Optimization design method for axial flux permanent magnet wheel motor based on block permanent magnet

Abstract

The application discloses an axial flux permanent magnet synchronous motor optimization design method based on permanent magnet block, comprising the following steps: determining optimization target and optimization parameter; proposing calculation method of eddy current loss, average torque and torque fluctuation; constructing relationship between optimization parameter and optimization target; modeling the axial flux permanent magnet synchronous motor to obtain initial eddy current loss, average torque and torque fluctuation; dividing the permanent magnet into blocks to obtain eddy current loss, average torque and torque fluctuation result data of different block positions and block widths; and performing multi-objective optimization on the motor based on output result data by using swarm intelligence optimization algorithm. The structural optimization method proposed by the application is to perform parameterized analysis on the rotor side permanent magnet block structure, and further optimize the motor by using the swarm intelligence optimization algorithm to further optimize the motor, so as to achieve the purpose of inhibiting eddy current loss, improving average torque and optimizing torque fluctuation.

Description

Technical Field

[0001] The present invention relates to the technical field of axial flux permanent magnet synchronous hub motors, and in particular to an optimization design method of axial flux hub motors based on permanent magnet segmentation. Background Art

[0002] In-wheel hub motors, as a key component of distributed drive systems, have garnered significant attention. Currently, there are two main types of in-wheel hub motors: radial and axial. Radial motors have a radial effective magnetic field and operate through the interaction of radial magnetic fields. They are the most widely used and technologically mature motor structure. Axial motors, on the other hand, have an axial effective magnetic field and operate through the interaction of axial magnetic fields. They offer advantages such as high torque density, high power density, high efficiency, low torque ripple, and smooth operation, making them more suitable for in-wheel hub motors. This has led to the increasing popularity of axial flux motors in recent years. Axial flux motors can be categorized based on the relative position of the stator and rotor and their structural topology: single-rotor single-stator, dual-stator single-rotor, single-stator dual-rotor, and multi-disk axial flux motors. Because the dual-stator single-rotor axial motor structure can offset the unbalanced axial magnetic pull between the stator and rotor, it offers high structural stability and is more suitable for frequent vehicle starts.

[0003] In-wheel motors inevitably experience losses during operation, significantly impacting motor efficiency. These losses primarily come from copper losses, iron losses, and mechanical losses. Iron losses primarily include hysteresis losses, eddy current losses, and residual magnetism losses. Because permanent magnets are a critical component of the motor's magnetic circuit, different permanent magnet structures affect the motor's magnetic energy density and magnetic circuit, further impacting key parameters such as motor losses and torque. Summary of the Invention

[0004] In response to the above-mentioned technical problems to be solved, the present invention provides an optimization design method for an axial flux hub motor based on permanent magnet segmentation, which can reduce the motor's eddy current loss and improve the motor's efficiency after ensuring reasonable output torque and torque fluctuation optimization.

[0005] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0006] An optimization design method for an axial flux hub motor based on permanent magnet segmentation includes the following steps:

[0007] Step S1, determining an optimization target of the axial flux permanent magnet synchronous motor, where the optimization target includes eddy current loss, average torque, and torque ripple;

[0008] Step S2, determining the optimized parameters of the axial flux permanent magnet synchronous motor;

[0009] Step S3, proposing a calculation method for eddy current loss, average torque and torque ripple;

[0010] Step S4, constructing a relationship between the optimization parameters of the axial flux permanent magnet synchronous motor and the optimization target of the axial flux permanent magnet synchronous motor;

[0011] Step S5, modeling the axial flux permanent magnet synchronous motor to obtain the initial eddy current loss, average torque and torque ripple of the axial flux permanent magnet synchronous motor;

[0012] Step S6, dividing the permanent magnets of the axial flux permanent magnet synchronous motor into blocks, and obtaining eddy current loss, average torque and torque fluctuation result data of different block positions and block widths;

[0013] Step S7: converting the output result data into per-unit values, and performing multi-objective optimization on the motor using a swarm intelligence optimization algorithm based on the per-unit values ​​of the output result data.

[0014] As a further improvement of the above technical solution:

[0015] Preferably, in step S2, the optimization parameters include block position and block width.

