Design assistance device and design assistance method

Abstract

A design support device (2) is configured to have: a data acquisition unit (11) that acquires a plurality of design candidate data including a plurality of design parameters as candidates for design data of a motor, and acquires a first evaluation value for each of the design candidate data; and a data generation unit (13) that selects, from among the plurality of design candidate data acquired by the data acquisition unit (11), a plurality of upper-order design candidate data having relatively high first evaluation values as first design candidate data, and generates, from each of the first design candidate data, second design candidate data including a plurality of design parameters. The design support device (2) further comprises: an evaluation value calculation unit (14) that calculates a second evaluation value for each of the first design candidate data on the basis of the plurality of design parameters included in each of the first design candidate data, and that calculates a second evaluation value for each of the second design candidate data on the basis of the plurality of design parameters included in each of the second design candidate data; and a design data selection unit (15) that selects, on the basis of the second evaluation value calculated by the evaluation value calculation unit (14), design candidate data used as design data for the motor from among the plurality of first design candidate data and the plurality of second design candidate data.

Description

Technical Field

[0001] The present disclosure relates to a design assistance device and a design assistance method. Background Art

[0002] The design data of the motor includes a plurality of design parameters. The plurality of design parameters include, for example, magnetic flux density, winding temperature, starting current, torque characteristics, allowable constraint time, efficiency, or power factor. The plurality of design parameters may include two or more design parameters having a trade-off relationship. The two or more design parameters having a trade-off relationship affect each other, so the designer of the motor may not be able to easily design the design data.

[0003] There is a design assisting device that assists in designing an electric motor (hereinafter referred to as a “conventional design assisting device”).

[0004] A conventional design support device includes a storage unit and a calculation unit. The storage unit stores a plurality of design candidate data as candidates for design data of an electric motor. Each of the design candidate data includes a plurality of design parameters.

[0005] The calculation unit calculates the evaluation value of each design candidate data based on the plurality of design parameters included in each design candidate data stored in the storage unit. Then, the calculation unit selects the design candidate data with the highest evaluation value from the plurality of design candidate data stored in the storage unit as the design data of the motor.

[0006] However, Patent Document 1 discloses a technique for determining an evaluation function for calculating an evaluation value.

[0007] Prior art literature

[0008] Patent Literature

[0009] Patent Document 1: Japanese Patent Application Publication No. 2014-74994 Summary of the invention

[0010] Problems to be solved by the invention

[0011] The number of design candidate data stored in the storage unit of the existing design assistance device is limited. Therefore, it may happen that design candidate data with an evaluation value higher than the design candidate data stored in the storage unit (hereinafter referred to as "high-evaluated design candidate data") is not stored in the storage unit. In this case, there is a problem that the operation unit cannot select the high-evaluated design candidate data as the design data of the motor. Even if the existing design assistance device uses the technology disclosed in Patent Document 1 to determine the evaluation function for calculating the evaluation value, it may still happen that the high-evaluated design candidate data is not stored in the storage unit.

[0012] The present disclosure has been made to solve the above-mentioned problems, and an object of the present disclosure is to provide a design support device capable of selecting the design candidate data with a higher evaluation value as design data for a motor when there is design candidate data with a higher evaluation value than the design candidate data prepared in advance.

[0013] Means for solving problems

[0014] The design support device disclosed in the present invention comprises: a data acquisition unit, which acquires a plurality of design candidate data including a plurality of design parameters as candidates for design data of the motor, and acquires a first evaluation value of each design candidate data; and a data generation unit, which selects a plurality of upper design candidate data with a relatively high first evaluation value as the first design candidate data from the plurality of design candidate data acquired by the data acquisition unit, and generates second design candidate data including a plurality of design parameters based on each first design candidate data. In addition, the design support device comprises: an evaluation value calculation unit, which calculates a second evaluation value of each first design candidate data based on a plurality of design parameters included in each first design candidate data, and calculates a second evaluation value of each second design candidate data based on a plurality of design parameters included in each second design candidate data; and a design data selection unit, which selects design candidate data used as design data of the motor from the plurality of first design candidate data and the plurality of second design candidate data based on the second evaluation value calculated by the evaluation value calculation unit.

[0015] Effects of the Invention

[0016] According to the present disclosure, when there is design candidate data having a higher evaluation value than the design candidate data prepared in advance, the design candidate data having the higher evaluation value can be selected as the design data of the electric motor. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] [ Figure 1 ] is a structural diagram showing a design support system including a design support device 2 according to embodiment 1.

[0018] [ Figure 2 ] is a hardware configuration diagram showing the hardware of the design support device 2 according to the first embodiment.

[0019] [ Figure 3 ] is a hardware structure diagram of a computer when the design support device 2 is implemented by software or firmware, etc.

[0020] [ Figure 4 ] is a flowchart showing the processing steps of the design support device 2, that is, the design support method.

[0021] [ Figure 5 ] is an explanatory diagram showing an example of the objective function g.

[0022] [ Figure 6 ] Figure 6 A represents N design candidate data x1′~x N ' respectively contains M design parameters g(y m '). Figure 6 B is a diagram showing the first design candidate data z selected by the data generating unit 13. 1，h The M design parameters g(y m ').

[0023] [ Figure 7 ] is a diagram showing the second design candidate data z 2，j An illustration of the generation example (1).

