France



Introduction - Recently, as the demand for robots and the supply ratio of renewable energy have increased, the usage of electric motors and generators has increased. Therefore, sensors required for detecting the position of the rotor has also increased. Of these, the safety window motor for preventing accidents in which an automobile window is pinched is based on the principle that a ring type bond magnet is attached to the lower part of the rotor of the motor to detect the magnetic flux and detect the position. At this time, a dead zone, which is a section where the magnetic flux is very weak, is generated between the N pole and the S pole of the ring-type bond magnet and the hall sensor does not detect the magnetic flux in this section When the range of this dead zone is large, the region where the magnetic flux can be detected is limited, so that accurate position detection is impossible. In this paper, we provide the optimum model of a polar anisotropic molding yoke with a magnetic flux-concentrated structure for the dead zone reduction plan of ring type bond magnets for accurate control of electric motors and generators.&lt;br/&gt;&lt;br/&gt;Equation - In order to concentrate the magnetic flux generated from the permanent magnet of the molding yoke, a structure having a high magnetic flux concentration factor is required. This indicates that the more magnetic flux passing through the magnet than the air gap, the more the magnetic flux is concentrated. Therefore, if the magnetic flux-concentrated structure is used, when a magnetic field is applied, the air gap flux density can be higher than that of the conventional model, and the dead zone of the ring type bond magnet can be reduced.&lt;br/&gt;&lt;br/&gt;Analysis &amp; Result – In the case of the conventional model, the structure is such that a magnetic field is directly applied to a very different ring type bond magnet with a permanent magnet. Therefore, the magnetic flux does not penetrate deeply into the magnet, and a large Dead Zone is generated. To reduce this dead zone, this paper designed a model that could be molded with a high air gap flux density by inserting a magnetic flux concentration core. The thickness of the inner and outer teeth and the direction of the magnetic field applied to the permanent magnet were used as the design variable. In this paper, the results were analyzed through finite element analysis. The design variable of inner and outer teeth thickness was set range of 0mm to 12mm and the angle degree of the magnetic field applied to the permanent magnet was set the range of 0° to 90°.&lt;br/&gt;&lt;br/&gt;a) Air gap flux density according to magnetization angle&lt;br/&gt;When the inner teeth thickness is 11mm and the outer teeth thickness is 0mm, the change in air gap flux density according to the magnetization direction was analyzed. When the angle of the magnetization direction is too large or too small, the magnetic flux leaks to the permanent magnet and the outside. So it can be confirmed that the maximum air gap flux density is generated around 40°.&lt;br/&gt;&lt;br/&gt;b) Air gap flux density according to the thickness of the inner teeth&lt;br/&gt;When the angle of the magnetization direction is 40° and the thickness of the outer teeth is 0mm, the change in air gap flux density according to the thickness of the inner teeth was analyzed. Analyzing the results at 12.5° where the dead zone occurs in a ring type bond magnet, the magnetic flux leaks to the adjacent core when the thickness of the inner teeth is too large. So it can be confirmed that the magnetic flux is most concentrated on the pole of the ring type bond magnet when the thickness of the inner teeth is 11mm.&lt;br/&gt;&lt;br/&gt;c) Air gap flux density according to the thickness of the outer teeth&lt;br/&gt;When the angle of the magnetization direction is 40° and the thickness of the inner teeth is 11mm, the change in air gap flux density according to the thickness of the outer teeth was analyzed. It is confirmed that when the thickness of the outer teeth is 0mm, the magnetic flux leaked to the outside is minimized and the maximum air gap flux density is generated.&lt;br/&gt;&lt;br/&gt;Therefore, an optimum model that can be molded to the highest air gap flux density was obtained. Comparing the waveforms of the air gap flux density of the proposed model and the conventional model, the proposed model increased the air gap magnetic flux density by 23% compared to the conventional model. As a result, dead zone decreased by about 22%.&lt;br/&gt;&lt;br/&gt;Conclusion – In this paper, a flux-concentrated core was inserted to reduce the dead zone range of the ring type bond magnet. As a result, it is possible to reach a higher air gap flux density than the conventional model. Finally, the validity of this paper was verified through the finite element analysis method. Based on this, it is expected that the market share of the safety window can be expanded, and further, the technological competitiveness of domestic sensor industries can be improved.&lt;br/&gt;&lt;br/&gt;Acknowledgment - This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT). (No. 2020R1A2C1013724) NRF - 2020R1A2C1013724

**References:**

H. J. Kim et al, IEEE Trans. Magn., vol. 46, no. 6, pp. 2314-2317, Jun. 2010

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/9cab3636cee4a5e0db5c3e684990f0cb.jpg)
Magnetic Flux Density of Conventional &amp; Proposed Model

![](https://assets.underline.io/uploads/markdown_image/1/image/eb542ad3264d6f8c7f1b0dc4dff9549a.jpg)
Waveform Comparison of Conventional &amp; Proposed Model

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 Research on Polar Anisotropic Molding Yoke Shape to Reduce Dead Zone of Ring Type Bond Magnets

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Introduction - Recently, as the demand for robots and the supply ratio of renewable energy have increased, the usage of electric motors and generators has increased. Therefore, sensors required for detecting the position of the rotor has also increased. Of these, the safety window motor for preventing accidents in which an automobile window is pinched is based on the principle that a ring type bond magnet is attached to the lower part of the rotor of the motor to detect the magnetic flux and detect the position. At this time, a dead zone, which is a section where the magnetic flux is very weak, is generated between the N pole and the S pole of the ring-type bond magnet and the hall sensor does not detect the magnetic flux in this section When the range of this dead zone is large, the region where the magnetic flux can be detected is limited, so that accurate position detection is impossible. In this paper, we provide the optimum model of a polar anisotropic molding yoke with a magnetic flux-concentrated structure for the dead zone reduction plan of ring type bond magnets for accurate control of electric motors and generators. Equation - In order to concentrate the magnetic flux generated from the permanent magnet of the molding yoke, a structure having a high magnetic flux concentration factor is required. This indicates that the more magnetic flux passing through the magnet than the air gap, the more the magnetic flux is concentrated. Therefore, if the magnetic flux-concentrated structure is used, when a magnetic field is applied, the air gap flux density can be higher than that of the conventional model, and the dead zone of the ring type bond magnet can be reduced. Analysis & Result – In the case of the conventional model, the structure is such that a magnetic field is directly applied to a very different ring type bond magnet with a permanent magnet. Therefore, the magnetic flux does not penetrate deeply into the magnet, and a large Dead Zone is generated. To reduce this dead zone, this paper designed a model that could be molded with a high air gap flux density by inserting a magnetic flux concentration core. The thickness of the inner and outer teeth and the direction of the magnetic field applied to the permanent magnet were used as the design variable. In this paper, the results were analyzed through finite element analysis. The design variable of inner and outer teeth thickness was set range of 0mm to 12mm and the angle degree of the magnetic field applied to the permanent magnet was set the range of 0° to 90°. a) Air gap flux density according to magnetization angle When the inner teeth thickness is 11mm and the outer teeth thickness is 0mm, the change in air gap flux density according to the magnetization direction was analyzed. When the angle of the magnetization direction is too large or too small, the magnetic flux leaks to the permanent magnet and the outside. So it can be confirmed that the maximum air gap flux density is generated around 40°. b) Air gap flux density according to the thickness of the inner teeth When the angle of the magnetization direction is 40° and the thickness of the outer teeth is 0mm, the change in air gap flux density according to the thickness of the inner teeth was analyzed. Analyzing the results at 12.5° where the dead zone occurs in a ring type bond magnet, the magnetic flux leaks to the adjacent core when the thickness of the inner teeth is too large. So it can be confirmed that the magnetic flux is most concentrated on the pole of the ring type bond magnet when the thickness of the inner teeth is 11mm. c) Air gap flux density according to the thickness of the outer teeth When the angle of the magnetization direction is 40° and the thickness of the inner teeth is 11mm, the change in air gap flux density according to the thickness of the outer teeth was analyzed. It is confirmed that when the thickness of the outer teeth is 0mm, the magnetic flux leaked to the outside is minimized and the maximum air gap flux density is generated. Therefore, an optimum model that can be molded to the highest air gap flux density was obtained. Comparing the waveforms of the air gap flux density of the proposed model and the conventional model, the proposed model increased the air gap magnetic flux density by 23% compared to the conventional model. As a result, dead zone decreased by about 22%. Conclusion – In this paper, a flux-concentrated core was inserted to reduce the dead zone range of the ring type bond magnet. As a result, it is possible to reach a higher air gap flux density than the conventional model. Finally, the validity of this paper was verified through the finite element analysis method. Based on this, it is expected that the market share of the safety window can be expanded, and further, the technological competitiveness of domestic sensor industries can be improved. Acknowledgment - This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT). (No. 2020R1A2C1013724) NRF - 2020R1A2C1013724

