Method and device for predicting steady-state temperature of motor stator

Abstract

The invention discloses a prediction method and a prediction device for the steady-state temperature of a motor stator. The prediction method comprises the following steps: acquiring a plurality of actually measured temperatures of the motor stator in a preset operation period; wherein the duration of the preset operation time period is smaller than the operation duration of the motor stator from the initial temperature to the steady-state temperature; obtaining a prediction model of the prediction temperature and the operation duration of the motor stator; wherein the parameters of the prediction model comprise an initial temperature, a steady-state temperature and at least one constant coefficient; acquiring initial values of the initial temperature, the steady-state temperature and the constant coefficient; according to the prediction model, the initial temperature, the initial temperature, the steady-state temperature and the initial value of the constant coefficient, obtaining a plurality of predicted temperatures in one-to-one correspondence with the actually measured temperatures of the motor stator in the preset operation period; and according to the actually measured temperature and the predicted temperature, determining the predicted value of the steady-state temperature of the prediction model and the optimal value of the constant coefficient. The temperature rise test efficiency can be improved, the energy consumption can be reduced, and the accuracy of the predicted value of the steady-state temperature can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of motor testing, and in particular to a method and a device for predicting the steady-state temperature of a motor stator. Background Art

[0002] Motor temperature rise test is an important indicator to judge whether the motor insulation material and production process can meet the normal operation and R&D design life of the motor.

[0003] In the actual temperature rise test process, the tested permanent magnet synchronous motor is usually required to run from cold state to thermal stable condition under stable load, which wastes a lot of time and energy in the temperature rise test of the motor in the R&D stage. In addition, considering the uncertainty of the electromagnetic scheme and production process of the newly developed prototype, especially for the high-power, high-power density permanent magnet synchronous prototype, when running to thermal stable condition, the temperature rise may be too high to damage the motor, causing irreparable losses.

[0004] Therefore, how to solve the problems of low efficiency and high energy consumption in temperature rise testing has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] The present invention provides a method and device for predicting the steady-state temperature of a motor stator, so as to solve the problems of low efficiency and high energy consumption in temperature rise testing.

[0006] According to one aspect of the present invention, a method for predicting the steady-state temperature of a motor stator is provided, comprising:

[0007] Acquire multiple measured temperatures of the motor stator in a preset operating period; wherein the duration of the preset operating period is less than the operating time for the motor stator to reach a steady-state temperature from an initial temperature;

[0008] Obtaining a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the parameters of the prediction model include the initial temperature, the steady-state temperature and at least one constant coefficient;

[0009] Acquire an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient;

[0010] According to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, a plurality of predicted temperatures of the motor stator in the preset operating period are obtained; the plurality of predicted temperatures correspond one to one with the plurality of measured temperatures;

[0011] According to the measured temperature and the predicted temperature, the predicted value of the steady-state temperature of the prediction model and the optimal value of the constant coefficient are determined.

[0012] Optionally, the prediction model includes:

[0013] T(t)=(ad)×f(t)+d;

[0014] Wherein, t is the theoretical operating time, T(t) is the predicted temperature; a is the initial temperature; d is the steady-state temperature; f(t) is a functional relationship with the theoretical operating time, f(t) includes at least one constant coefficient, and f(0)=1, f(∞)=0.

[0015] Optionally, f(t) = 1 / [1+(t / c) b ];

[0016] Wherein, b and c are both constant coefficients.

[0017] Optionally, obtaining an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient includes:

[0018] Get the initial values ​​of a, b, c, and d; wherein the initial values ​​of a, b, c, and d are all positive numbers, and a<b.

[0019] Optionally, determining the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature includes:

[0020] According to the plurality of measured temperatures and the plurality of predicted temperatures that correspond one to one, respectively, a sum of squares of differences between all corresponding measured temperatures and predicted temperatures is obtained;

[0021] The sum of the squares of the differences is defined as the minimum value, the steady-state temperature and the constant coefficient are defined as variables, and a planning solution is performed;

[0022] The steady-state temperature obtained by the planning solution is determined as the predicted value of the steady-state temperature, and the constant coefficient obtained by the planning solution is determined as the optimal value of the constant coefficient.