[0024] [ Figure 8 ] is a diagram showing the second design candidate data z 2，j An illustration of the generation example (2).

[0025] [ Fig. 9 ] is a diagram showing the second design candidate data z 2，j An illustration of the generation example (3). DETAILED DESCRIPTION

[0026] Hereinafter, in order to explain the present disclosure in more detail, the mode for implementing the present disclosure will be described with reference to the drawings.

[0027] Implementation Method 1

[0028] Figure 1 1 is a diagram showing a configuration of a design support system including the design support device 2 according to the first embodiment.

[0029] Figure 2 1 is a hardware configuration diagram showing the hardware of the design support device 2 according to the first embodiment.

[0030] exist Figure 1 In the embodiment, the design support system includes a design data storage unit 1, a design support device 2, and a display device 3.

[0031] The design data storage unit 1 is implemented by, for example, nonvolatile or volatile semiconductor memories such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable Programmable Read Only Memory), magnetic disks, floppy disks, optical disks, high-density disks, mini disks, or DVDs (Digital Versatile Discs).

[0032] The design data storage unit 1 stores a plurality of design candidate data as candidates for design data of the motor. Each of the design candidate data includes a plurality of design parameters. The design parameters are design factors of the motor.

[0033] The design candidate data stored in the design data storage unit 1 is, for example, design data of a motor designed in the past. As for the motor to be designed this time and the motor designed in the past, the design data of the motor designed in the past may not be directly used as the design data of the motor to be designed this time due to differences in the environmental conditions or operating conditions in which they are installed.

[0034] Examples of the plurality of design parameters include magnetic flux density, winding temperature, starting current, torque characteristics, allowable constraint time, efficiency, or power factor.

[0035] The magnetic flux density, winding temperature and starting current are design parameters with a design condition that they must not exceed an upper limit value. The torque characteristics, allowable constraint time, efficiency and power factor are design parameters with a design condition that they must not fall below a lower limit value.

[0036] In addition, among the multiple design parameters, there are sometimes two or more design parameters that have a trade-off relationship. For example, when the performance of one of the two or more design parameters is improved, the performance of the other of the two or more design parameters is reduced. The certain design parameter and the other design parameter are in a trade-off relationship. The certain design parameter and the other design parameter affect each other, so the designer of the motor sometimes cannot easily design the design data. For example, efficiency and torque characteristics have a trade-off relationship.

[0037] The design support device 2 is a device that supports the design of the electric motor.

[0038] The design support device 2 includes a data acquisition unit 11 , a preprocessing unit 12 , a data generation unit 13 , an evaluation value calculation unit 14 , and a design data selection unit 15 .

[0039] The display device 3 displays the design candidate data, the first evaluation value, the design data of the motor, and the like on a display (not shown) according to the display data output from the design support device 2 .

[0040] The data acquisition unit 11 performs, for example, Figure 2 It is implemented by the data acquisition circuit 21 shown.

[0041] The data acquisition unit 11 includes a design data conversion unit 11 a .

[0042] The data acquisition unit 11 acquires a plurality of design candidate data from the design data storage unit 1 , and acquires a first evaluation value of each design candidate data from the preprocessing unit 12 .

[0043] The design data conversion unit 11 a converts each design parameter included in each design candidate data by substituting each design parameter into the objective function.

[0044] The objective function is a function that outputs the converted design parameters when the design parameters are substituted. In addition, the objective function is, for example, a function having a minimum value, and is a function in which the first evaluation value is the smallest near the upper limit value within the upper and lower limit range or near the lower limit value within the upper and lower limit range.

[0045] The data acquisition unit 11 outputs a plurality of design candidate data including a plurality of converted design parameters to the preprocessing unit 12 and the data generation unit 13 , respectively, and outputs a first evaluation value of each design candidate data to the data generation unit 13 .

[0046] exist Figure 1 In the design support device 2 shown in the figure, the data acquisition unit 11 includes the design data conversion unit 11 a . However, this is just an example, and the design data conversion unit 11 a may be provided outside the data acquisition unit 11 .

[0047] The preprocessing unit 12 is, for example, Figure 2 This is achieved by the pre-processing circuit 22 shown.

[0048] The pre-processing unit 12 includes an interface unit 12 a .

[0049] The interface unit 12 a is a human-machine interface realized by, for example, a mouse, a keyboard, or a touch panel.

[0050] The interface unit 12 a performs a process of accepting the setting of the desired level of each design parameter acquired by the data acquisition unit 11 and also performs a process of accepting the correction of the desired level.

[0051] Furthermore, the interface unit 12a performs processing for accepting settings of ideal values ​​of various design parameters.

[0052] The preprocessing unit 12 calculates a first evaluation value of each design candidate data using a plurality of design parameters included in each design candidate data acquired by the data acquiring unit 11 , a desired level of each design parameter, and an ideal value of each design parameter.

[0053] The preprocessing unit 12 outputs the first evaluation value of each design candidate data to the data acquiring unit 11 .

[0054] Furthermore, the preprocessing unit 12 generates display data for displaying each design candidate data acquired by the data acquiring unit 11 and the first evaluation value of each design candidate data, and outputs the display data to the display device 3 .