**References:**

H. J. Kim et al, IEEE Trans. Magn., vol. 46, no. 6, pp. 2314-2317, Jun. 2010

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/9cab3636cee4a5e0db5c3e684990f0cb.jpg)
Magnetic Flux Density of Conventional & Proposed Model

![](https://assets.underline.io/uploads/markdown_image/1/image/eb542ad3264d6f8c7f1b0dc4dff9549a.jpg)
Waveform Comparison of Conventional & Proposed Model

poster

This work focuses on the analysis of rotor geometry parameters and added flux barriers design to improve the anti-demagnetization capability of fractional slot concentrated windings interior permanent magnet motor (IPM) for electric vehicle (EV) traction applications. A 2.5kW V-shape IPM motor (12 slots and 8 poles) is designed to achieve high torque density and wide constant power speed range (CPSR), which is selected to study in this paper. The influence of rotor geometry parameters variation (such as the magnet position and angle, the width and thickness of magnet) on the relation of characteristic current (Ich) and demagnetization in wide-speed range operation is firstly investigated under high-temperature and high current density operation. Then, the impact of added flux barriers design on the anti-demagnetization capability of the IPM motor is evaluated. The analysis results show that the increase of magnet angle of V-shape IPM would improve the anti-demagnetization capability but would reduce Ich; meanwhile, the increase of magnet thickness would increase Ich and simultaneously improve the anti-demagnetization capability. In addition, the added flux barriers design significantly affects the anti-demagnetization capability of the V-shape IPM motor. Finally, a unique multi-objective genetic algorithm is applied for the rotor geometry optimization of the V-shape IPM motor to achieve good anti-demagnetization capability, excellent CPSR, and high efficiency. Finite element analysis (FEA) is used for evaluation, and experiments are conducted to validate the analysis. I.Introduction In order to achieve the power and torque requirements of an EV motor, magnetic loading and electrical loading need to be improved. However, due to the saturation of the electrical steel sheet, a high current density design is unavoidable. In a high current operating environment, due to the high temperatures and strong armature magnetic field presented in the motor, the magnetic field provided by the magnet is usually reduced. Under these conditions, the magnet can suffer from irreversible demagnetization. For this reason, a higher current will be required to achieve the originally expected performance. To avoid this type of problem is very important to design a motor with high resistance to demagnetization for the safety and reliability of the product. II.Target Models and Analysis Method A 2.5 kW fractional slot concentrated windings V-shape IPM motor with 12 slots and 8 poles is applied to study here. The rotor configuration of V-shape IPM with the design parameters is shown in Fig. 1(a) and the design of different flux barriers is presented in Fig. 1(b). Finite element analysis (FEA) is utilized to comprehensively evaluate the impact of rotor geometry parameters variation and design characteristic of added flux barriers on the relation of characteristic current (Ich) and the anti-demagnetization capability of the V-shape IPM motor. The details will be reported in the full paper. III.Analysis Results and Experiments Fig. 2 shows the comparison of magnetic flux density distribution on PM without and with added flux barriers design during no-load and load conditions. It can be seen that the added flux barriers design significantly affects the demagnetization risk on PM. Fig. 3 presents the comparison of back EMF of V-shape IPM motor without and with the added flux barriers design before and after demagnetization. The result shows that the added flux barriers design significantly reduces the demagnetization risk on PM of V-shape IPM motor. Fig. 4(a) shows the rotor configuration after optimized of the V-shape IPM motor which is made as a prototype for validating the analyses. Fig. 4(b) shows the comparison of back EMF of V-shape IPM motor between the simulation and experiment at 1500 rpm speed. The phase voltage of back EMF is 13.45 V in the simulation, thus the peak-to-peak of back EMF is 23.3 V; meanwhile, the measured back EMF is 24.8 V. The error between the simulation and experiment is only 6%, thus the analysis results are reliable. Fig. 5(a) shows the torque and power versus speed curves of the V-shape IPM motor. The output torque of the motor is 9.17 Nm for simulation and 8.9 Nm for the experiment, respectively. Fig. 5(b) presents the comparison of back EMF of IPM motor before and after demagnetization in the experiment. The back EMF of the motor after fully demagnetized magnets only has an error of 2%. The accuracy of the simulation is thus verified by the experiment results. Detail analysis and experiment will be reported in the full paper. IV.Conclusion This digest has analyzed the impact of rotor geometry parameters variation and design characteristic of added flux barriers on the performance and the anti-demagnetization capability of fractional slot concentrated windings V-shape IPM motor. The added flux barriers design significantly affects the performance and anti-demagnetization capability of the V-shape IPM motor. The detail analysis and experimental results will be reported in the full paper.