[0016] Preferably, in step S3, the eddy current loss P(t) of the permanent magnet is e for:

[0017]

[0018] Where r n is the inner radius of the sector permanent magnet (n=1, 2); r i is the outer radius of the sector permanent magnet (i=3, 4); x is the horizontal coordinate; B m is the harmonic magnetic flux amplitude; f is the harmonic magnetic flux frequency; δ pm is the penetration depth of magnetic flux density into the permanent magnet; σ pm is the resistivity of the permanent magnet;

[0019] Preferably, in step S3, the average torque T avg for:

[0020]

[0021] Where p f is the number of pole pairs; N ph is the number of winding turns; T is a time period; r inner 、r outer B is the inner and outer radius of the stator winding; m is the magnetic flux density; I(t) is the stator current; r is the radius.

[0022] Preferably, in step S3, the torque fluctuation K R for:

[0023]

[0024] Where, T max The maximum output torque is: T min is the minimum output torque; T avg is the average torque.

[0025] Preferably, in step S7, the conversion into the average torque per unit value, the eddy current loss per unit value and the torque ripple per unit value is:

[0026]

[0027] Where f1 is the average torque per unit value; T0 is the initial average torque before optimization; T t is the t-th average torque; f2 is the per-unit value of eddy current loss; P0 is the initial eddy current loss before optimization; P t is the t-th eddy current loss; f3 is the per-unit value of torque fluctuation; K0 is the initial torque fluctuation before optimization; K t is the t-th torque fluctuation.

[0028] Preferably, in step S7, a swarm intelligence optimization algorithm is used to perform multi-objective optimization on the motor based on the per-unit value of the output result data as follows:

[0029] F(r3, D1)=ω1·f1-ω2·f2-(1-ω1-ω2)·f3 (14)

[0030] Where F(r3, D1) is the final optimized value, 0<ω1+ω2<1; ω1 is the weight coefficient of f1; ω2 is the weight coefficient of f2.

[0031] The flux permanent magnet synchronous hub motor optimization design method based on permanent magnet segmentation provided by the present invention has the following advantages over the prior art:

[0032] (1) The present invention further suppresses eddy current loss, optimizes average torque, and improves the efficiency of the axial flux permanent magnet synchronous motor by dividing the permanent magnet structure into blocks.

[0033] (2) The present invention reduces eddy current loss by adopting tangential segmentation on the surface of the same magnet, while reducing the amount of permanent magnets used, thereby greatly reducing the cost of the motor. It can also offset the unbalanced axial magnetic pull between the stator and rotor, has high structural stability, and is more suitable for frequent vehicle starts.

[0034] (3) The segmented permanent magnet design of the present invention improves the uniformity of the permanent magnet's magnetic field distribution. This segmented design localizes magnetic field variations, reduces magnetic field gradients, and improves the uniformity of the magnetic field distribution. This uniform magnetic field distribution helps reduce magnetic field fluctuations in the motor, improving motor stability and output torque smoothness.

[0035] (4) The block design of the present invention also helps to reduce the heat concentration effect inside the permanent magnet. In the traditional single-piece permanent magnet structure, due to the uniformity of the magnetic field, eddy current losses caused by magnetic field changes will cause heat concentration inside the entire permanent magnet. The block design localizes the magnetic field changes, so that the heat is more evenly distributed among the small blocks of the permanent magnet, which helps to improve the cooling efficiency, reduce the impact of heat on the permanent magnet, and extend the service life of the permanent magnet. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of the structure of the permanent magnet block of the present invention.

[0037] FIG2( a ) is an exploded view of a quarter structure of the axial motor in the present invention.

[0038] FIG2( b ) is a rear view of FIG2( a ).

[0039] Figure 3 It is a structural schematic diagram of the rotor core of the present invention.

[0040] FIG4( a ) is a schematic diagram of the permanent magnet block form of the present invention.

[0041] FIG4( b ) is a schematic diagram of the permanent magnet and the iron core of the present invention.

[0042] FIG5( a ) is an overall diagram of a quarter structure of the axial motor of the present invention.

[0043] FIG5(b) is a rear view of FIG5(a).

[0044] Figure 6 This is a diagram of the axial motor coil winding arrangement of the present invention.

[0045] FIG7( a ) is a structural diagram of the axial motor coil winding and stator according to the present invention.

[0046] FIG7( b ) is a structural diagram of the axial motor coil winding and stator according to the present invention.

[0047] Figure 8 This is a three-dimensional diagram of the eddy current loss of the axial permanent magnet synchronous motor of the present invention.