[0055] exist Figure 1 In the design support device 2 shown, the preprocessing unit 12 has the interface unit 12 a . However, this is just an example, and the interface unit 12 a may be provided outside the preprocessing unit 12 .

[0056] In addition, Figure 1 In the design support device 2 shown, the preprocessing unit 12 generates display data for displaying each design candidate data including a plurality of converted design parameters. However, this is only an example, and the preprocessing unit 12 may acquire each design candidate data stored in the design data storage unit 1 from the data acquisition unit 11 and generate display data for displaying each design candidate data.

[0057] In addition, Figure 1 In the design support device 2 shown in the figure, the preprocessing unit 12 calculates the first evaluation value of each design candidate data using the plurality of converted design parameters included in each design candidate data, the expected level of each design parameter, and the ideal value of each design parameter. However, this is only an example, and the preprocessing unit 12 may calculate the first evaluation value of each design candidate data using the plurality of design parameters included in each design candidate data stored in the design data storage unit 1, the expected level of each design parameter, and the ideal value of each design parameter.

[0058] The data generation unit 13 performs, for example, Figure 2 This is achieved by the data generation circuit 23 shown.

[0059] The data generating unit 13 acquires a plurality of design candidate data including a plurality of converted design parameters from the data acquiring unit 11 .

[0060] The data generating unit 13 selects, from among the plurality of design candidate data, a plurality of top design candidate data having relatively high first evaluation values ​​as first design candidate data.

[0061] exist Figure 1 In the design support device 2 shown, the data generating unit 13 acquires a plurality of design candidate data including a plurality of converted design parameters from the data acquiring unit 11. However, this is only an example, and the data generating unit 13 may acquire a plurality of design candidate data stored in the design data storage unit 1 from the data acquiring unit 11.

[0062] The data generating unit 13 generates second design candidate data including a plurality of design parameters based on each first design candidate data.

[0063] Specifically, the data generating unit 13 generates each second design candidate data such that the value of an arbitrary design parameter among a plurality of design parameters included in each second design candidate data is different from the value of the design parameter corresponding to the arbitrary design parameter included in the first design candidate data as the generation source.

[0064] The data generating unit 13 outputs each first design candidate data and each second design candidate data to the evaluation value calculating unit 14 .

[0065] The evaluation value calculation unit 14 performs, for example, Figure 2 This is achieved by the evaluation value calculation circuit 24 shown.

[0066] The evaluation value calculation unit 14 calculates the second evaluation value of each first design candidate data based on a plurality of design parameters included in each first design candidate data selected by the data generation unit 13 .

[0067] The evaluation value calculation unit 14 calculates the second evaluation value of each piece of second design candidate data based on a plurality of design parameters included in each piece of second design candidate data generated by the data generation unit 13 .

[0068] The evaluation value calculation unit 14 outputs each first design candidate data, the second evaluation value of each first design candidate data, each second design candidate data, and the second evaluation value of each second design candidate data to the design data selection unit 15 .

[0069] The design data selection unit 15 is configured by, for example, Figure 2 The design data selection circuit 25 shown is implemented.

[0070] The design data selection unit 15 selects design candidate data to be used as design data of the motor from among the plurality of first design candidate data and the plurality of second design candidate data, based on the second evaluation value calculated by the evaluation value calculation unit 14 .

[0071] The design data selection unit 15 outputs the design data of the electric motor to, for example, a design data management device (not shown).

[0072] Furthermore, the design data selection unit 15 generates display data for displaying the design data of the motor, and outputs the display data to the display device 3 .

[0073] exist Figure 1 In the embodiment, it is assumed that the data acquisition unit 11, the preprocessing unit 12, the data generation unit 13, the evaluation value calculation unit 14 and the design data selection unit 15, which are the structural elements of the design support device 2, are respectively Figure 2 That is, it is assumed that the design support device 2 is implemented by a data acquisition circuit 21, a preprocessing circuit 22, a data generation circuit 23, an evaluation value calculation circuit 24, and a design data selection circuit 25.

[0074] The data acquisition circuit 21, the preprocessing circuit 22, the data generation circuit 23, the evaluation value calculation circuit 24 and the design data selection circuit 25 are, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or a combination thereof.

[0075] The components of the design support device 2 are not limited to those implemented by dedicated hardware, and the design support device 2 may be implemented by software, firmware, or a combination of software and firmware.

[0076] Software or firmware is stored as a program in a computer's memory. Computer means hardware that executes programs, such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a central processing unit, a processing unit, an arithmetic unit, a microprocessor, a microcomputer, a processor, or a DSP (Digital Signal Processor).

[0077] Figure 3 This is a hardware configuration diagram of a computer when the design support device 2 is implemented by software, firmware, or the like.

[0078] When the design support device 2 is implemented by software or firmware, a program for causing a computer to execute each processing step in the data acquisition unit 11, the preprocessing unit 12, the data generation unit 13, the evaluation value calculation unit 14, and the design data selection unit 15 is stored in the memory 31. Then, the processor 32 of the computer executes the program stored in the memory 31.

[0079] In addition, Figure 2In FIG. 1 , an example is shown in which the components of the design support device 2 are respectively implemented by dedicated hardware. Figure 3 , an example is shown in which the design support device 2 is implemented by software or firmware. However, this is just an example, and some components of the design support device 2 may be implemented by dedicated hardware, and the remaining components may be implemented by software or firmware.