**References:**

[1] H. Chen, R. Qu, J. Li and D. Li, "Demagnetization Performance of a 7 MW Interior Permanent Magnet Wind Generator With Fractional-Slot Concentrated Windings," IEEE Transactions on Magnetics, vol. 51, no. 11, pp. 1-4, Nov. 2015. [2] K. Imamura, M. Sanada, S. Morimoto, and Y. Inoue, "Improvement of Demagnetization by Rotor Structure of IPMSM with Dy-Free Rare-Earth Magnet," in Proceeding of IEEE International Electrical Machines and Systems Conference, Sapporo, 2012.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/fcfca40933137a8cd42350003e640535.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/2d090a655c8e9f78b85a456e612d031d.jpg)

 Design and Optimization of Fractional Slot Concentrated Windings Interior Permanent Magnet Traction Motor Considering Anti-Demagnetization Capability

I. Introduction With the large-scale application of rare-earth permanent magnet motors, the consumption of rare-earth PM material has increased sharply [1]. As a non-renewable resource, such excessive consumption increases the potential risks of further larger scale application of rare-earth PM motors. Recently, to alleviate the dependence on the rare-earth PMs, a type of less rare-earth permanent magnet (LRE-PM) machines has attracted much attention since the adoption the low cost of non-rare-earth Ferrite-PMs [2]. In this paper, a new asymmetric-PM-placed rotor topology is applied to the conventional LRE hybrid magnet machine, where such new placement of hybrid magnets can be designed to improve the torque performance effectively. Considering the complexity of rotor structure and the difference between two magnetic materials, the relationship among the size of the hybrid magnets (NdFeB-PMs and Ferrite-PMs), torque density and torque ripple is investigated through theoretical derivation and finite element analysis. And, some key size parameters are optimized to improve torque performances. II. Optimization Design and Analysis of Torque Performance In this paper, a new frozen permeability method is used to separate the components of total torque [3], and the design factors influencing torque ripple are deduced theoretically. According to the principle of equivalent magnetomotive force, the initial design of hybrid magnets is carried out. Then for the key size of hybrid magnets, the sensitivity analysis of multiple optimization objectives is conducted to obtain the optimal solution [4]. The effectiveness of the proposed method is verified by comparing the torque performance and anti-demagnetization property of the initial machine with that of the optimized one. Fig. 1(a) shows the proposed asymmetric-hybrid-PM machine structure. In the rotor, the NdFeB-PMs and Ferrite-PMs are asymmetric arranged in mixed series-parallel connection. It can be seen that the permanent magnet torque (Tpm) decreases due to the coupling effect of the two different magnets. However, by properly designing the size of spoken hybrid magnet element arranged asymmetrically, the reluctance torque (Tr) can be improved and the maximum torque approximation angle can be optimized to improve the torque density. Fig. 1(b) shows the sensitivity analysis results of key parameters and the optimal solution. The improvement of torque capabilities and anti-demagnetization ability is shown in Fig. 2, which verifies the validity of the proposed optimal method. III. Verification by FEM and Experimental Results In order to further verify the feasibility of the motor topology and the effectiveness of the proposed optimal method, an experimental prototype is fabricated, and more detailed electromagnetic performance analysis and experimental results will be presented in the full paper.

**References:**

Xianxian Zeng , Li Quan, Xiaoyong Zhu, et al., Investigation of an asymmetrical rotor hybrid permanent magnet motor for approaching maximum output torque. IEEE Trans. Appl. Supercond., 2019, vol. 29, no. 2, Article No. 0602704. Qian Chen, Gaohong Xu, Guohai Liu, et al., Reduction of torque ripple caused by slot harmonics in FSCW spoke-type FPM motors by assisted poles, IEEE Trans. Ind. Electron., 2020, Vol. 67, No. 11, pp. 9613-9622. Xiaoyong Zhu, Deyang Fan, Zixuan Xiang, et al., Systematic multi-level optimization design and dynamic control of less-rare-earth hybrid permanent magnet motor for all-climatic electric vehicles. Appl. Energy, 2019, 253, 113549. B.Ma, G. Lei, J. Zhu,Y. Guo, et al., Application-oriented robust design optimization method for batch production of permanent-magnet motors, IEEE Trans. Ind. Electron., vol. 65, no. 2, pp. 1728-1739, Feb. 2018.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/03c0c46a76b52ca2246ddd38c2652f05.jpg)
The asymmetric-hybrid-PM machine structure and the optimal design.

![](https://assets.underline.io/uploads/markdown_image/1/image/b35a41508a2c8d22094211a2422f6d66.jpg)
The performance improvement of the proposed machine.

 Optimization of a New Asymmetric-hybrid-PM Machine with High Torque Density and Low Torque Ripple Considering the Difference of Magnetic Materials

I. INTRODUCTION This paper proposed a new flux-concentrating rotor for PM machine, taking advantages of spoke-type and Halbach array PM flux-concentrating. As shown in Fig. 1 (a), it is the evolution of the proposed rotor. The upper part of tangentially magnetized magnets still remain the spoke-type flux-concentrating property, while the bottom tangentially magnetized magnets and the radially magnetized magnets form a primitive Halbach array [1] [2]. Since the ratio match tangentially/radially magnetized magnets directly affects the effect of flux-concentrating, as well as the saliency ratio and torque performance, this paper focuses on the optimization of the size of permanent magnets on the rotor on the basis of keeping the same amount of PMs and the polar arc coefficient. II. OPTIMAL DESIGN OF NEW FLUX-CONCENTRATING ROTOR Response surface method (RSM) is a set of statistical and mathematical techniques to find the “best fitted” response of the physical system through experiment or simulation [3]. In RSM, a polynomial model, called a fitted model, is generally constructed to represent the relationship between the performance and design parameters. As shown in Fig. 1 (a), it is the evolution of the proposed rotor. Ensuring the same volume of PM in three rotors, the new rotor was optimized. The geometric parameters of the new rotor are shown in Fig. 1 (b). In order to quantitatively compare with the motor whose pole-arc coefficient is 0.8, including in various electromagnetic characteristics. b is determined as 8 mm. The volume of PM is defined as (1). where p is pole pairs, l is stack length, m is the volume of PMs. The optimized objective is formulated to maximize the air-gap flux density under the constraint of keeping the PM volume. Tab. I shows electromagnetic analysis results under various combinations of lx and hy. The relationship between air-gap flux density and lx, hy is shown in Fig. 2 (a). Two optimized points are found, where the analysis result is better than the predicted value. The regression equations of air-gap flux density obtained by RSM analysis is as (2). As shown in Fig. 2 (b), the predicted value and the actual result maintain a high consistency. It can be concluded that the regression equation obtained by the RMS is reliable. As shown in Fig. 3, The result of optimization is to maximize the air-gap magnetic density. . lx is determined as 16.5 mm, and hy is determined as 3.75 mm. Fig. 4 shows the comparison of two rotors. The final optimized model is built by 2-D FEA, as shown in Fig.5. III. FEA AND EXPERIMENTAL VERIFICATION Tab. II gives the main parameters of optimized rotor. Fig. 6 (a) compares the air-gap flux density of the motors with optimized rotor and the original rotor. The air-gap flux density in the motor with optimized rotor is higher than that in the initial one. As shown in Fig. 6 (b), the line back electromotive force (EMF) of the motor with optimized rotor increases slightly due to the higher air gap flux density. Fig. 6 (c) shows the C-T relationship under maximum torque per ampere (MTPA) control and id=0 control. The results show that under MTPA control and id=0 control, the output torque of the optimized rotor is higher than the initial model. In Fig. 6 (d), the saliency ratio is higher in the optimized rotor than in the original one. so the flux-weakening ability is stronger. Considering the manufacturing process, the actual rotor structure is shown in Fig. 7 the shape of the radially magnetized PMs are rectangular. The stator, rotor and test platforms are shown in Fig. 8. Fig. 9 compares the experimental and FEA results. Fig. 9 (a) is the comparison between the experimental and analytical result about back EMF without load, Fig. 9 (b) shows the C-T relationship of the motors with original rotor and optimized rotor under MTPA control and the results present a high consistency and error is less than 2%. But the error is large in the relationship between experiment and analysis under id=0 control due to the reluctance torque is fully utilized with the large current. IV. CONCLUSION In this paper, a new flux-concentrating rotor for PM machines is designed to combing spoke-type IPM rotor and Halbach PM array The size parameters of PM of the new rotor are optimized by the response surface method for the maximum air-gap flux density and torque capacity considering the constant pole-arc coefficient and the volume of PM.The 72-slot/16-pole PM motor with the optimized rotor is developed by 2-D FEA and experiments. The experimental result the air-gap flux density is increased by 6.7%and the torque is increased by 7.5%.

