Cooling media analysis device for predicting coverage of cooling media in rotary electric machine system and rotary electric machine system using the same

Abstract

To optimize a cooling structure of an electric drive system including a rotary electric machine.SOLUTION: Clustering processing of machine learning is applied to coordinate points set in structural elements constituting an electric drive system to group each of the coordinate points into each portion of the electric drive system, and a coverage of cooling media for each portion is automatically obtained from a supply state of the cooling media to the coordinate points belonging to each portion.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a coolant analysis device for predicting a coverage rate of a coolant in a rotating electrical machine system, and to a rotating electrical machine system using the same. [Background technology]

[0002] A technology has been disclosed that estimates the current temperature of the magnet of the rotor core based on the current values ​​of peripheral elements such as the temperature of the stator coil and the temperature of the cooling oil that constitute a rotating electric machine, the current values ​​of peripheral elements of the magnet of the motor core, and the previous estimated value of the temperature of the magnet of the rotor core (Patent Document 1).Also disclosed is a technology that cools an electric motor while suppressing the energy required for cooling (Patent Document 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2018-102102 [Patent Document 2] Japanese Patent Application Laid-Open No. 2013-207957 Summary of the Invention [Problem to be solved by the invention]

[0004] However, when trying to predict the temperature of each part of a rotating electrical machine based on the temperature of the cooling oil, as in Patent Document 1, it is necessary to create in advance a condition in which the cooling oil is reliably applied to the parts inside the motor, which are the main heat source.

[0005] In addition, in conventional technology, when actually cooling a rotating electrical machine, the height of the cooling oil surface is controlled to keep the rotating electrical machine immersed in the cooling oil. However, it is difficult to grasp the overall state of the cooling oil flowing inside the rotating electrical machine by only looking at the cooling oil that accumulates at the bottom of the rotating electrical machine. Furthermore, it is not possible to cool all of the high-temperature parts of the rotating electrical machine by simply managing the height of the cooling oil surface. [Means for solving the problem]

[0006] One aspect of the present invention is a cooling medium analysis device for an electric drive system including a rotating electric machine, which applies a machine learning clustering process to coordinate points set on structural elements that make up the electric drive system to group each of the coordinate points into parts of the electric drive system, and automatically calculates the coverage rate of the cooling medium for each part from the supply state of the cooling medium to the coordinate points that belong to each part.

[0007] Here, the clustering process is preferably performed by applying the k-means method or the k-means++ method.

[0008] Furthermore, it is preferable that the supply state of the cooling medium to the coordinate points is analyzed by computational fluid dynamics (CFD).

[0009] It is also preferable to determine the coverage of the cooling medium for each of the portions in accordance with information on the flow path and supply port of the cooling medium for the electric drive system.

[0010] Another aspect of the present invention is a rotating electric machine system characterized in that the cooling medium analysis device determines the cooling medium coverage rate for each of the parts for a combination of design specifications and operating conditions of the electric drive system, and controls the supply of cooling medium to each of the parts of the electric drive system in accordance with the cooling medium coverage rate for each of the parts.

[0011] Here, it is preferable to generate map data that associates the coverage rate of the cooling medium for each of the parts with combinations of design specifications and operating conditions of the electric drive system, and to control the supply of the cooling medium to each of the parts of the electric drive system by referring to the map data.

[0012] It is also preferable to control the flow rate of the cooling medium to each of the parts of the electric drive system by controlling a valve provided in a flow path of the cooling medium.

[0013] It is also preferable to control the flow rate of the cooling medium to each of the parts of the electric drive system by controlling a pump that supplies the cooling medium.

[0014] Another aspect of the present invention is a rotating electric machine system characterized in that the cooling medium analysis device determines the cooling medium coverage rate for each of the parts for a combination of design specifications and operating conditions of the electric drive system, and controls the output of the electric drive system in accordance with the cooling medium coverage rate for each of the parts. [Effects of the Invention]