[0080] Next, Figure 1 The operation of the design support device 2 shown will be described.

[0081] Figure 4 1 is a flowchart showing the processing procedure of the design support device 2 , that is, the design support method.

[0082] The data acquisition unit 11 acquires N design candidate data x from the design data storage unit 1. n As a candidate for design data of the motor ( Figure 4 Step ST1). n=1, ..., N, where N is an integer greater than 2.

[0083] Design candidate data x n Contains design parameters y m . m=1, ..., M, where M is an integer greater than or equal to 2.

[0084] The design data conversion unit 11a of the data acquisition unit 11 stores, for example, Figure 5 The objective function g is shown.

[0085] Figure 5 : is an explanatory diagram showing an example of the objective function g.

[0086] exist Figure 5 In the figure, the horizontal axis is the design parameter y m The vertical axis is g(y m ').y m ' is the design parameter y m Obtained by normalization.

[0087] like Figure 5 As shown, the objective function g is a function with a minimum value. Figure 5 In the example, after normalization, the design parameter y m 'There is a minimum value near 1.0. However, Figure 5 The waveform of the objective function g shown is deformed and does not completely match the actual waveform.

[0088] exist Figure 5 In the example, the value of the objective function g is the converted design parameter g(y m The upper and lower limits of ') are 0.0 to 1.0. The objective function g is the first evaluation value V nThe function that is smallest near the upper value within the range or near the lower value within the range.

[0089] If the candidate data x is designed n The design parameters y included in m is a value that cannot exceed the upper limit y UP，m The design parameters of such design conditions are as shown in the following formula (1). The design data conversion unit 11a converts the design parameters y into m Normalize. It should not be higher than the upper limit value y UP，m Design parameters of such design conditions are, for example, magnetic flux density, winding temperature or starting current.

[0090] If the candidate data x is designed n The design parameters y included in m is a value that cannot be lower than the lower limit y LO，m The design parameters of such design conditions are as shown in the following formula (2). The design data conversion unit 11a converts the design parameters y into m Normalize. Must not be lower than the lower limit y LO，m Design parameters are, for example, torque characteristics or permissible constraint time.

[0091] In the design parameter y shown in formula (1) m In the normalization of , it is done as follows: if y m =y UP，m , then the normalized design parameter y m 'becomes "1" if y m =y LO，m , then the normalized design parameter y m ' becomes "0".

[0092] In addition, the design parameter y shown in equation (2) m In the normalization of , it is done as follows: if y m =y UP，m , then the normalized design parameter y m ' becomes "0", if y m =y LO，m , then the normalized design parameter y m ' becomes "1".

[0093]

[0094] As shown in the following formula (3), the design data conversion unit 11a converts the design candidate data x n The normalized design parameters y contained in m 'Substitute the objective function g into the normalized design parameter y m'Convert and obtain the converted design parameters g(y m ').

[0095]

[0096] In formula (3), γ m is the threshold value.

[0097] In y LO，m <y m ' <y UP，m Hour, 0 <g(y m ')<1, in y m 'with y UP，m When they are roughly equal, g(y m ') becomes approximately 1.0. In addition, m '>y UP，m When g(y m ') is infinite.

[0098] The data acquisition unit 11 includes the design parameters g(y1′) to g(y2′) converted by the design data conversion unit 11a. M ') design candidate data x n '(n=1, ..., N) is output to the pre-processing unit 12.

[0099] The preprocessing unit 12 acquires the design candidate data x from the data acquiring unit 11 n '(n=1,…,N).

[0100] The interface unit 12a of the preprocessing unit 12 receives the design candidate data x n The normalized design parameters y contained in ' m '(m=1,…,M) expected level f m asp Settings.

[0101] Specifically, for example, if the designer of the motor uses the interface unit 12a to set the design parameter y m 'Expected level m asp The interface unit 12a accepts the expected level f m asp The expected level f m asp It indicates the level expected by the designer, which is higher than the ideal value f m ideal The designer of the motor can obtain M expected levels f1 by using an expected level method such as the satisfaction compromise method. asp ~f M asp .

[0102] In addition, the interface unit 12a receives the design candidate data x n The normalized design parameters y contained in ' m The ideal value of 'f m ideal Settings.

[0103] Specifically, for example, if the designer of the motor uses the interface unit 12a to set the design parameter y m The ideal value of 'f m ideal The interface unit 12a accepts the ideal value f m ideal Settings.

[0104] The preprocessing unit 12 substitutes the converted design parameter g(y) into the evaluation function shown in the following equation (4), for example. m '), expected level f m asp and the ideal value f m ideal , calculate the design candidate data x n 'The first evaluation value V n .

[0105]

[0106] In formula (4), max is the largest value m in () searched among m=1, ..., M and its maximum value is set as V n Mathematical symbols.

[0107] exist Figure 1 In the design support device 2 shown in FIG. 1 , the preprocessing unit 12 calculates the design candidate data x using the evaluation function shown in equation (4). n 'The first evaluation value V n However, this is just an example, and the preprocessing unit 12 may also use an evaluation function other than equation (4) to calculate the first evaluation value V n The evaluation function other than the formula (4) may include, for example, the installation conditions or operation conditions of the motor.