[0048] Figure 9 This is a three-dimensional diagram of the torque of the axial permanent magnet synchronous motor of the present invention.

[0049] Figure 10This is a three-dimensional diagram of the torque fluctuation of the axial permanent magnet synchronous motor of the present invention.

[0050] Figure 11 This is a three-dimensional distribution diagram of the torque optimization percentage of the present invention.

[0051] Figure 12 This is a three-dimensional distribution diagram of the optimized percentage of eddy current loss of the present invention.

[0052] Figure 13 This is a three-dimensional distribution diagram of the torque fluctuation optimization percentage of the present invention.

[0053] Figure 14 The three-dimensional distribution diagram of percentages is optimized for the purpose of the present invention.

[0054] Figure 15 This is the initial loss distribution diagram that is not optimized in the present invention.

[0055] Figure 16 The initial torque distribution diagram is not optimized in the present invention.

[0056] Figure 17 This is the eddy current loss distribution diagram after optimizing the structure in the present invention.

[0057] Figure 18 This is the torque distribution diagram after optimizing the structure in the present invention.

[0058] Description of labels:

[0059] 1. Winding; 2. Stator; 3a. Outer row of permanent magnets; 3b. Inner row of permanent magnets; 4. Rotor core. DETAILED DESCRIPTION

[0060] The following is a detailed description of the specific embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention.

[0061] like Figures 1 to 18 As shown, the present invention is based on the optimization design method of the axial flux hub motor with permanent magnet segmentation. By adjusting the motor magnetic flux path and the magnetic field distribution form by segmenting the permanent magnets on the rotor, the suppression of the motor eddy current loss, the optimization of the average torque and the torque fluctuation are calculated.

[0062] Eddy current loss and hysteresis loss are important components of a motor's rotor core loss. When the motor is operating, the magnetic field changes with the current. This change in the magnetic field generates an induced electromotive force in the motor's conductive components (such as the stator and rotor). According to Faraday's law of electromagnetic induction, the generation of the induced electromotive force causes an induced current to flow in the conductor. The induced current forms circulating currents within the conductor, known as eddy currents, which are directed in the opposite direction of the magnetic field change within the conductor. Due to the conductor's resistance, eddy currents generate resistive losses within the conductor. The magnitude of the eddy currents is closely related to the conductor's resistance and geometry. The greater the conductor's resistance, the higher the eddy current loss. The conductor's geometry (such as its thickness, surface area, and shape) also affects the magnitude of the eddy current loss.

[0063] The optimization design method of the present invention further suppresses eddy current loss and improves the efficiency of the axial flux permanent magnet synchronous motor by optimizing the permanent magnet structure and tangentially dividing the permanent magnets. The rotor core 4 is provided with slots for placing permanent magnets. The permanent magnets are divided into inner row permanent magnets 3b and outer row permanent magnets 3a, and are evenly arranged in blocks along the circumferential direction of the rotor; the winding 1 is wound on the stator 2.

[0064] The optimization design method of the present invention specifically comprises the following steps:

[0065] In step S1, an axial flux permanent magnet synchronous motor is selected as the structural optimization object. Since the dual-stator single-rotor axial flux permanent magnet synchronous motor structure can offset the unbalanced axial magnetic pull between the stator and rotor, it has high structural stability and is more suitable for frequent vehicle starts. Therefore, the dual-stator single-rotor axial flux permanent magnet synchronous motor is selected as the structural optimization object. An exploded diagram of one quarter of the dual-stator single-rotor axial flux permanent magnet synchronous motor structure is shown in Figure 2, and the initial parameters of the dual-stator single-rotor axial flux permanent magnet synchronous motor are shown in Table 1.

[0066] Table 1 Determination of initial parameters of dual-stator single-rotor axial flux permanent magnet synchronous motor

[0067]

[0068]

[0069] Step S2, determining the optimization target of the axial flux permanent magnet synchronous motor, the optimization target includes eddy current loss P(t) e , average torque T avg and torque ripple K R .

[0070] Step S3, confirming the optimization parameters of the axial flux permanent magnet synchronous motor, and calculating the suppression of the motor's eddy current loss, the average output torque, and the optimization of the torque fluctuation by dividing the permanent magnets on the rotor into blocks and adjusting the motor's axial flux path and magnetic field distribution.