[0023] Optionally, determining the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature includes:

[0024] According to the plurality of measured temperatures and the plurality of predicted temperatures that correspond one to one, respectively, a sum of squares of differences between all corresponding measured temperatures and predicted temperatures is obtained;

[0025] The sum of the squares of the differences is defined as the minimum value, the steady-state temperature and the constant coefficient are defined as variables, and a planning solution is performed;

[0026] Averaging the minimum values ​​of the sum of squared differences obtained by the planning solution to obtain an average value of the squared differences;

[0027] When the average value of the square of the difference is less than or equal to a first threshold, determining the steady-state temperature obtained by the planning solution as the predicted value of the steady-state temperature, and determining the constant coefficient obtained by the planning solution as the optimal value of the constant coefficient;

[0028] When the average value of the square of the difference is greater than the first threshold, the duration of the preset operating period is increased by a preset increment, and the step of obtaining multiple measured temperatures of the motor stator in the preset operating period is returned to until the average value of the sum of the square of the difference is less than or equal to the first threshold or the duration of the preset operating period is greater than or equal to the second threshold.

[0029] Optionally, also include:

[0030] Determining an optimal prediction model according to the initial value of the initial temperature, the predicted value of the steady-state temperature and the optimal value of the constant coefficient;

[0031] According to the optimal prediction model, a predicted value of the running time for the motor stator to reach a preset temperature from an initial temperature is determined; wherein the preset temperature is less than the predicted value of the steady-state temperature.

[0032] According to another aspect of the present invention, there is provided a device for predicting the steady-state temperature of a motor stator, comprising:

[0033] A measurement module, used to obtain a plurality of measured temperatures of the motor stator in a preset operation period; wherein the duration of the preset operation period is less than the operation duration for the motor stator to reach a steady-state temperature from an initial temperature;

[0034] A modeling module, used to obtain a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the prediction model includes the initial temperature, the steady-state temperature and at least one constant coefficient;

[0035] An assignment module, used for obtaining an initial value of the initial temperature, an initial value of the steady-state temperature and an initial value of the constant coefficient;

[0036] A first calculation module, for obtaining a plurality of predicted temperatures of the motor stator in the preset operating period according to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient; the plurality of predicted temperatures correspond one-to-one to the plurality of measured temperatures;

[0037] A prediction module is used to determine the predicted value of the steady-state temperature of the prediction model and the optimal value of the constant coefficient according to the measured temperature and the predicted temperature.

[0038] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0039] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for predicting the steady-state temperature of the motor stator as described in any embodiment of the present invention.

[0040] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for predicting the steady-state temperature of a motor stator as described in any embodiment of the present invention when executed.

[0041] The technical solution of the present invention can optimize the prediction model by obtaining multiple measured temperatures of the motor stator in a preset operating period and calculating multiple predicted temperatures of the motor stator in a preset operating period through a prediction model, and predict the temperature value of the motor stator when the motor runs to a thermally stable condition according to the optimized prediction model. There is no need to control the motor to actually run to a thermally stable condition, which can greatly shorten the test time, save energy consumed in the test, improve test safety, reduce risks, and avoid the steady-state temperature of the motor stator being too high when the motor actually runs to a thermally stable condition, thereby damaging the motor and causing irreparable losses.

[0042] In addition, the prediction model includes an initial temperature and a steady-state temperature, as well as at least one constant coefficient, which can make the predicted temperature obtained by the prediction model more accurate and obtain a more accurate predicted value of the steady-state temperature. The constant coefficient can be adjusted according to the test object, test conditions or test environment so that the predicted temperature obtained by the prediction model is closer to the actual measured temperature, which is conducive to improving the accuracy of the prediction model.

[0043] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0045] Figure 1 is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in Embodiment 1 of the present invention;

[0046] Figure 2 is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in Embodiment 2 of the present invention;

[0047] Figure 3 is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in Embodiment 3 of the present invention;

[0048] Figure 4 It is a structural schematic diagram of a device for predicting the steady-state temperature of a motor stator provided by a fourth embodiment of the present invention;

[0049] Figure 5 A schematic diagram of the structure of an electronic device that can be used to implement an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0051] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0052] Embodiment 1

[0053] Figure 1This is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in the first embodiment of the present invention. This embodiment can be applied to the temperature change of a motor from an initial state to a steady state during production or research and development. The method can be executed by a prediction device for the steady-state temperature of a motor stator. The prediction device can be implemented in the form of hardware and / or software. The prediction device can be configured in a prediction system for the steady-state temperature of a motor stator. Figure 1 As shown, the method includes:

[0054] S1001. Acquire multiple measured temperatures of a motor stator in a preset operating period; wherein the duration of the preset operating period is shorter than the operating time for the motor stator to reach a steady-state temperature from an initial temperature.