[0015] According to the present invention, it becomes easy to optimize the cooling structure of an electric drive system including a rotating electric machine. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a diagram showing a configuration of a rotating electrical machine system according to an embodiment of the present invention; [Figure 2] 1 is a diagram showing an example of the configuration of a vehicle equipped with a rotating electric machine according to an embodiment of the present invention; [Figure 3] 1 is a diagram showing a configuration of a coolant analyzing device according to an embodiment of the present invention. [Figure 4] FIG. 10 is a diagram illustrating a clustering process according to an embodiment of the present invention. [Figure 5] FIG. 4 is a flowchart illustrating a coolant analysis process according to an embodiment of the present invention. [Figure 6] 10A and 10B are diagrams illustrating optimization of the supply of a cooling medium in an embodiment of the present invention. [Figure 7] 10A and 10B are diagrams illustrating optimization of the supply of a cooling medium in an embodiment of the present invention. [Figure 8] 10A and 10B are diagrams illustrating optimization of the supply of a cooling medium in an embodiment of the present invention. [Figure 9] 10A and 10B are diagrams illustrating optimization of the supply of a cooling medium in an embodiment of the present invention. [Figure 10]FIG. 2 is a diagram illustrating an example of a configuration for controlling the supply of a cooling medium according to an embodiment of the present invention. [Figure 11] FIG. 2 is a diagram illustrating an example of a configuration for controlling the supply of a cooling medium according to an embodiment of the present invention. [Figure 12] FIG. 4 is a flowchart illustrating a cooling oil supply control according to the embodiment of the present invention. [Figure 13] FIG. 3 is a diagram showing an example of map data according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0017] 1, a rotating electric machine system 100 according to an embodiment of the present invention includes a rotor 10, a shaft 12, a stator 14, bearings 16, a casing 18, an inverter 20, a battery 22, a control unit 24, an oil pump 26, a motor 28, and an oil pan 29. The rotor 10, the shaft 12, the stator 14, the bearings 16, and the casing 18 constitute a rotating electric machine 101.

[0018] 2 shows an example of a vehicle 200 equipped with a rotating electric machine 101. The vehicle 200 travels by transmitting power output from the rotating electric machine 101, which is a power source, to drive wheels (tires) 108 via a transmission 102, a differential gear 104, and a drive shaft 106.

[0019] The configuration including the rotating electric machine 101, the transmission 102, and the differential gear 104 as structural elements is referred to as an electric drive system. However, the electric drive system only needs to include the rotating electric machine 101, and may also include other structural elements. The following description will be primarily focused on the rotating electric machine 101 to explain the analysis of the cooling medium supply state and the control based on the analysis results, but the same can be applied to other components included in the electric drive system.

[0020] The rotor 10 is a part that rotates in the rotating electric machine 101. The rotor 10 is composed of a rotor core permanent magnet 10a and a rotor core electromagnetic steel plate 10b. The shaft 12 is connected to rotate together with the rotor 10. The shaft 12 is used to transmit the rotational torque output from the rotor 10 to the outside of the rotating electric machine 101. The stator 14 is a part that is stationary relative to the rotor 10 in the rotating electric machine 101. The stator 14 is composed of a stator coil 14a and a stator core electromagnetic steel plate 14b. The rotor 10, shaft 12, and stator 14 are housed in a casing 18. A bearing 16 is arranged between the shaft 12 and the casing 18, allowing the rotor 10 to rotate smoothly together with the shaft 12.

[0021] The voltage and frequency of the power supplied from the battery 22 are adjusted by the inverter 20, and the current flowing through the stator coil 14a of the rotating electric machine 101 is controlled. When the current appropriately controlled by the inverter 20 flows through the stator coil 14a, a rotating magnetic field is created in the stator 14. The magnetic interaction between this rotating magnetic field and the rotor core permanent magnet 10a generates a rotational torque in the rotor 10, causing the rotor 10 to rotate.

[0022] The control unit 24 is also called an on-board computer and includes an arithmetic unit for processing information, a storage unit for storing information, etc. The control unit 24 calculates the torque required for the rotating electric machine 101 based on information such as the accelerator pedal operation amount operated by the driver and the vehicle speed. Then, the control unit 24 issues a command to the inverter 20 to control the current flowing through the stator coil 14a in accordance with the required torque.

[0023] When current flows through the stator coil 14a, a portion of the power is lost, causing the stator coil 14a to heat up. Furthermore, when the rotor 10 rotates, eddy currents flow through the rotor core electromagnetic steel plate 10b, generating heat. To cool the rotating electric machine 101, which is heated by the heat generated by these currents, cooling oil is supplied from an oil pump 26. The oil pump 26 is driven by a motor 28. After absorbing heat from the rotor 10 and the stator 14, the cooling oil is returned to an oil pan 29 and released into the outside air for cooling. A radiator (not shown) may be used to increase the efficiency of heat exchange with the outside air. Alternatively, the heat from the cooling oil may be used to heat another component, such as the battery 22. The cooling oil also functions as a lubricant, smoothing the movement of sliding parts such as the bearings 16.