[0071] The permanent magnets on the rotor are divided into blocks, including the block position r3 and the block width D1 = r2-r3. The permanent magnet block form is as follows Figure 1 and as shown in Figure 4. Figure 1 In the equation, θ is the circular angle of the sector permanent magnet; r n is the inner radius of the sector permanent magnet (n=1, 2); r i is the outer radius of the sector permanent magnet (i=3, 4); l n is the average value of the outer arc length and inner arc length of the sector-shaped permanent magnet (n=1, 2).

[0072] Step S4, eddy current loss P(t) is obtained e Calculation method: Confirm the induced electromotive force E and the equivalent resistance Rpm of the eddy current circuit. According to Faraday's law of electromagnetic induction, the eddy current loss P(t)e can be obtained as shown in formula (1), the induced electromotive force E can be obtained as shown in formula (2), and the magnetic flux area S can be obtained as shown in formula (3).

[0073]

[0074] Where, is the magnetic flux; B(t) is the magnetic induction intensity; θ is the circular angle of the sector permanent magnet; r n is the inner radius of the sector permanent magnet (n=1, 2); r i is the outer radius of the sector permanent magnet (i=3, 4); l n is the average value of the outer arc length and inner arc length of the sector-shaped permanent magnet (n=1, 2).

[0075] Since the permanent magnet is a fan-shaped structure, and the eddy current flow path area of ​​the fan-shaped permanent magnet can be equivalent to a rectangular permanent magnet with the same area, the eddy current flow path area of ​​the fan-shaped permanent magnet is equivalent to a rectangular permanent magnet with the same area as shown in formulas (4), (5), and (6), and then the induced electromotive force E is confirmed as shown in formula (7), and then the equivalent resistance Rpm of the eddy current circuit is confirmed as shown in formula (9). Finally, the eddy current loss P(t)e of the axial flux permanent magnet synchronous motor with permanent magnet blocks is obtained as shown in formula (10).

[0076]

[0077] In the formula, y is the vertical coordinate and x is the horizontal coordinate.

[0078] The sector flux area S is equivalent to the rectangular flux area S′ as shown in formula (6):

[0079]

[0080] Substituting formula (6) into formula (2), the voltage induced by the magnetic field on the magnetic circuit is shown in formula (7):

[0081]

[0082] Where B m is the harmonic magnetic flux amplitude; f is the harmonic magnetic flux frequency.

[0083] The penetration depth of magnetic flux density in permanent magnet is δ pm As shown in formula (8):

[0084]

[0085] Where μ0 is the vacuum permeability; μ pm Permanent magnet relative permeability; σ pm is the resistivity of the permanent magnet.

[0086] The equivalent resistance Rpm of the flat-plate eddy current circuit is shown in formula (9):

[0087]

[0088] Substituting equations (7) and (8) into equation (1), we can obtain the eddy current loss P(t) of the permanent magnet: e for:

[0089]

[0090] Step S5, propose the average torque T avg and torque ripple K R Calculation method, its average torque T avg As shown in formula (11), the torque fluctuation K R As shown in formula (12).

[0091]

[0092] Where p f is the number of pole pairs; N ph is the number of winding turns; T is a time period; r inner 、r outer B is the inner and outer radius of the stator winding; m is the magnetic flux density; I(t) is the stator current; r is the radius.

[0093] The torque fluctuation K under different conditions was analyzed by finite element analysis. R Calculation formula (12):

[0094]

[0095] Where, T max The maximum output torque is: T min is the minimum output torque; T avg is the average torque.

[0096] Step S6, modeling the axial flux permanent magnet synchronous motor, and performing finite element simulation analysis on the axial flux permanent magnet synchronous motor, to obtain the initial eddy current loss P0 of the axial flux permanent magnet synchronous motor before permanent magnet segmentation. Figure 15 As shown, the initial torque T0 is Figure 16 shown.

[0097] Figure 1 Figure 5 is the initial eddy current loss distribution diagram, the maximum eddy current loss is 346.3468mw, and the average is 311.5815mw.

[0098] Figure 1 Figure 6 is the initial torque distribution diagram, with a maximum value of 261.4896 mN·m, an average value of 156.2343 mN·m, and a minimum value of 46.7287 mN·m.

