890s, it has been considered as an innovative technology, which offers definite advantages of reliability and electrical isolation [1]. Due to these outstanding advantages, many researchers have applied this emerging technology in the domestic and industrial electronic areas, such as consumer electronics and medical devices [2]. The idea of wireless motor can be traced back to 2016 when Motoki Sato proposed probably the first wireless motor [3], which aims to avoid power cable friction. Although it is favorable in harsh environments, it is ill-suited for isolated environments, because the motor controller is installed in the secondary side, which highly requires regular maintenance. To overcome this problem, wireless switched reluctance (SR) motor [4] is proposed, which adopts a self-drive circuit to replace the motor controller. However, this system needs three receivers to feed three-phase stator windings, and this causes three drawbacks: 1) this topology is bulky and heavy; 2) mutual inductance between receivers will harm system selectability; 3) after commutation, the energy restored in the receiver coil will be discharged by feeding the corresponding stator winding, which extends the commutation time and causes reverse torque. In other words, this topology highly limits motor speed and decreases system efficiency. The purpose of this paper is to propose a new wireless SR motor with single receiver, which takes distinct advantages of compact structure and better dynamic performance. The key is to employ a suitable three-frequency resonating compensation (TFRC) network [5], and a specially designed self-drive inverter. METHODOLOGY Fig. 1 depicts the system configuration, where LT and LR are the inductance of transmitter and receiver; CT, CT1, LT1, CT2, and LT2 are the resonant inductances and resonant capacitance to constitute the primary TFRC network, while CR, CR1, LR1, CR2, and LR2 constitute the secondary TFRC network; LU, CU, LV, CV, LW, and CW constitute three-phase LC tuning circuits to offer the control signal for secondary inverter; CL is the filter capacitance of the bridge rectifier; SU, SV, and SW comprise the three-phase inverter; VS, VCU, VCV and VCW are adopted to represent the voltage of AC power source, CU, CV, and CW, respectively. It should be noted that the TFRC network can fully compensate transmitter and receiver at three frequencies, namely fU, fV, and fW, and the design procedure is described in [5]. Besides, U-phase, V-phase, and W-phase LC tunning circuits are resonant at fU, fV, and fW, respectively. The whole control process can be handle from the primary side by changing the frequency of VS, and the method of extracting control signal for secondary inverter is basically same as wireless SPIM [6]. Taking U-phase as an example, when the primary side transmits the energy at fU, the receiver current mainly flows the U-phase LC tunning circuit, so VCU is high while VCV and VCW are almost zero, thus only SU is switched on while the other switches are off. Therefore, by switching system frequency alternatively, three stator windings can be fed in turns, and rotating stator magnetic field can be acquired. Besides, rotor position can be detected by Hall position sensor, and transmitted to the primary side through Bluetooth. In addition, power balance between three phases is also considered. As the secondary induced voltage is inversely proportional to the transmitting frequency, the effective value of transmitter current should be carefully regulated according to [6]. Circuit simulations are carried out to show the feasibility of the proposed system. The key parameters will be given in the full paper, and the load motor is replaced by 20 Ω resistor, which is the equivalent resistance of SR motor according to [4]. The result is shown in Fig. 2 (a), where three stator windings are fed with IU, IV, and IW in turns, which proves the feasibility of this system. Meanwhile, it can be observed that the value of three-phase current is the same by changing the transmitter current IT in different phases. Besides, self-drive ability is also analyzed. As shown in Fig. 2(b) and (c), VCU, VCV, and VCW are reliably higher than 7V when the system operates at the corresponding frequencies, and these voltages can be employed to control inverter after isolating and rectifying. CONCLUSION In this paper, a novel wireless SR motor system is presented. Compared with [4], the proposed system employed single transmitter and single receiver system to achieve compact structure, and a self-drive inverter is adopted to avoid the freewheeling and the resulting reverse torque. Besides, this system retains the merit of secondary-controller-less, which is favorable for maintenance-free operation. For verification, simulations are conducted and prove system feasibility. Furtherly, the experiment will be given in the full paper. Acknowledgment This work was supported by a grant (Project No. 17207420) from the Hong Kong Research Grants Council, Hong Kong Special Administrative Region, China.

**References:**

[1] Y. Bu, T. Mizuno, and H. Fujisawa, "Proposal of a wireless power transfer technique for low-power multireceiver applications," IEEE Transactions on Magnetics, vol. 51, no. 11 (2015) [2] H. Moon, S. Kim, and H. H. Park, "Design of a resonant reactive shield with double coils and a phase shifter for wireless charging of electric vehicles," IEEE Transactions on Magnetics, vol. 53, vol. 51, no. 3 (2015) [3] M. Sato, G. Yamamoto, and D. Gunji, "Development of wireless in-wheel motor using magnetic resonance coupling," IEEE Transactions on Power Electronics, vol. 31, no. 7, pp. 5270-5278 (2016) [4] C. Jiang, K. T. Chau, and W. Liu, "An LCC-compensated multiple-frequency wireless motor system," IEEE Transactions on Industrial Informatics, vol. 15, no. 11, pp. 6023-6034 (2019) [5] Z. Zhang, X. Li, and H. Pang, "Multiple-frequency resonating compensation for multichannel transmission of wireless power transfer," IEEE Transactions on Power Electronics, to be published. [6] H. Wang, K. T. Chau, and C. H. T. Lee, "Design, analysis and implementation of wireless shaded-pole induction motors," IEEE Transactions on Industrial Electronics, to be published.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/75300181fca23227eb765522c9deab08.jpg)
System configuration of wireless SR motor

![](https://assets.underline.io/uploads/markdown_image/1/image/8127b0ae42bc060b3e750e77ff4a8ec1.jpg)
Simulation results under rated condition. (a) Current of transmitter and load. (b) Voltages of capacitors in LC tunning circuits. (c) Voltages of capacitors in LC tunning circuits after rectification.

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