[0024] Here, in operating the electric drive system, it is extremely important to control the temperature of the rotating electric machine 101 within an appropriate range. If the temperature of the rotor core permanent magnets 10a arranged in the rotor 10 exceeds an allowable value, irreversible demagnetization may occur, in which the magnetic force does not return even after the rotor core permanent magnets 10a are subsequently cooled and the temperature returns to normal. If irreversible demagnetization occurs, the upper limit of the torque that the rotating electric machine 101 can output decreases, and the performance of the rotating electric machine 101 deteriorates. Furthermore, if the temperature of the stator coil 14a exceeds the allowable value, the insulating coating may be destroyed, causing a short circuit, and other damage to the entire electric drive system.

[0025] [Cooling medium analysis device and cooling medium analysis method] The following describes a cooling medium analysis device and a cooling medium analysis method according to this embodiment. In the following description, the cooling medium is assumed to be cooling oil, but the cooling medium is not limited to this and may be any fluid that can provide cooling in an electric drive system including the rotating electric machine 101.

[0026] The coverage rate is one indicator used to quantify the cooling effect of the cooling oil flowing inside the electric drivetrain. The coverage rate of cooling oil is calculated as the percentage of the surface area of ​​each part of the electric drivetrain that is actually covered with cooling oil. If no cooling oil is attached to the surface of each part of the electric drivetrain, the coverage rate is 0%, and conversely, if cooling oil is attached to the entire surface, the coverage rate is 100%. To quickly cool the electric drivetrain, it is desirable to maintain a high coverage rate.

[0027] In this embodiment, a "part" refers to a location within the target electric drive system. For example, a "part" may refer to a group of components or parts of the electric drive system. For example, if the electric drive system is a rotating electric machine 101, a component unit such as the rotor 10, the shaft 12, or the stator 14 may be treated as a single part. Also, a smaller unit such as the rotor core permanent magnet 10a or the rotor core electromagnetic steel plate 10b may be treated as a single part. For example, an even smaller unit such as the center of the rotor core permanent magnet 10a, the center of the stator 14 (stator center), or the coil end of the stator coil 14a may be treated as a single part. The classification of each part can be appropriately designed depending on the purpose. Furthermore, in this embodiment, a "part" may refer to a portion formed by combining multiple parts or parts thereof. For example, the rotor core permanent magnet 10a and the rotor core electromagnetic steel plate 10b may be combined and treated as one part, or the rotor core permanent magnet 10a and a part of the rotor core electromagnetic steel plate 10b may be combined and treated as one part.

[0028] 3, the coolant analysis device 300 can include a processing unit 30, a storage unit 32, an input unit 34, an output unit 36, and a communication unit 38. The coolant analysis device 300 may be a part of the control unit 24, or may be configured separately from the control unit 24.

[0029] The processing unit 30 includes a means for performing calculations, such as a CPU. The processing unit 30 executes a CFD analysis program stored in the storage unit 32 to analyze the cooling oil supply state of the electric drivetrain, and also executes a clustering processing program to perform clustering processing on the results of the CFD analysis. The storage unit 32 includes storage means, such as a semiconductor memory or a memory card. The storage unit 32 is accessible to the processing unit 30 and stores the CFD analysis program, the clustering processing program, and various information required for processing by the processing unit 30. The input unit 34 includes a means for inputting information. The input unit 34 includes, for example, a keyboard, a touch panel, buttons, etc. for receiving input from an administrator. The output unit 36 ​​includes a means for outputting processing results. The output unit 36 ​​includes, for example, a display for outputting processing results, such as a user interface screen (UI). The communication unit 38 includes an interface for communicating with external devices via an information and communication network, such as the Internet or a LAN. Communication by the communication unit 38 may be wired or wireless.

[0030] In order to optimize the cooling structure during the design stage of an electric drive system, a method of analyzing the flow of cooling oil using computational fluid dynamics (CFD) is used. The coverage rate of cooling oil can be calculated from the results of CFD analysis according to design specifications such as the shape of the cooling oil flow path, and operating conditions such as the rotational speed of the rotor of the rotating electric machine 101 and the discharge volume of the pump that delivers the cooling oil.