**References:**

[1]Igor P. Wiltuschnig, Paulo R. Eckert, David G. Dorrell ,“A Study of the influence of quasi-Halbach arrays on a torus machine,” IEEE Trans. Magn.,.vol. 52, no. 7, pp. 1325-1328. July 2016. [2]M. M. Rahman, K.-T. Kim, and J. Hur, “Design and optimization of neodymium-free spoke-type motor with segmented wing-shaped PM,” IEEE Trans. Magn., vol. 50, no. 2, Feb. 2014, Art. ID 7021404. [3]Byeong-Hwa Lee;Jung-Pyo Hong;Jung-Ho Lee ,“Optimum Design Criteria for Maximum Torque and Efficiency of a Line-Start Permanent-Magnet Motor Using Response Surface Methodology and Finite Element Method,” IEEE Trans. Magn. .vol. 48, no. 2, pp. 863-866. Feb. 2012.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/71f9b4e9aeefd5ad0fbdc3e6fb75fafa.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/d80d0be36065b68335586a8a185383f6.jpg)

 Design and Optimization of New Flux-Concentrating Rotors combining Halbach PM array and spoke-type IPM for PMSM

I. Introduction Interior permanent magnet (IPM) machines are very attractive for the electric vehicle (EV) traction applications due to its excellent performance such as high torque density, and good flux-weakening capability. The multi-layered magnet rotors are more and more adopted in IPM machines, such as the 2008 Lexus LS600H, 2012 Nissan Leaf, 2016 BMW i3, and 2017 Prius which are delta-shape and 2U-shape magnet configuration. A multi-objective tradeoff design method is proposed in a multi-layered IPM machine for EV applications. The multi-objective including the cogging torque, average torque at different loads, torque ripple at different loads, iron loss, and magnet eddy-current loss. Firstly, the single-objective according to the variation of rotor flux-barriers are investigated individually. It is hard to tradeoff design between them, because there have seven targets. Then, a novelty method synthesize the torque on different loads, torque ripple on different loads, and total iron loss which can reduce the targets number from seven to three. The center of gravity of the three points are selected as the eventual angles of rotor flux-barriers. Finally, the multi-layered IPM machine is prototyped and experimented to verify the tradeoff design results. II. Main Body Fig. 1(a) shows the multi-layered magnet configurations. The rib1-rib5 are the bridges and ribs, PMa2 - PMa3 are the angle of magnets, ba1 - ba3 are the angle of barriers. The magnets are inserted in the rotor barriers. Multi-layer magnet has adopted to enhancing saliency ratio for improving reluctance torque. The rated power of the machines is 48 kW, the continuous rated current (rated load) is 200 A, the maximum current (over load) is 400 A, and the maximum speed of the machines is 12000 r/min. The torque ripple is generated by the harmonic interaction of the stator magnetic force harmonic and the rotor magnetic field. It will also cause the vibration, and noise, affecting the comfort of passengers in the EV. In the design of IPM machines, it is desire to minimize the torque ripple. Not only just about the rated load, also about over load condition. The torque ripple at different loads according to the variation of ba3 and ba6 are shown in Fig. 2(a) and Fig. 2(b). The minimum torque ripple under rated load condition is located at point A. The minimum torque ripple under over load condition is located at point B. With different loads, the location of point A, and B are different. To considerate the overall torque ripple, synthesize the rated load, and the over load condition. In the design of IPM machines, it is desire to minimize the core loss and magnet eddy-current loss. The core loss and magnet eddy-current loss at 12000 r/min according to the variation of ba3 and ba6 are shown in Fig. 2(c) and Fig. 2(d). The minimum core loss is located at point C. The minimum magnet eddy-current loss is located at point D. Therefore, it is hard to achieve minimum core loss and magnet eddy-current loss simultaneously. In order to verify the results of the previous analysis, a prototype machine with multi-layered magnet rotor is manufactured. Fig. 1(b) shows photographs of the rotor. The FEA predicted and measured no-load phase EMF at 1500 r/min of multi-layered IPM machines are compared. It can be seen that the measured EMF waveforms consist of three steps corresponding to the pole-arc to pole-pitch ratios of three PM layers, which agrees well with the results of the FEA. The torque and efficiency are measured by a digital meter, the measured results are also agrees well with the results of the FEA. III. Conclusion This paper has presented a multi-objective tradeoff design method in a multi-layered IPM machine for EV traction applications. The novelty method synthesize the torque on different loads, torque ripple on different loads, and total iron loss, which can reduce the targets numbers. The selected of the center of gravity of the three targets can consider the global performances simultaneously, it is a reasonable tradeoff design. It is demonstrated that the effects of angles of rotor flux-barriers on torque ripple and core loss is significant. Therefore, rotor flux-barrier angles is an important issue in the design of multi-layered IPM machine. Finally, the prototype machine with multi-layered magnet rotor is fabricated and experimented.

**References:**

[1] Burak Ozpineci, “Oak Ridge National Laboratory Annual Progress Report for the Electric Drive Technologies Program,” Oak Ridge National Laboratory, ORNL/SR-2016/640, Oct. 2016. [2] Rodrigo Silva, Armin Salimi1, Min Li, “Visualization and Analysis of Tradeoffs in Many-Objective Optimization: A Case Study on the Interior Permanent Magnet Motor Design, ” IEEE Trans. Magn., vol. 52, no. 3, pp. 8102404, Mar. 2016.

**Images:**

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 Multi-Objective Tradeoff Designs of Rotor Flux-Barrier in a Multi-layered IPM Machines for EV Applications