[0108] The preprocessing unit 12 performs the preprocessing according to the first evaluation value V n From high to low, N design candidate data x1'~x N 'Sort and generate design candidate data x1'~x1 for displaying sorted design candidate data N ' display data, and output the display data to the display device 3.

[0109] The display device 3 displays the sorted design candidate data x1′ to x2′ on a display (not shown). N '.

[0110] For example, a designer of an electric motor confirms the sorted design candidate data x1′ to x2′ displayed on the display. N '.

[0111] If N design candidate data x1'~x N ' is not sorted as intended, the motor designer can use the interface 12a to modify the design parameters y m 'Expected level m asp operation.

[0112] If the interface unit 12a receives the expected level f m asp The preprocessing unit 12 uses the corrected expected level f m asp , calculate the design candidate data x again n 'The first evaluation value V n .

[0113] If N design candidate data x1'~x N ' is sorted according to the designer's intention, the pre-processing unit 12 will design candidate data x n 'The first evaluation value V n (n=1, . . . , N) is output to the data acquisition unit 11.

[0114] The data acquisition unit 11 acquires the design candidate data x from the preprocessing unit 12 n 'The first evaluation value V n (n=1,…,N)( Figure 4 Step ST2).

[0115] The data acquisition unit 11 obtains the design candidate data x n ' and the first evaluation value V n Output to the data generation unit 13.

[0116] The data generation unit 13 acquires the design candidate data x from the data acquisition unit 11 n '(n=1, ..., N) and the first evaluation value V n .

[0117] The data generation unit 13 generates N design candidate data x1′ to x N 'Select the first evaluation value V n The relatively high H design candidate data are selected as the first design candidate data z 1，h ( Figure 4 Step ST3). h = 1, ..., H. H is an integer greater than 1.

[0118] Figure 6 A represents N design candidate data x1′~x N ' respectively contains M design parameters g(y m '). Figure 6 In example A, N=5, M=2.

[0119] Figure 6 B is a diagram showing the first design candidate data z selected by the data generating unit 13. 1，h The M design parameters g(y m '). Figure 6 In the example, H=3, M=2.

[0120] exist Figure 6 A and Figure 6 In B, the horizontal axis is the design parameter g(y1'), and the vertical axis is the design parameter g(y2'). n '(n=1, ..., 5), ○ indicates the first design candidate data z 1，h (h=1, 2, 3).

[0121] The circled numbers indicate the first evaluation value V n The evaluation value with a circle number = 1 is the first design candidate data z 1，1 The evaluation value V1 of is the highest among the first evaluation values ​​V1 to V3.

[0122] The evaluation value of the circled number = 2 is the first design candidate data z 1，2 The evaluation value V2 of is the second highest among the first evaluation values ​​V1 to V3. The evaluation value with a circle number = 3 is the first design candidate data z 1，3 The evaluation value V3 is the third highest among the first evaluation values ​​V1 to V3.

[0123] In most cases, the first evaluation value V n High first design candidate data z 1，h The evaluation value of the surrounding design candidate data is greater than that of the first design candidate data z 1，h The evaluation value of the design candidate data at a distance is high.

[0124] The data generation unit 13 generates the first design candidate data z 1，h Generate the second design candidate data z containing M design parameters 2，j (j=1,…,J)( Figure 4 Step ST4). J is an integer greater than 1.

[0125] Specifically, the data generating unit 13 sets the second design candidate data z 2，jThe M design parameters g(y1”) to g(y M ”) in any design parameter g(y m ”) and the first design candidate data z as the generation source 1，h The design parameters g(y m ') is different, the second design candidate data z is generated 2，j .

[0126] The data generating unit 13 generates the first design candidate data z 1，h and the second design candidate data z 2，j The result is output to the evaluation value calculation unit 14 .

[0127] Next, the second design candidate data z generated by the data generating unit 13 is 2，j A specific generation example is described below.

[0128] [Generation example (1)]

[0129] In the case of H = 3, Figure 7 As shown, the data generating unit 13 sets the first design candidate data z 1，1 , the first design candidate data z 1，2 and the first design candidate data z 1，3 Surrounded area.

[0130] Figure 7 The second design candidate data z 2，j An illustration of the generation example (1).

[0131] exist Figure 7 In the figure, the horizontal axis is the first design candidate data z 1，h The design parameters g(y1') and the second design candidate data z 2，j The vertical axis is the design parameter g(y1”) contained in the first design candidate data z 1，h The design parameters g(y2') and the second design candidate data z 2，j The design parameters g(y2”) are included in .

[0132] The black thick line shows the first design candidate data z 1，1 , the first design candidate data z 1，2 and the first design candidate data z 1，3 Here, the black thick line indicates the rectangular area. However, this is just an example. For example, the black thick line may also indicate the first design candidate data z 1，1 , the first design candidate data z 1，2 and the first design candidate data z 1，3Therefore, the data generating unit 13 may also set the H first design candidate data z selected by the data generating unit 13 to 1，1 ~z 1，H The H-shaped areas exist at the vertices respectively.

[0133] Each △ existing in the region is included in the first design candidate data z 1，h Any design parameter g(y m ') Different design parameters g(y m ”) design candidate data. Figure 7 In the example, there are 13 △ in the region.