[0031] In particular, it is easy to group each part in an electric drive system into large sections such as the coil ends of the stator or rotor, the rotor core, etc., and determine the coverage rate for each section. However, if there is a bias in the flow of cooling oil within the electric drive system, and there are areas with high and low coverage rates within a single part such as the coil ends or stator core, it is necessary to organize the enormous amount of data obtained for each coordinate point on the surface of each part in the electric drive system in the CFD analysis.

[0032] For example, the flow rate of cooling oil flowing through coordinate points set on the surface of each part in an electric drivetrain can be immediately determined from the results of a CFD analysis. In contrast, to calculate the coverage rate for each subdivided surface shape, it is first necessary to group and allocate the enormous number of coordinate points set to represent the complex surface shape of each part inside the electric drivetrain into a specified number of parts. However, doing this manually requires a great deal of effort.

[0033] In the coolant analysis of this embodiment, a machine learning clustering method is applied to group a huge number of coordinate points and distribute them to a specified number of parts. Typical examples of machine learning clustering methods include the k-means method and the k-means++ method.

[0034] Figure 4 shows the processing flow of the k-means method, a representative clustering method. In the k-means method, for an infinite number of data points as shown in Figure 4(a), initial reference points for the centroids are given for the number of groups to be organized as shown in Figure 4(b). In this case, the initial reference points for the centroids can basically be random. Then, as shown in Figure 4(c), by calculating the distance between each data point and the centroid, groups are formed for each closest centroid, and the position of the centroid of each group is updated. After repeated searches for the centroids closest to each data point and shifting of the centroids, the centroids hardly shift at all, and the grouping process for the data points is completed, as shown by the dashed boundary in Figure 4(d).

[0035] In this way, by applying clustering methods such as k-means or its improved version, k-means++, it is possible to automatically group large amounts of data points. Therefore, it is possible to quickly process the large amount of data obtained as a result of CFD analysis regarding cooling oil and determine the coverage rate for each subdivided area. Therefore, if a large amount of data regarding the complex surface shape of each part is automatically processed using a machine learning clustering method during the design stage of an electric drive system, it is possible to easily determine the coverage rate of cooling oil in each grouped area, thereby reducing the effort required to optimize the cooling structure.

[0036] FIG. 5 is a flowchart showing a cooling medium analysis process that predicts the coverage of cooling oil in an electric drivetrain by combining CFD analysis and clustering processing.

[0037] In step S10, a process of setting coordinate points (data points) for CFD analysis of the supply of cooling oil is performed. Here, coordinate points indicating the structure of rotating electric machine 101, such as the stator, rotor, and housing, can be set as coordinate points (data points) for the CFD analysis from CAD data obtained in the structural design of the electric drive system.

[0038] In step S12, the supply of cooling oil is analyzed by CFD analysis. In the CFD analysis, the supply state of cooling oil is determined for each coordinate point (each data point) set in step S10 according to design specifications such as the shape of the cooling oil flow path, and operating conditions such as the rotational speed of the rotor of the rotating electrical machine 101 and the discharge rate of the pump that delivers the cooling oil. For example, an analysis is performed to determine whether cooling oil is being supplied to each coordinate point (each data point) set in step S10.

[0039] In step S14, an initial reference point for the center of gravity for the clustering process is set. An initial reference point for the center of gravity is set for each group for which the cooling oil coverage rate is to be calculated within the structure of the electric drivetrain. The initial reference point for the center of gravity may be set randomly, or may be set at a location close to the region for each part to be grouped.

[0040] In step S16, a clustering process is performed to determine the coverage of cooling oil for each part in the electric drivetrain. By applying a clustering method such as the k-means algorithm or its improved version, the position of the center of gravity for the coordinate points (data points) set for the CFD analysis is repeatedly updated, and the coordinate points (data points) are assigned to each group of parts. When the center of gravity converges through the clustering process, the coordinate points (data points) are grouped with respect to each center of gravity, and the grouped coordinate points (data points) are collectively designated as coordinate points (data points) belonging to each part.