I. Introduction There has been a growing demand for permanent magnet electric machines with high torque and power density per unit current. Furthermore, electric machines are increasingly required to have high efficiency by regulation of energy efficiency. Many optimization algorithms are being studied to achieve high efficiency of IPMSM. Practically, manufactured electric machines can’t expect high performance for all products due to material deviations and dimensional tolerances. Therefore, we must consider the problems that occur while manufacturing to perform an optimization algorithm. However, considering the manufacturing tolerances along with many of the design variables of IPMSM requires a lot of time and cost. Therefore, we propose to apply multiple regression method to improve the performance of the conventional particle swarm optimization (PSO) algorithm. In addition, we can estimate the function formula for the design variables and derive the global solution by using estimated function formula. The convergence speed of the conventional PSO algorithm is improved by using the information of the solution obtained by performing the multiple regression. In addition, we will ensure the robustness of the design by estimating the appropriate regression equation for each design space. II. Particle Swarm Optimization with Multiple Regression Method Since the PSO algorithm finds the optimal solution using the information of each individual, the optimal solution can be found only when the particle moves. In this paper, multiple regression analysis is performed on the accumulation data obtained through the PSO algorithm. Then, an approximate solution can be obtained by using multiple regression. PSO with multiple regression algorithm has the same main loop as conventional PSO algorithm. First, initial particles are created with random locations, and update the velocity and position to find the global solution every iteration. If the amount of data for multiple regression is considered to be sufficient, then regression analysis is performed. We iterate this process until we reach the defined objective function. We selected seven numerical test functions to validate the proposed algorithm. The data obtained from performing the PSO algorithm is used to construct the Multiple Regression Model. Multiple regression is performed within the overall design space, and the result is a rough model. However, it is not a problem because it is used to improve the convergence speed. III. Robust Design Optimization of IPMSM A robust solution is the solution that has the lowest variability of the objective function in the design space that meets the requirements of the objective function. Constraints are needed to solve the problem of finding a robust solution. Constraints are obtained through multiple regression analysis. In particular, in order to consider the variability of design variables, the surrogate model must be configured in all solutions to find a robust solution. However, multiple regression analysis over the entire design space can improve the convergence of the algorithm, but it is challenging to construct an accurate surrogate model. Therefore, we used a method of reducing the design space into limited space that can be explained by multiple regression. A detailed procedure to find a robust solution is as follows. First, perform the modified PSO algorithm to save the data of the particles and find the first solution. When finding a solution, convergence speed is improved by performing multiple regression in the total design space. Second, Construct a multiple regression model around the first solution. The construct region of the multiple regression model limits the region to the adjusted coefficient of determination above 0.95. Multiple regression models verify the variability of the objective function. Third, the first and second process is repeated except for the multiple regression areas obtained in the second section. This procedure is repeated to the extent that it does not violate the constraints of the objective function. We have applied the proposed algorithm to the robust design optimization of IPMSM. We considered the variability of the objective function according to manufacturing tolerances. Target model was selected as IPMSM with eight poles and 48 slots as the target model for driving a vehicle. The constraint condition is over 165 Nm of average torque at 3000 RPM and objective function is minimization of the torque ripple. The central case torque and central case torque ripple are the average torque and torque ripple at the reference point. The worst case torque and worst case torque ripple are the average torque and torque ripple at the design variable values that represent the largest variation within the manufacturing tolerances. As a result of optimization using proposed algorithm, global solution and robust solution were found as shown in Fig. 1, 2. The robust solution has smaller torque ripple variability in Fig. 1. however, global solutions are large variability when considering manufacturing tolerance in Fig. 2. The engineers have the problem of selecting a global solution with higher torque at a similar torque ripple level without considering manufacturing tolerances. However, considering manufacturing tolerances, engineers can choose a robust solution with low variability.

**References:**

B. D. S. G. Vidanalage, M. S. Toulabi, S. Filizadeh, IEEE Transactions on Energy Conversion., vol. 33, p.1547 (2018) C. Ma, L. Qu, IEEE Transactions on Energy Conversion., vol. 30, p.1144 (2015) J. Ou, Y. Liu, R. Qu, IEEE Transactions on Industrial Electronics., vol. 65, p.3772 (2018) J. H. Lee, J. Song, D. Kim, IEEE Transactions on Industrial Electronics., vol. 65, p.1791 (2018) B. Ma, G. Lei, C. Liu, IEEE Transactions on Magnetics., vol. 54, p.8102404 (2018)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/908113e9a2e7b790164fee363a61922d.jpg)
Average torque variability of robust solution

![](https://assets.underline.io/uploads/markdown_image/1/image/65a881435d964a839699329924c44f98.jpg)
Average torque variability of global solution

 Robust Design Optimization Based on Separated Surrogate Model Method for IPMSM

In this paper, a novel global search algorithm tornado optimization (TO) and its hybridization with pattern search method (PSM) are proposed to solve the multimodal optimization problem. The TO enhances capability of global searching with two strategies, intensification strategy and diversification strategy. The hybridization with PSM supports the exact and fast convergence on adjacent optima from the points that are discovered in global search using TO. Outstanding performance of the proposed algorithm is verified by comparison with niching genetic algorithm at the test function and the algorithm is applied to the optimal design of the interior permanent magnet synchronous motor for electric vehicle. I. Introduction To analyze the accurate characteristics of the electric motors for electric vehicle (EV), finite element method (FEM) analysis, which takes a lot of time, is required because of the nonlinear magnetic saturation of the motors [1]. Computational problem of FEM becomes worse when it is applied to the multimodal optimization problem, such as an optimal design of motor. To solve this problem, several algorithms such as niching genetic algorithm (NGA) have been studied. The NGA is an improved algorithm of GA for the multimodal function [2]. However, the NGA still have a problem with calculation time because it takes a lot of function calls to converge to the accurate peak point [3]. To reduce the number of function calls and to enhance the convergence characteristic, this paper proposes the tornado optimization (TO) hybridized with pattern search method (PSM). The TO is an algorithm to search overall area and to designate some points as candidates for several optima. The performance of the algorithm is maximized with the usage of the PSM, which is a kind of deterministic algorithm. II. TORNADO OPTIMIZATION WITH PSM In hybrid algorithm for the multimodal function, adopting strategy and role sharing of each search algorithm are important. Global search algorithm adopts diversification strategy to search overall area and to find undiscovered candidates. On the other hand, local search algorithm converges candidates to each adjacent optimum quickly and precisely by adopting intensification strategy [4]. In TO, the processes of being sucked into tornadoes and searching the opposite side by Zone 1 are employed as intensification strategy. On the other hand, thunder strike of Zone 2 is used as a diversification strategy to prevent particles from being trapped in a local optimum. First, the superior initial particles are generated by Latin hypercube sampling (LHS), which scatters samples evenly, and search each location [5]. With their results, tornadoes occur with their own zones. The rest of particles are sucked into tornado. When they enter the zone of tornado, they will be moved in two ways. As seen in Fig. 1, if they enter in Zone 1 which is the half of the zone, they are swept away by tornado and fly to the opposite side of the tornado. On the other hand, if they enter in Zone 2 which is the inside of the zone, they will be scattered outside the tornado, just as thunder strikes from inside to outside of the real tornado. They will continue to be sucked into the tornado at the relocated area. And then, the searched tornado extends its zone to the location of the absorbed particle. At the same time, the proportion of Zone 2 increases. Zone 1 reduces the number of function calls in advance before the PSM to be executed and helps to find optima hiding beyond the tornado. Zone 2 prevents meaningless re-discovery of discovered tornado and it helps to find new candidates that has not been found yet. In addition, expansion of Zone 2 increases the weight of thunder strikes instead of being swept away. It means that the proportion of diversification strategy increases with each iteration of the search. After repeating this process, new tornadoes occur in potentially optimal candidates recorded during the process. After enough tornadoes are created by TO, those candidates are converged to adjacent optimum by the PSM. The hybridization with the PSM makes TO to find the accurate peak point without being trapped to the local optima [3]. III. VERIFICATION OF PROPOSED ALGORITHM To verify the performance of the proposed algorithm, TO and NGA are applied to the mathematical test function. Test was carried out 100 times with each algorithm. As shown in Fig. 2, there is no doubt that the TO shows outstanding performance than the NGA. The Dstavg means the average distance from the found peak point to the actual peak point. When the function calls of TO and NGA are 1108 and 1380, respectively, the Dstavg of the TO is 72% less than the result of NGA. The TO consumed 19% less function calls than the NGA, even though the accuracy was higher. The application of the TO to the optimal design of the interior permanent magnet synchronous motor (IPMSM) will be covered in full paper. IV. CONCLUSION This paper introduces a novel hybrid algorithm on the purpose of both reducing function call and increasing accuracy of multimodal problem. The outstanding performance of the TO was confirmed through a test function, compared with NGA. The TO was applied to the optimal design for minimizing the cogging torque of IPMSM for EV and successfully derived the optimum model. Acknowledgement This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (Ministry of Science and ICT) (No. 2019R1F1A1061132).