[0134] exist Figure 7 For example, in the first design candidate data z 1，1 The △ on the left side of contains the value and the first design candidate data z 1，1 The same design parameter g(y2') as the design parameter g(y2') included in , but does not include the same design parameter g(y2") as the first design candidate data z 1，1 The △ includes the same design parameter g(y1') as the design parameter g(y1") included in . Furthermore, the △ includes a design parameter g(y1") whose value is smaller than the design parameter g(y1'), for example, by the resolution of the design parameter g(y1').

[0135] For example, in the first design candidate data z 1，2 The △ on the upper side of contains the value and the first design candidate data z 1，2 The same design parameter g(y1') as the design parameter g(y1') included in , but does not include the same design parameter g(y1") as the first design candidate data z 1，2 The △ includes the same design parameter g(y2') as the design parameter g(y2") included in . Moreover, the △ includes a design parameter g(y2") whose value is larger than the design parameter g(y2'), for example, by the resolution amount of the design parameter g(y2').

[0136] The data generating unit 13 generates all 13 △ existing in the region as the second design candidate data z 2，j (j=1,…,J).

[0137] However, in the second design candidate data z 2，j When the upper limit number of has been determined, the data generation unit 13 selects the first evaluation value V from the 13 △. n The upper limit number of △ with a relatively high number is respectively generated as the second design candidate data z 2，j (j=1, ..., J). In this case, J is the second design candidate data z 2，j The upper limit number of .

[0138] The first evaluation value V for each △ n For example, the data generation unit 13 uses the formula (4) to perform calculations in the same manner as the preprocessing unit 12. In this case, the data generation unit 13 needs to obtain the expected level f from the preprocessing unit 12. m asp and the ideal value f m ideal .

[0139] [Generation example (2)]

[0140] like Figure 8 As shown, the data generating unit 13 sets the first design candidate data z to be surrounded by 1，h The region of (h=1,…,H).

[0141] Figure 8 The second design candidate data z 2，j An illustration of the generation example (2).

[0142] exist Figure 8 In the figure, the horizontal axis is the first design candidate data z 1，h The design parameters g(y1') and the second design candidate data z 2，j The vertical axis is the design parameter g(y1”) contained in the first design candidate data z 1，h The design parameters g(y2') and the second design candidate data z 2，j The design parameters g(y2”) are included in .

[0143] Region (1) surrounds the first design candidate data z 1，1 The area (2) surrounds the first design candidate data z 1，2 In addition, region (3) is a region surrounding the first design candidate data z 1，3 area.

[0144] exist Figure 8 In the example, the sizes of regions (1) to (3) are the same as each other, and regions (1) to (3) each contain 8 △.

[0145] However, this is just an example, and the sizes of the regions (1) to (3) may be different from each other. In addition, the shape of the regions (1) to (3) is not limited to a quadrilateral, and may be a polygon other than a quadrilateral.

[0146] The data generating unit 13 generates all eight deltas existing in the regions (1) to (3) as the second design candidate data z 2，j (j=1,…,J).

[0147] However, in the second design candidate data z 2，jWhen the upper limit number of △ is determined, the data generation unit 13 selects the first evaluation value V from 23 (=8×3-1) △. n The upper limit number of △ with a relatively high number is respectively generated as the second design candidate data z 2，j (j=1, ..., J). The △ at the top left of region (3) overlaps with the △ at the bottom right of region (1). Therefore, here, the first evaluation value V is selected from 23 (=8×3-1) △ instead of 24 (=8×3) △. n In this case, the first evaluation value V for each △ is n For example, the data generation unit 13 performs calculation using equation (4) in the same manner as the preprocessing unit 12 .

[0148] In addition, in the second design candidate data z 2，j When the upper limit number of has been determined, the data generation unit 13 generates a first evaluation value V n (n=1, 2, 3), the number Sel(n) of second design candidate data that can be selected from the regions (1) to (3), respectively, is calculated.

[0149] For example, if the upper limit number is L and 0≤V n ≤1.0, the number Sel(n) is calculated as shown in the following formula (5).

[0150] Sel(n)=L×V n / 1.0 (5)

[0151] For example, if L=10, V1=0.5, V2=0.3, V2=0.2, the data generating unit 13 calculates "5" as the number Sel(1) of the second design candidate data that can be selected from the region (1). In addition, the data generating unit 13 calculates "3" as the number Sel(2) of the second design candidate data that can be selected from the region (2), and calculates "2" as the number Sel(3) of the second design candidate data that can be selected from the region (3).

[0152] In this example, the data generation unit 13 generates a first evaluation value V for each of the eight deltas present in the region (1). n Relatively high Sel(1) (=5) △ are used as the second design candidate data z 2，j .

[0153] Furthermore, the data generating unit 13 generates a first evaluation value V for each of the eight deltas present in the region (2). n Relatively high Sel(2) (=3) △ are used as the second design candidate data z 2，j .

[0154] Furthermore, the data generating unit 13 generates a first evaluation value V for each of the eight deltas present in the region (3). n Relatively high Sel(3) (=2) △ is used as the second design candidate data z 2，j .

[0155] [Generation example (3)]

[0156] In the generation example (2), the data generation unit 13 sets the first design candidate data z 1，h (h=1, ..., H) exist in the center region respectively.