[0099] Step S7, dividing the permanent magnets of the axial flux permanent magnet synchronous motor into blocks, specifically the block position r3 and the block width D1 = r2-r3. Figure 1 As shown in FIG4 , finite element simulation analysis is performed to obtain the eddy current loss P(t) corresponding to different block positions r3 and block widths D1 = r2-r3. e , average torque T avg and torque ripple K R Result data.

[0100] Further, the eddy current loss P(t) of the axial permanent magnet synchronous motor is obtained e Three-dimensional images such as Figure 8 As shown, the average torque T of the axial permanent magnet synchronous motor avg Three-dimensional images such as Figure 9 As shown, the torque fluctuation K of the axial permanent magnet synchronous motor R Three-dimensional images such as Figure 10 As shown, the horizontal coordinates are the block position r3 and the block width D1 = r2-r3, and the vertical coordinates are the eddy current loss P(t) e , average torque T avg and torque ripple K R .

[0101] Step S8: converting the output result data into per-unit values, and performing multi-objective optimization on the motor using a swarm intelligence optimization algorithm based on the per-unit values ​​of the output result data.

[0102] Since the output result data eddy current loss P(t)e , average torque T avg and torque ripple K R The fluctuation value is large and difficult to analyze, so it is processed into per-unit value and converted into the per-unit value of average torque f1, per-unit value of eddy current loss f2, and per-unit value of torque fluctuation f3 as shown in formula (13):

[0103]

[0104] Where T0 is the initial average torque; T t is the tth average torque; P0 is the initial eddy current loss; P t is the tth eddy current loss; K0 is the initial torque fluctuation; K t is the t-th torque fluctuation.

[0105] The three-dimensional graph of the optimized target per unit value and the three-dimensional graph of the average torque per unit value f1 are obtained as follows: Figure 11 As shown, the three-dimensional diagram of the per-unit value of eddy current loss f2 is as follows Figure 12 As shown, the three-dimensional diagram of the torque fluctuation per unit value f3 is as follows Figure 13 As shown, the horizontal coordinates are the block position r3 and the block width D1 = r2-r3, and the vertical coordinates are the average torque per unit value f1, the eddy current loss per unit value f2 and the torque fluctuation optimization per unit value f3.

[0106] Step S9: eddy current loss P(t) e , average torque T avg and torque ripple K R The optimization target is converted into the per-unit value of average torque f1, per-unit value of eddy current loss f2 and per-unit value of torque fluctuation f3. Based on the per-unit value of the output result data, the swarm intelligence optimization algorithm is used to perform multi-objective optimization of the motor as shown in formula (14). The optimal value coordinates are found in MATLAB software as shown in Figure 14 shown.

[0107] F(r3, D1)=ω1·f1-ω2·f2-(1-ω1-ω2)·f3 (14)

[0108] Where F(r3, D1) is the final optimized value where 0<ω1+ω2<1; ω1 is the weight coefficient of the per-unit value f1; ω2 is the weight coefficient of the per-unit value f2.

[0109] Step S10, the optimized parameters obtained after multi-objective optimization are divided into block position r3 and block width D1 = r2-r3, and the eddy current loss is simulated in finite element analysis as follows: Figure 17 As shown and the torque as Figure 18 shown.

[0110] Experimental verification

[0111] Through the above steps, the dual-stator single-rotor axial flux permanent magnet synchronous motor is selected as shown in Table 1. Based on the per-unit value of the output results, the swarm intelligence optimization algorithm is used to perform multi-objective optimization of the motor, and the weight coefficients ω1 = 0.35 and ω2 = 0.5 are set. When r3 = 28.113 mm and D1 = r2-r3 = 4 mm, the optimal value F(r3, D1) is obtained. min =-0.4351, the optimization results are as follows Figure 14 shown.

[0112] like Figure 15 The initial eddy current loss P0 = 311.5815 mW.

[0113] like Figure 16 is the initial average torque T avg0 =156.2343mN·m.

[0114] Initial torque fluctuation:

[0115] like Figure 17 The optimized eddy current loss P avg1 =254.3878mW.

[0116] like Figure 18 is the average torque after optimization T avg1 =281.8331mN·m.