**References:**

[1] M. Caruso, A. O. Di Tommaso, L. Ferraris, 2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)(2017) [2] B.-K. Son, G.-J. Park, J.-W. Kim, IEEE Trans. Magnetics., vol.52, No.3 (2016) [3] Emanuele Dilettoso, Nunzio Salerno, IEEE Trans. Magnetics., vol.42, No.4, pp.1203-1206 (2006) [4] K. Lei, F. Wang, Y. Qiu, Proc. Auto. Decentralized Syst. (ISADS), pp. 513–519 (2005) [5] Y.-R. Kang, J.-C. Son, D.-K. Lim, IEEE Access., vol.8, pp. 117405-117412 (2020)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/64e0812025167577a83918e641bb885b.jpg)
Fig 1. Concept of Tornado Optimization

![](https://assets.underline.io/uploads/markdown_image/1/image/eab6d8aa0606079f102d34d7340fde75.jpg)
Fig 2. Result of test function. (a) TO, (b) NGA

 Tornado Optimization with Pattern Search Method for Optimal Design of IPMSM

This paper focuses on designing a optimal novel structure for high power densitiy of a concentric winding integer slots permanent magnet synchronous motor(PMSM). This research shows the motor design possibility with a higher power density than a typical distributed winding model, within the same size. If the number of slots per phase per pole(NSPP) of PMSM is larger than 1, distributed windings are applied mostly. The distributed winding is a winding method that the number of turns is distributed into each slot according to NSPP. The distributed winding can make a sinusoidal magnetomotive force(MMF) waveform. Also, harmonics can be reduced. Distributed Windings can be classified into lap winding and concentric winding according to the number of pitch of each coil. In lap winding, the number of pitch of each coil is same. On the other hand, the number of pitch of each coil is different maintaining same center of each coil in concentric winding. The distinction between the winding methods is shown in Fig. 1. The concentric winding is divided into identical concentric winding and nonidentical concentric winding according to the number of each coil. Identical concentric winding is that the number of turns in each coil is identical. Nonidentical concentric winding, maintaining a sinusoidal waveform even if the number of turns in each coil is nonidentical, has the advantage of adjusting the number of turns in each coil can obtain a higher winding factor than the lap winding[1-3]. The winding factor is the determinant by the MMF at the air gap and is proportional to the fundamental amplitude of back electromotive force (BEMF)[4-5]. Consequently, the nonidentical concentric winding has potential to enhance a power density of motors according to winding factor. In general, all slots in the stator are the identical shape, so if each coil has a different number of turns, slot fill factors vary from each slot. As a result of slot fill factor differences, some slots are inefficient in utilizing space. It affects the BEMF's fundamental wave amplitude as well, which the output performance of the nonidentical concentric winding motors could be worse than the identical concentric winding one. To improve this problem, we need to design the structure of stator with optimization algorithm to make each slot shape efficiently. In this paper, we study about nonidentical slotted concentric winding in the following ways. A concentric winding integer slots model is selected with 3-phase 4-pole 24-slots PMSM that NSPP is 2. the winding factors of identical concentric winding type and various nonidentical concentric winding types are calculated and compared in case of the number of turns distribution for nonidentical one. nonidentical concentric winding is selected to the winding factor higher than identical concentric winding. For improving the above mentioned problem, a new structure of the stator, nonidentical slotted concentric winding, is optimized and designed. the winding factors of identical concentric winding type and various nonidentical concentric winding types are calculated and compared in case of the number of turns distribution for nonidentical one. Variable shown in Fig. 2. for algorithm is composed of factors which control a slot area. The purpose of optimization is power density and performance. Therefore, objective functions are average torque and torque ripple, and they are minimized as the following two objective function equations. obj1= 1/Tavg obj2= Te, ripple = (Te,max-Te,min)/Te * 100 Te, avg is the average torque and Te, ripple is the torque ripple ratio. Te, max and Te, min are the maximum and minimum of the instantaneous torque, respectively. Through a finite element analysis(FEA) of designed models, we ultimately compared the performance of motor models according to identical concentric winding, nonidentical concentric winding and nonidentical slotted concentric winding. Finally, we propose a novel structure of stator with each different slot areas and nonidentical concentric winding. it is called nonidentical slotted concentric winding. This research shows the motor design possibility with a higher power density than a typical distributed winding model, within the same size.

**References:**

[1] T.A.Lipo, "Introduction to AC Machine Design", University of Wisconsin, pp. 53-82, 2004. [2] M. M. Liwschitz, "Distribution Factors and Pitch Factors of the Harmonics of a Fractional-Slot Winding," in Transactions of the American Institute of Electrical Engineers, vol. 62, no. 10, pp. 664-666, Oct. 1943. [3] G. R. Slemon, A. Straughen “Electric Machines” University of Toronto, pp. 369-383, 1980. [4] Wen Ouyang, A. El-Antably, Surong Huang and T. A. Lipo, "Analysis of optimal stator concentric winding patterns design," 2005 International Conference on Electrical Machines and Systems, Nanjing, vol. 1, pp. 94-98, 2005. [5] J.R. Hendershot, T.J.E.Miller, “Design of Brushless Permanent-Magnet Machines” Magna Physics Publishing & Oxford University Press, pp. 180-181, 2010 [6] J. H. Lee, J. Kim, J. Song, Y. Kim and S. Jung, "A Novel Memetic Algorithm Using Modified Particle Swarm Optimization and Mesh Adaptive Direct Search for PMSM Design," in IEEE Transactions on Magnetics, vol. 52, no. 3, pp. 1-4, March, 2016.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/3cc92d2bebd6cacb0fb22b847ccaf7b1.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/3b059057e1fd0dc89bf8ef5b24adb7fe.jpg)