[0157] However, this is just one example. Fig. 9 As shown, the data generating unit 13 may also set the first design candidate data z 1，h (h=1, ..., H) exist in regions (1) to (3) near the region boundaries. Regarding the processing other than the setting of the region, the generation example (3) is the same as the generation example (2).

[0158] Fig. 9 The second design candidate data z 2，j An illustration of the generation example (3).

[0159] exist Fig. 9 In the figure, the horizontal axis is the first design candidate data z 1，h The design parameters g(y1') and the second design candidate data z 2，j The vertical axis is the design parameter g(y1”) contained in the first design candidate data z 1，h The design parameters g(y2') and the second design candidate data z 2，j The design parameters g(y2”) are included in .

[0160] The evaluation value calculation unit 14 obtains the first design candidate data z from the data generation unit 13 1，h (h=1, ..., H) and the second design candidate data z 2，j (j=1,…,J).

[0161] As shown in the following formula (6), the evaluation value calculation unit 14 calculates the first design candidate data z 1，h The normalized design parameters y contained in m '(m=1,…,M), calculate the first design candidate data z 1，h The second evaluation value E 1，h ( Figure 4 Step ST5).

[0162]

[0163] In formula (6), sum is the sum of the values ​​in () of m=1, ..., M, and is set to E. 1，h Mathematical symbols.

[0164] As shown in the following formula (7), the evaluation value calculation unit 14 calculates the second design candidate data z 2，j The design parameters y included in m ”(m=1,…,M), calculate the second design candidate data z 2，j The second evaluation value E 2，j ( Figure 4 Step ST5).

[0165]

[0166] The evaluation value calculation unit 14 calculates the first design candidate data z 1，h (h=1, ..., H), first design candidate data z 1，h The second evaluation value E 1，h , the second design candidate data z 2，j (j=1, ..., J) and the second design candidate data z 2，j The second evaluation value E 2，j Output to the design data selection unit 15.

[0167] The design data selection unit 15 obtains the first design candidate data z from the evaluation value calculation unit 14. 1，h (h=1, ..., H), first design candidate data z 1，h The second evaluation value E 1，h , the second design candidate data z 2，j (j=1, ..., J) and the second design candidate data z 2，j The second evaluation value E 2，j .

[0168] The design data selection unit 15 selects the second evaluation value E 1，h (h=1, ..., H) and the second evaluation value E 2，j (j=1, ..., J), in the first design candidate data z 1，1 ~z 1，H and the second design candidate data z 2，1 ~z 2，J The candidate design data ( Figure 4 Step ST6).

[0169] Specifically, the design data selection unit 15 sets the second evaluation value E 1，1 ~E 1，H , E 2，1 ~E 2，J The highest second evaluation value is determined by comparing them with each other.

[0170] Then, the design data selection unit 15 selects the first design candidate data z 1，1 ~z 1，H and the second design candidate data z 2，1 ~z 2，J The design candidate data corresponding to the highest second evaluation value is selected as the design data of the electric motor.

[0171] The design data selection unit 15 outputs the design data of the electric motor to, for example, a design data management device (not shown).

[0172] Furthermore, the design data selection unit 15 generates display data for displaying the design data of the motor, and outputs the display data to the display device 3 .

[0173] In the above-mentioned first embodiment, the design support device 2 is configured to include: a data acquisition unit 11 that acquires a plurality of design candidate data including a plurality of design parameters as candidates for design data of the motor, and acquires a first evaluation value of each design candidate data; and a data generation unit 13 that selects a plurality of upper design candidate data with a relatively high first evaluation value from the plurality of design candidate data acquired by the data acquisition unit 11 as first design candidate data, and generates second design candidate data including a plurality of design parameters from each first design candidate data. In addition, the design support device 2 includes: an evaluation value calculation unit 14 that calculates a second evaluation value of each first design candidate data based on a plurality of design parameters included in each first design candidate data, and calculates a second evaluation value of each second design candidate data based on a plurality of design parameters included in each second design candidate data; and a design data selection unit 15 that selects design candidate data used as design data of the motor from the plurality of first design candidate data and the plurality of second design candidate data based on the second evaluation value calculated by the evaluation value calculation unit 14. Therefore, when there is design candidate data having a higher evaluation value than the design candidate data prepared in advance, the design support device 2 can select the design candidate data having a higher evaluation value as the design data of the electric motor.

[0174] Furthermore, in the first embodiment, the design support device 2 is configured to include a preprocessing unit 12, which calculates a first evaluation value of each design candidate data using a plurality of design parameters included in each design candidate data acquired by the data acquisition unit 11, a desired level of each design parameter, and an ideal value of each design parameter, and outputs the first evaluation value of each design candidate data to the data acquisition unit 11. Therefore, in the design support device 2, the probability that the top several design candidate data selected by the data generation unit 13 are design candidate data including design parameters with a high probability of achieving the performance desired by the designer increases. In addition, the probability that the second design candidate data generated by the data generation unit 13 are design candidate data including design parameters with a high probability of achieving the performance desired by the designer increases.

[0175] In the first embodiment, the design support device 2 is configured such that the preprocessing unit 12 includes the interface unit 12a that receives the setting of the desired level of each design parameter acquired by the data acquisition unit 11. Therefore, in the design support device 2, the designer can set the desired desired level.