[0041] In step S18, the coverage rate of cooling oil for each part is calculated based on the supply state of cooling oil to the coordinate points (data points) belonging to each grouped part. That is, for each grouped part, the coverage rate of cooling oil for the coordinate points (data points) belonging to that part is calculated as [the sum of the number of coordinate points (data points) to which cooling oil is supplied] / [the sum of the number of coordinate points (data points) to which that part belongs].

[0042] 6 to 9 show examples of optimizing the cooling structure based on the coverage rate of the cooling oil. In FIG. 6, cooling oil is applied to the rotating electrical machine 101 through one flow path 40 and an oil hole (cooling oil supply port) 42. In this case, cooling oil is applied to the central portion of the rotor 10 and the stator 14, but not to either side. In this case, if the entire stator 14 is considered as one part, the coverage rate of that part is 30% or less. However, it is not clear how the cooling structure should be modified based on this coverage rate alone.

[0043] Figure 7 shows the stator 14 divided circumferentially into eight groups using a clustering method. As shown in Figure 7, it is clear that the coverage rate of cooling oil varies among the groups. The numerical values ​​shown in Figure 7 indicate the coverage rate of cooling oil among the groups.

[0044] Therefore, the coverage of the cooling oil in each part can be increased by increasing the number of oil holes 42 per flow path 40 as shown in Fig. 8, or by increasing the number of flow paths 40 and oil holes 42 as shown in Fig. 9. This makes it possible to easily carry out a structural design that improves the cooling performance of the cooling oil in each part. Note that, although this embodiment shows an example in which the stator 14 is divided into eight parts, the number of divisions may be changed in actual operation.

[0045] [Cooling oil supply control] By calculating the coverage rate for each finely divided part based on the results of the CFD analysis of the cooling oil, it is possible to determine the flow paths and parts where the cooling oil should be given priority. Below is an example of cooling oil supply control based on the analysis of this coverage rate.

[0046] 10 shows an example of a configuration for controlling the supply of cooling oil. A directional switching valve 44 is provided in the cooling oil flow path 40, and the cooling oil is directed to a flow path that should be prioritized among three flow paths 40 (40a to 40c) in order to improve coverage of each part, such as the rotor 10 and the stator 14. The cooling oil flow path 40 is not limited to this, and other flow paths 40 may be provided. The control unit 24 controls the directional switching valve 44 in accordance with design specifications such as the shape of the cooling oil flow path, and operating conditions such as the rotational speed of the rotor of the rotating electrical machine 101 and the discharge rate of the pump that delivers the cooling oil, to supply the cooling oil to the required parts.

[0047] FIG. 11 shows another example of a configuration for controlling the supply of cooling oil. In this configuration, a flow control valve 46 (46a to 46c) is provided for each of multiple cooling oil flow paths 40 (40a to 40c). This allows the flow rate of cooling oil in the three flow paths 40 (40a to 40c) to be independently controlled to improve coverage of each component, such as the rotor 10 and the stator 14. The cooling oil flow paths 40 and flow control valves 46 are not limited to these, and other flow paths 40 and flow control valves 46 may be provided. The control unit 24 controls the flow control valves 46 in accordance with design specifications such as the shape of the cooling oil flow paths, and operating conditions such as the rotational speed of the rotor of the rotating electrical machine 101 and the discharge rate of the pump that delivers the cooling oil, thereby supplying the required flow rate of cooling oil to the required components.

[0048] 12 shows a flowchart of the cooling oil supply control. Hereinafter, the cooling oil supply control process will be described with reference to the flowchart of FIG.

[0049] In step S20, data indicating the state of the electric drive system during operation, such as the rotational speed of the rotor 10, the rotational torque of the rotor 10, the current value, the voltage value, the temperature of the rotating electric machine 101, the temperature of the cooling oil (oil temperature), and the air temperature around the vehicle, is acquired. Regarding the temperature of the rotating electric machine 101, a temperature sensor can be attached to the stator 14 or the like, and data can be acquired from that sensor. In addition, the temperature of each part of the rotating electric machine 101 can also be estimated or predicted based on data obtained from other sensors.

[0050] In step S22, the current cooling oil coverage rate for each part in the electric drivetrain is calculated based on the data obtained in step S20. The required coverage rate is also calculated. The required coverage rate for each part may be set in advance for each state of the electric drivetrain. The difference between the current cooling oil coverage rate and the required coverage rate is also calculated.