 A Novel Structure Design about Nonidentical Slotted Concentric Winding

In this paper, subdivided kriging multi objective optimization (SKMOO) is proposed for the optimal design of interior permanent magnet synchronous motor (IPMSM). The SKMOO with inverse searching can obtain uniform and accurate pareto front set with reduced computation cost compared to conventional algorithms. In the SKMOO algorithm, Fill blank method is applied to prevent premature convergence. In addition, the subdivided kriging grid is proposed to make well distributed and precise pareto front set. Superior performance of the SKMOO is confirmed the by compared conventional MOO algorithms with the test function and applied it to the optimal design of IPMSM for electric vehicle. I. Introduction The interior permanent magnet synchronous motor (IPMSM) has the torque caused by the magnet and reluctance torque. Therefore, the IPMSM torque greater than surface mounted PMSM [1]. However, such a permanent magnet type motor has a disadvantage of high cogging torque and torque ripple which causes in the motor’s noise, vibration, and efficiency reduction. This is important to electric vehicle for comfortable driving [2]. Therefore, we aim to design the IPMSM with reduced cogging torque and torque ripple. Finite element method (FEM) analysis is required since the accurate analysis is difficult by using simple mathematical models due to the nonlinear characteristic of the IPMSM [3]. However, the actual motor design using FEM analysis should meet several requirements. It takes a lot of time and effort to simultaneously consider multi objective functions in motor design that require FEM interpretation [4],[5]. To solve this problem, a lot of studies are in progress [6],[7]. The most widely used algorithms are multi objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm-II (NSGA-II). However, the MOPSO and NSGA-II still need many function calls to get the accurate and well distributed pareto front set. Therefore, subdivided kriging multi objective optimization (SKMOO) is proposed which applies the surrogate model to reduce function calls. Outstanding performance of the proposed algorithm is verifyverified through comparison of results with the MOPSO and NSGA-II. And the optimal design was derived by applying the SKMOO to design of the IPMSM with reduced cogging torque and torque ripple. II. Proposed Algorithm MOO performance can be determined based on the accuracy, uniform distribution, and number of function calls while consisting the SKMOO uses the following methods to improve algorithm performance. Pareto front set are extracted from samples using non-dominated sorting and sorted one objective function. The Euclidean distance of adjacent solutions is calculated to obtain a uniform pareto front set and predicted solution is added directly between the two solutions with the longest distance. The spline interpolation is used to increase the accuracy of the solution as shown in Fig. 1. Design variables are inversely searched to generate a real solution. The most similar combination of design variables is found by comparing the objective function value of the surrogate model with the predicted value and the function call is executed to the explored design variables. Fill blank method is used to prevent premature convergence. This method is greatly efficient because it does not overlap the area already explored. When the algorithm converges after the set number of iterations, subdivided kriging grid is proposed to improve performance. The same methods are used to adds solutions, but more accurate solutions can be added because the kriging grid is finely divided. Also, the solution with the closest distance is deleted, if the distance is less than a set distance and if it is more than a set distance, a new solution is added as the intermediate point of before and after solution to obtain more uniform distribution. Fig. 1 shows that the solution is directly added in objective function area. However, the solution is added only at the grid points. Therefore, there is a difference between predicted and real solution. In this case, solutions are uneven and inaccurate. Subdivided grid is a method to solve this problem by dividing kriging grid finely as shown in right of Fig. 1. III. verification of proposed algorithm The SKMOO, the NSGA-II and MOPSO are applied to the test functions. GD indicates how similar the pareto set to the real pareto set and SP indicates how uniformly the solution is distributed. GD and SP value mean better performance if values close to zero. Table. I summarize the results and shows that the SKMOO has superior performance on GD, SP, and the number of function calls than NSGA-II and MOPSO. IV. Conclusion In this paper, SKMOO based on surrogate model is presented to solve MOO problems. The SKMOO can reduce computation cost and show superior performances in the MOO problems. The proposed algorithm is validated by comparing with MOPSO and NSGA-II. Finally, we applied the SKMOO to the optimal design of IPMSM. Taguchi method is used to select variables among several variables that are sensitive to the objective function. The application of the SKMOO to optimal design of the IPMSM will be covered in full paper. V. Acknowledgment This research was supported by Korea Electrotechnology Research Institute (KERI) Primary research program through the National Research Council of Science & Technology (NST) funded by the Ministry of Science and ICT (MSIT) (No. 21A01082).

**References:**

[1] Guo Hong, Tian Wei, and Xiaofeng Ding, IEEE Access, Vol. 6, pp. 23568-23581, (2018). [2] Young-Rok Kang, Ji-Chang Son, and Dong-Kuk Lim, IEEE Access, Vol. 8, (2020). [3] M. Caruso, A. O. Di Tommaso, L. Ferraris, R. Miceli, F. Viola,2017 Twelfth International Conference on Ecological Vehicles and Renewable Energies (EVER)., (2017) [4] Min Li, Fabien Gabriel, Maria Alkadri, IEEE Transactions on Magnetics, Vol. 52, (2016) [5] Siguang An, Shiyou Yang, Osama A. Mohammed, IEEE Transactions on Magnetics, Vol. 54, (2018) [6] Khalil Alkebsi, Wenli Du, IEEE Access., Vol. 8, (2020) [7] Vikas Palakonda, Rammohan Mallipeddi, IEEE Access, Vol. 8, (2020)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/de072cbbc28eead8bddd09747917a1f9.jpg)
Fig.1 Conceptual diagram of SKMOO

![](https://assets.underline.io/uploads/markdown_image/1/image/51d55f48cade1a8cf8b2cc9ec7346562.jpg)
Table. I Test function results

 Optimal Design of IPMSM for EV using Subdivided Kriging Multi Objective Optimization

I. Introduction Due to the outstanding advantages, such as simple structure, high torque density and excellent dynamic performance, permanent magnet motors (PMMs) have been widely applied over the past four decades. Yet, the implementation of PMSM is limited in servo system with high demand for low torque ripple. In this background, the research on how to reduce torque ripple has become a hot spot for many scholars. In order to reduce the high torque ripple of PMM, different methods have been put forward, which can be concluded as rotor skewing, auxiliary slots or teeth, magnet shaping and flux barriers etc. Among these methods, magnet shaping has been developed as an effective method. A rotor consists of several different PM segments arranged in the axial direction is proposed in [1], which is validated by the effectiveness of reducing torque ripple. However, the shape of PM is random and lack of pertinence. By injecting the optimal third harmonic into PM shape, torque performance can be improved with analysis of airgap flux density in [2]. However, only one harmonic is considered into magnet design process. Hence, the influence of different harmonic injection methods on PM shape design is investigated comprehensive in [3], in which various magnet shape is explored to reduce torque ripple. However, the consequents of different initial phase angles of injected harmonics are neglected. In this paper, a magnet design method considering multi-harmonic injection is proposed, which selects an inset-permanent-magnet motor (Inset-PMM) as research subjective. The key of the study is to extensively consider the factor of harmonic phase angle into the design process. Then, based on different harmonic combination and phase angle consideration, two feasible rotor topologies are proposed. Based on the reasonable design, the torque ripple can be reduced effectively, while the motor can also offer a relatively high output torque. II. Motor features and Analysis Inset-PMMs with two optimal phase angle of injected harmonics and four optimal phase angle of injected harmonics are shown in Fig. 1. The principle of initial phase angle of injected harmonics into rotor design process is listed in Fig. 2, which confirms the effectiveness of proposed method. The relationships between torque ripple and different initial phase angle of injected harmonics are given in Fig. 3, meanwhile, the Inset-PMM without phase angle of injected harmonics, considering two optimal phase angle of injected harmonics and four optimal phase angle of injected harmonics are proposed. The comparisons of the initial phase angle of the proposed Inset-PMM are listed in Table I. The flux density, harmonic spectrum, magnetic field distributions and flux distributions of three Inset-PMM are shown in Fig. 4 and Fig. 5, which can be seen that the amplitudes of injected harmonics are almost same. The comparisons of torque performance of three Inset-PMM are presented in Fig. 6, which validates the effectiveness of the proposed method on reducing torque ripple. III. Conclusion Based on the analysis above, the initial phase angle of injected harmonics into rotor design process on torque performance in Inset-PMMs are investigated. Torque ripple is reduced from 37.9% to 13.7% when the factor of harmonic phase angle is considered, the results not only verify the effectiveness of the proposed method on reducing torque ripple, but also prove the validity of the Inset-PMM which can realize the low-cost design and enhance torque capability simultaneously, providing the new orientation for reducing the torque ripple. More detailed electromagnetic performance analysis and FEA results will be presented in the full paper.