[0117] Torque fluctuation after optimization:

[0118] The eddy current loss P avg1 , average torque T avg1 and torque ripple K R1 The optimization target is converted into the average torque per unit value f1, the eddy current loss per unit value f2 and the torque ripple per unit value f3 and F(r3, D1) is recalculated. min Optimal value:

[0119]

[0120] F(r3, D1)1=ω1·f1-ω2·f2-(1-ω1-ω2)·f3

[0121] =0.35×(-0.8039)-0.55×0.1836-0.1×0.4385=-0.4389

[0122] Error value:

[0123] The error value is relatively small, so the optimization results are consistent with the simulation results.

[0124] The present invention optimizes the permanent magnet structure and tangentially divides the permanent magnets to further suppress eddy current loss, improve the efficiency of the axial flux permanent magnet synchronous motor, and suppress torque fluctuation. The axial flux permanent magnet synchronous motor optimization based on permanent magnet segmentation can optimize the motor torque, torque fluctuation and eddy current loss with multiple objectives by selecting different radial segment positions r3 and radial segment width D1=r2-r3.

[0125] The above examples are merely preferred embodiments of the present invention and are not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, they are not intended to limit the present invention. Therefore, any simple modifications, equivalent variations, and modifications to the above examples that do not depart from the technical solution of the present invention and are based on the technical essence of the present invention shall fall within the scope of protection of the technical solution of the present invention.

Claims

1. An optimization design method for an axial flux hub motor based on permanent magnet segmentation, characterized in that: The following steps are involved: Step S1, determining an optimization target of the axial flux permanent magnet synchronous motor, where the optimization target includes eddy current loss, average torque, and torque ripple; Step S2, determining the optimization parameters of the axial flux permanent magnet synchronous motor; the optimization parameters include block position and block width; Step S3, proposing a calculation method for eddy current loss, average torque and torque ripple; Step S4, constructing a relationship between the optimization parameters of the axial flux permanent magnet synchronous motor and the optimization target of the axial flux permanent magnet synchronous motor; Step S5, modeling the axial flux permanent magnet synchronous motor, and performing finite element simulation analysis on the axial flux permanent magnet synchronous motor to obtain the initial eddy current loss, average torque, and torque ripple of the axial flux permanent magnet synchronous motor before permanent magnet segmentation; Step S6, dividing the permanent magnet of the axial flux permanent magnet synchronous motor into blocks, and performing finite element simulation analysis to obtain eddy current loss, average torque and torque fluctuation result data corresponding to different block positions and block widths; In step S7, the output result data of step S6 is converted into per-unit values ​​according to the initial eddy current loss, average torque and torque fluctuation obtained in step S5, and a swarm intelligence optimization algorithm is used to perform multi-objective optimization on the motor based on the per-unit values ​​of the output result data.

2. The optimization design method of the axial flux hub motor based on permanent magnet segmentation according to claim 1 is characterized in that: In step S3, the eddy current loss of the permanent magnet for: （10） Where, is the inner radius of the sector permanent magnet; is the outer radius of the sector permanent magnet; is the horizontal axis; is the harmonic magnetic flux amplitude; is the harmonic magnetic density frequency; is the penetration depth of magnetic flux density into the permanent magnet; is the resistivity of the permanent magnet; .

3. The optimization design method of the axial flux hub motor based on permanent magnet segmentation according to claim 1 is characterized in that: In step S3, the average torque for: （11） Where, is the pole pair number; is the number of winding turns; For a time period; 、 is the inner and outer radius of the stator winding; is the magnetic flux density; is the stator current; is the radius.

4. The optimization design method of the axial flux hub motor based on permanent magnet segmentation according to claim 1 is characterized in that: In step S3, the torque fluctuation for: （12） Where, The maximum output torque is: is the minimum output torque; is the average torque.

5. The optimization design method of the axial flux hub motor based on permanent magnet segmentation according to claim 1 is characterized in that: In step S7, the average torque, eddy current loss and torque ripple are converted into per-unit values: （13） Where, is the average torque per unit value; is the initial average torque before optimization; is the tth average torque; is the per-unit value of eddy current loss; is the initial eddy current loss before optimization; is the tth eddy current loss; is the per-unit value of torque fluctuation; is the initial torque fluctuation before optimization; is the t-th torque fluctuation.

6. The optimization design method of the axial flux hub motor based on permanent magnet segmentation according to claim 5 is characterized in that: In step S7, a swarm intelligence optimization algorithm is used to perform multi-objective optimization on the motor based on the per-unit value of the output result data: （14） Where, is the final optimized value, ; for Weight coefficient; for Weight coefficient.

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