[0051] In step S24, the flow rate of cooling oil to be supplied to each part is determined based on the current coverage rate of cooling oil at each part. That is, the flow rate is set so as to increase or decrease the flow rate of cooling oil by the difference between the current coverage rate of cooling oil at each part and the required coverage rate.

[0052] In step S26, the flow rate of cooling oil to each part is actually controlled according to the flow rate set in step S24. Specifically, the operation amount of the directional control valve 44 and the operation amount of the flow control valve 46 are calculated, and control is performed according to the calculated values. Note that the flow rate of cooling oil may be controlled not only by operating the valves but also by adjusting the discharge rate of the oil pump 26.

[0053] When the rotating electric machine 101 is operated continuously at high output, the electric drive system can be cooled quickly by concentrating the flow of cooling oil in areas where a high coverage rate of cooling oil is required. On the other hand, if the coverage rate exceeds the required value due to overlapping of cooling oil from multiple flow paths, the flow rate of the cooling oil can be reduced, reducing the drag loss of the cooling oil and the loss of the oil pump 26, thereby improving the fuel and electricity efficiency of the vehicle.

[0054] The above-described CFD analysis and clustering process may be performed by an on-board computer such as the control unit 24. In this case, it is preferable to use the on-board computer to operate the system while improving the analytical performance so that the value of the cooling oil coverage rate coincides with the oil application state on the rotating electrical machine 101, or so that the predicted cooling effect coincides with the actual effect.

[0055] Furthermore, to reduce the calculation load on the onboard computer, parameters required for controlling the supply of cooling oil, such as the operation amounts of valves, pumps, etc., may be converted into map data based on the value of the cooling oil coverage rate of each part calculated in advance for each operating condition of the electric drivetrain, as shown in Figure 13. In this case, when the electric drivetrain is operating, the supply of cooling oil can be controlled by referring to the parameter values ​​in the map data corresponding to the operating conditions of the electric drivetrain. The map data is multidimensional data that takes the required coverage rate, motor torque, rotor rotation speed, cooling oil temperature (oil temperature), air temperature around the vehicle, etc. as input data and outputs the amount of cooling oil supplied to each part.

[0056] Furthermore, the output and efficiency of the electric drive system may be controlled based on the value of the coverage rate of cooling oil for each part calculated in advance for each operating condition of the electric drive system. For example, when the coverage rate of cooling oil for each part calculated in advance for each operating condition of the electric drive system is sufficient, the output from the rotating electric machine 101 may be allowed to be at its maximum, and when the coverage rate of cooling oil for each part is insufficient, the output from the rotating electric machine 101 may be limited. This allows the operating efficiency of the electric drive system to be controlled.

[0057] According to this embodiment, it becomes easy to optimize the cooling structure of the electric drive system including the rotating electric machine 101. As a result, the maximum output and continuous operation time of the electric drive system are significantly improved compared to conventional systems, and the running performance of a vehicle equipped with a rotating electric machine is improved. In addition, the flow rate of the cooling fluid required for cooling during operation can be reduced. As a result, losses during operation are reduced, and fuel economy and electricity cost are improved. In addition, various controls, such as supply control of the cooling medium in the electric drive system, can be effectively performed.

[0058] [Configuration of the present invention] [Configuration 1] A cooling medium analysis device for an electric drive system including a rotating electric machine, A cooling medium analysis device characterized by applying machine learning clustering processing to coordinate points set on structural elements that make up the electric drive system to group each of the coordinate points into parts of the electric drive system, and automatically determining the coverage rate of the cooling medium for each part from the supply status of the cooling medium to the coordinate points that belong to each part. [Configuration 2] The coolant analysis device according to configuration 1, The cooling medium analysis device is characterized in that the clustering process is performed by applying the k-means method or the k-means++ method. [Configuration 3] The coolant analysis device according to configuration 1 or 2, A cooling medium analysis device characterized in that the supply state of the cooling medium to the coordinate point is analyzed by computational fluid dynamics (CFD). [Configuration 4] The coolant analysis device according to any one of configurations 1 to 3, A cooling medium analysis device that determines a coverage rate of the cooling medium for each of the portions in accordance with information on the flow paths and supply ports of the cooling medium of the electric drive system. [Configuration 5] determining a coverage rate of the coolant for each of the portions for a combination of design specifications and operating conditions of the electric drive system by the coolant analysis device according to any one of configurations 1 to 4; A rotating electrical machine system, characterized in that the supply of cooling medium to each of the parts of the electric drive system is controlled in accordance with a coverage rate of the cooling medium for each of the parts. [Configuration 6] A rotating electric machine system according to configuration 5, generating map data that associates a coverage rate of the cooling medium for each of the portions with a combination of design specifications and operating conditions of the electric drive system; A rotating electrical machine system, characterized in that the supply of cooling medium to each of the components of the electric drive system is controlled by referring to the map data. [Configuration 7] The rotating electric machine system according to configuration 5 or 6, A rotating electrical machine system, characterized in that a flow rate of the cooling medium for each of the parts of the electric drive system is controlled by controlling a valve provided in a flow path of the cooling medium. [Configuration 8] The rotating electric machine system according to configuration 5 or 6, A rotating electrical machine system, characterized in that a flow rate of the cooling medium for each of the components of the electric drive system is controlled by controlling a pump that supplies the cooling medium. [Configuration 9] determining a coverage rate of the coolant for each of the portions for a combination of design specifications and operating conditions of the electric drive system by the coolant analysis device according to any one of configurations 1 to 4; A rotating electrical machine system, characterized in that an output of the electric drive system is controlled in accordance with a coverage rate of the cooling medium for each of the parts. [Explanation of symbols]