[0176] Furthermore, in the first embodiment, the preprocessing unit 12 generates display data for displaying each design candidate data acquired by the data acquisition unit 11 and the first evaluation value of each design candidate data, and outputs the display data to the display device 3. Furthermore, the design support device 2 is configured such that the interface unit 12a receives the correction of the desired level of each design parameter acquired by the data acquisition unit 11. Therefore, in the design support device 2, for example, the designer can select desired design candidate data as the first design candidate data.

[0177] exist Figure 1 In the design support device 2 shown in FIG. 1 , the design data conversion unit 11 a uses the first evaluation value V n The objective function g is the smallest near the upper limit value within the upper and lower limits or near the lower limit value within the upper and lower limits, and the normalized design parameter y m ' to convert.

[0178] However, this is just an example. After normalization, the design parameter y m In the case where the design parameter y is a design parameter whose value is better if it is greater than the lower limit, the design data conversion unit 11a may use the objective function g shown in the following equation (8) to normalize the design parameter y m 'Convert. As a design parameter, such as efficiency or power factor, the higher the value, the better.

[0179]

[0180] In formula (8), in y m '>yLO,m When g(y m ')<1.

[0181] exist Figure 1 In the design support device 2 shown in FIG. 1 , the evaluation value calculation unit 14 calculates the first design candidate data z according to the formula (6): 1，h The second evaluation value E 1，h , calculate the second design candidate data z according to formula (7) 2，j The second evaluation value E 2，j .

[0182] However, this is just an example, and the evaluation value calculation unit 14 may also calculate the first design candidate data z according to the following formula (9): 1，h The second evaluation value E 1，h , calculate the second design candidate data z according to the following formula (10): 2，j The second evaluation value E 2，j .

[0183]

[0184] In addition, the present disclosure can modify any constituent elements of the embodiments or omit any constituent elements of the embodiments.

[0185] Industrial Applicability

[0186] The present disclosure is applicable to a design assistance device and a design assistance method.

[0187] Description of symbols

[0188] 1: design data storage unit; 2: design auxiliary device; 3: display device; 11: data acquisition unit; 11a: design data conversion unit; 12: preprocessing unit; 12a: interface unit; 13: data generation unit; 14: evaluation value calculation unit; 15: design data selection unit; 21: data acquisition circuit; 22: preprocessing circuit; 23: data generation circuit; 24: evaluation value calculation circuit; 25: design data selection circuit; 31: memory; 32: processor.

Claims

1. A design assistance device, wherein: The design aid has: a data acquisition unit that acquires a plurality of design candidate data including a plurality of design parameters as candidates for design data of the electric motor, and acquires a first evaluation value of each of the design candidate data; a data generating unit that selects a plurality of top design candidate data having relatively high first evaluation values ​​from the plurality of design candidate data acquired by the data acquiring unit as first design candidate data, and generates second design candidate data including the plurality of design parameters based on the first design candidate data; an evaluation value calculation unit that calculates a second evaluation value of each first design candidate data based on a plurality of design parameters included in each first design candidate data, and calculates a second evaluation value of each second design candidate data based on a plurality of design parameters included in each second design candidate data; as well as A design data selection unit selects design candidate data used as design data of the electric motor from among the plurality of first design candidate data and the plurality of second design candidate data based on the second evaluation value calculated by the evaluation value calculation unit.

2. The design assistance device according to claim 1, characterized in that: The data generating unit generates each second design candidate data such that a value of an arbitrary design parameter among a plurality of design parameters included in each second design candidate data is different from a value of a design parameter corresponding to the arbitrary design parameter included in the first design candidate data as a generation source.

3. The design assistance device according to claim 1, characterized in that: The design support device has a preprocessing unit, which uses multiple design parameters contained in each design candidate data acquired by the data acquisition unit, the expected level of each design parameter and the ideal value of each design parameter to calculate the first evaluation value of each design candidate data, and outputs the first evaluation value of each design candidate data to the data acquisition unit.

4. The design assistance device according to claim 3, characterized in that: The preprocessing unit includes an interface unit that receives settings of desired levels of the respective design parameters acquired by the data acquiring unit.

5. The design assistance device according to claim 4, characterized in that: the preprocessing unit generates display data for displaying each design candidate data acquired by the data acquiring unit and the first evaluation value of each design candidate data, and outputs the display data to a display device; The interface unit receives correction of the desired level of each design parameter acquired by the data acquisition unit.

6. A design assistance method, wherein: The data acquisition unit acquires a plurality of design candidate data including a plurality of design parameters as candidates for design data of the electric motor, and acquires a first evaluation value of each of the design candidate data. The data generating unit selects a plurality of top design candidate data having relatively high first evaluation values ​​from the plurality of design candidate data acquired by the data acquiring unit as first design candidate data, and generates second design candidate data including the plurality of design parameters based on each of the first design candidate data. the evaluation value calculation unit calculates a second evaluation value of each first design candidate data based on a plurality of design parameters included in each first design candidate data, and calculates a second evaluation value of each second design candidate data based on a plurality of design parameters included in each second design candidate data, The design data selection unit selects design candidate data used as design data of the electric motor from among the plurality of first design candidate data and the plurality of second design candidate data, based on the second evaluation value calculated by the evaluation value calculation unit.

Images