**References:**

[1] W. Zhao, T. A. Lipo and B. Kwon, “Material-Efficient Permanent-Magnet Shape for Torque Pulsation Minimization in SPM Motors for Automotive Applications,” IEEE Transactions on Ind Electron., vol. 61, no. 10, pp. 5779-5787, Oct. 2014. [2] K. Wang, Z. Q. Zhu and G. Ombach, "Torque Enhancement of Surface-Mounted Permanent Magnet Machine Using Third-Order Harmonic," IEEE Trans Magn., vol. 50, no. 3, pp. 104-113, March 2014. [3] Y. Zeng, M. Cheng, G. Liu and W. Zhao, "Effects of Magnet Shape on Torque Capability of Surface-Mounted Permanent Magnet Machine for Servo Applications," IEEE Transactions on Ind Electron., vol. 67, no. 4, pp. 2977-2990, April 2020.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/387bb906ffe71557d235a7258b6cb676.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/d920978404cf62639df1c861c4abc923.jpg)

 Design and Analysis of a Low Torque Ripple Inset-Permanent-Magnet Motor Considering Multi-Harmonic Injection

In this paper, internal division point genetic algorithm (IDP-GA) was proposed to lessen the computational burden of multi-variable multi-objective optimization problem using finite element analysis such as optimal design of electric vehicles. The IDP-GA could consider various objectives with normalized weighted sum method and could reduce the number of function calls with novel crossover strategy and vector-based pattern search method. The superiority of the proposed algorithm was verified by comparing performances with conventional optimization method at the test functions. Finally, the applicability of the IDP-GA in practical electric machine design was verified by successfully deriving an improved design of electric bicycle propulsion motor. I. Introduction Electric bicycles (EBs) are getting more attention in many countries for their convenience, long travelling distance and environment friendly features, therefore, EB propulsion motor with low cost and high performance is needed [1]. When designing a motor for EBs, high torque density and improved riding impression is required [2]. Permanent magnet assisted synchronous reluctance motor (PMa-SynRM) has advantage of high torque density as it utilizes both magnet torque and reluctance torque. Also, with the usage of inexpensive ferrite magnet, PMa-SynRM is competitive for the manufacturing cost. Hence, PMa-SynRM is selected for the EB propulsion motor. To relieve the noise and vibration of the motor, various performances such as cogging torque, and torque ripple should be considered, and those characteristics can be adjusted with optimization of the variables related to the structure of the motor [3], [4]. Therefore, optimal design of the PMa-SynRM can be defined as multi-objective multi-variable (MVMO) problem. Finite element analysis (FEA) is required for accurate analysis of electric machines. However, the FEA has the disadvantage of huge computational cost, and such burden becomes more worse when FEA is applied to optimization of MVMO problems. Therefore, this paper proposes the novel optimization algorithm that reduces the number of function calls. II. Proposed Algorithm GA is one of the heuristic algorithms and can successfully converges to the global solution [5]. However, the GA has problem with requiring many function calls to enhance the converge rate and cannot consider various objective functions at once. The IDP-GA reduces function calls with novel crossover strategy and VPSM. Also, multi-objective can be considered with NWSM. The NWSM is one of the multi-objective methods and can simply reduce several objectives to one objective. The total fitness is calculated by multiplying each normalized fitness by assigned weight and adding them all together. The designer can perform optimization by giving the desired weight to each objective with the NWSM. Conventional GA converges to global solution by selecting superior entities as parents and generating crossover on the middle of selected two parents. To enhance the convergence speed, the proposed algorithm applies internal division point (IDP) concept. The IDP literally generates crossover not on the middle point, but on the point divided by objective values of two parents. Fig. 1 shows the difference of conventional approach and IDP. Conventional crossover, which is blue dot, is generated on the center of two parents. However, the location of the red dot is determined considering objective values of parents. With the usage of IDP, superior crossover can be obtained. At the end of the algorithm, if the populations are regarded as gather near the global solution, VPSM is executed on the estimated solution to find the actual global solution, preventing unnecessary function calls, and enhancing convergence characteristic. The VPSM has pattern move and exploration move. On the pattern move step, unit direction vector is determined using objective value of infinitesimal displacement of starting point. Fig. 2(a) shows an example of calculating direction vector. Assuming that the problem region is continuous, with two function calls on the point DX and DY, the values of DX' and DY' can be interpolated. Then, increasing direction of each variable is determined, and the unit direction vector can be calculated. Secondly, as shown in Fig. 2(b), the exploration move is performed on the best particle with preset initial moving distance to determined direction, until the objective value decreases. If the value of next point decreases, pattern move is repeated on the previous point and exploration move with reduced moving distance. To verify the performance, the IDP-GA and conventional GA was applied to two mathematical test functions. The number of function calls of IDP-GA was decreased as 56% and 64% of GA in two tests, and the convergence rate was improved as well. The detailed explain of the IDP-GA, test functions, and application to optimal design of PMa-SynRM for EB will be described in a full paper. III. Conclusion This paper introduces IDP-GA to relieve the computational burden of the MVMO optimization problem applying FEA. The proposed algorithm was validated by applying to mathematical test functions and comparing performance with conventional algorithm. The applicability of the optimization of actual electric machines was also verified by deriving design with improved performances, when the IDP-GA is applied to optimal design of PMa-SynRM for EBs.

**References:**

[1] Y. Li, J. Hu, F. Chen, S. Liu, Z. Yan, and Z. He, IEEE Trans. Power Electronics, vol. 33, no. 10, pp. 8226-8230 (2018) [2] D. Lim, Y. Cho, J. Ro, S. Jung and H. Jung, IEEE Trans. Magnetics, vol. 52, no. 3, pp. 1-4 (2016) [3] Ji-Chang Son, Young-Rok Kang, and Dong-Kuk Lim, Energies, 13, 3395 (2020) [4] Young-Rok Kang, Ji-Chang Son, and Dong-Kuk Lim, IEEE Access, vol. 8, pp. 117405-117412 (2020) [5] K. Lee, H. Oh, S. Jung and Y. Chung, IEEE Trans. Magnetics, vol. 55, no. 6, pp. 1-4 (2019)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b8e7214a83d0a219e82755f99840b3c0.jpg)
Fig. 1. Comparison of conventional crossover and IDP.

![](https://assets.underline.io/uploads/markdown_image/1/image/c333d6a9764d1938e0f61b865a45b939.jpg)
Fig. 2. Conceptual schematic of VPSM. (a) Pattern move. (b) Exploration move.

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