[0059] 10 rotor, 10a rotor core permanent magnet, 10b rotor core electromagnetic steel plate, 12 shaft, 14 stator, 14a stator coil, 14b stator core electromagnetic steel plate, 16 bearing, 18 casing, 20 inverter, 22 battery, 24 control unit, 26 oil pump, 28 motor, 29 oil pan, 30 processing unit, 32 memory unit, 34 input unit, 36 output unit, 38 communication unit, 40 flow path, 40 (40a to 40c) flow path, 42 oil hole, 44 directional switching valve, 46 flow control valve, 46 (46a to 46c) flow control valve, 100 rotating electric machine system, 101 rotating electric machine, 102 transmission, 104 differential gear, 106 drive shaft, 108 driving wheel (tire), 200 vehicle, 300 Cooling medium analysis equipment.

Claims

1. A cooling medium analysis device for an electric drive system including a rotating electric machine, A cooling medium analysis device characterized by applying machine learning clustering processing to coordinate points set on structural elements that make up the electric drive system to group each of the coordinate points into parts of the electric drive system, and automatically determining the coverage rate of the cooling medium for each part from the supply status of the cooling medium to the coordinate points that belong to each part.

2. 2. The coolant analysis device according to claim 1, The cooling medium analysis device is characterized in that the clustering process is performed by applying the k-means method or the k-means++ method.

3. 3. The coolant analysis device according to claim 1, A cooling medium analysis device characterized in that the supply state of the cooling medium to the coordinate points is analyzed by computational fluid dynamics (CFD).

4. 2. The coolant analysis device according to claim 1, A cooling medium analysis device that determines a coverage rate of the cooling medium for each of the portions in accordance with information on the flow paths and supply ports of the cooling medium of the electric drive system.

5. determining a coverage rate of the coolant for each of the portions for a combination of design specifications and operating conditions of the electric drive system by using the coolant analysis device according to claim 1; A rotating electrical machine system, characterized in that the supply of cooling medium to each of the parts of the electric drive system is controlled in accordance with a coverage rate of the cooling medium for each of the parts.

6. 6. The rotating electrical machine system according to claim 5, generating map data that associates a coverage rate of the cooling medium for each of the portions with a combination of design specifications and operating conditions of the electric drive system; A rotating electrical machine system, characterized in that the supply of cooling medium to each of the components of the electric drive system is controlled by referring to the map data.

7. 7. The rotating electrical machine system according to claim 5, A rotating electrical machine system, characterized in that a flow rate of the cooling medium for each of the parts of the electric drive system is controlled by controlling a valve provided in a flow path of the cooling medium.

8. 7. The rotating electrical machine system according to claim 5, A rotating electrical machine system, characterized in that a flow rate of the cooling medium for each of the components of the electric drive system is controlled by controlling a pump that supplies the cooling medium.

9. determining a coverage rate of the coolant for each of the portions for a combination of design specifications and operating conditions of the electric drive system by using the coolant analysis device according to claim 1; A rotating electrical machine system, characterized in that an output of the electric drive system is controlled in accordance with a coverage rate of the cooling medium for each of the parts.

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