[0055] Among them, the motor stator is the fixed part of the motor, which is mainly composed of the stator core and the stator winding.

[0056] The operating period refers to the actual operating period of the motor from one state to another state. For example, it can be the period when the motor stator runs from the initial temperature to a temperature lower than the steady-state temperature. For example, it can also be the period after the running motor switches from one load to another (the load of the motor has stabilized) but has not yet reached the thermal stability condition.

[0057] The measured temperature refers to the temperature value of the motor stator actually measured. For example, an embedded thermometer method can be used to pre-embed a thermal resistor sensor at the end of the motor stator winding to collect the stator winding temperature.

[0058] In an optional embodiment, the actual temperature of the motor stator during the preset operation period and every m minutes of operation can be obtained, wherein m is an integer. Specifically, the temperature value of the motor stator is collected once every m minutes as the actual temperature.

[0059] In another optional embodiment, each time the measured temperature is collected, the same collection cycle may be used, and multiple temperature values ​​may be collected within the collection cycle, and the average value of the temperature values ​​within the same collection cycle may be used as the measured temperature obtained this time, so as to improve the accuracy of the measured temperature. For example, the collection cycle may be 5 seconds, 20 temperature values ​​may be collected within 5 seconds, and the average value of the 20 temperature values ​​may be used as the measured temperature collected this time.

[0060] In another optional embodiment, an average weighted method can be used to smooth the measured temperature obtained each time. For example, the smoothed measured temperature Y n =(X n-1 *p+X n +X n+1 *q) / 2, which can eliminate the interference of equipment, environment and other factors on the stator temperature during the acquisition process.

[0061] Among them, Xn-1 , X n , X n+1 represents the unsmoothed measured temperature, Y n represents the smoothed measured temperature, n is the number of multiple measured temperatures of the motor stator in the preset operating period sorted by the acquisition time, and the first and last smoothed measured temperatures are the same as the unsmoothed measured temperatures. p and q are both weighting coefficients. In one embodiment, if multiple measured temperatures of the motor stator in the preset operating period gradually increase, p < 0.5, q > 0.5, for example, p = 0.475, q = 0.525; if multiple measured temperatures of the motor stator in the preset operating period gradually decrease, p > 0.5, q < 0.5, for example, p = 0.525, for example, q = 0.475.

[0062] S1002, obtaining a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the parameters of the prediction model include an initial temperature, a steady-state temperature, and at least one constant coefficient.

[0063] Among them, the prediction model refers to the relationship between the predicted temperature of the motor stator and the theoretical running time. The theoretical running time in the prediction model can be greater than the actual running time of the motor. When the theoretical running time is zero, the predicted temperature is the initial temperature. When the theoretical running time is ∞, the predicted temperature is the steady-state temperature (the theoretical running time is ∞, the motor has run for a sufficient time, and the temperature of the motor stator can reach the steady-state temperature). The predicted temperature refers to the predicted value of the temperature of the motor stator calculated by the prediction model. By setting the initial temperature and steady-state temperature in the prediction model, the predicted temperature obtained by the prediction model can be more accurate. When the running time (theoretical running time, not actual running time) is long enough, a more accurate prediction value of the steady-state temperature can be obtained.

[0064] The prediction model also includes at least one constant coefficient, which is related to the test object, test conditions and test environment. The constant coefficient may be different for different test objects, test conditions or test environments. That is, the constant coefficient can be adjusted according to the test object, test conditions or test environment, so that the predicted temperature obtained by the prediction model can be more accurate and closer to the actual measured temperature.

[0065] S1003, obtaining an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient.

[0066] The initial value of the initial temperature can be the measured temperature of the motor stator at the initial moment of the running period. When the motor is in cold state at the initial moment of the running period, the initial value of the initial temperature can be the ambient temperature. The initial value of the steady-state temperature and the initial value of the constant coefficient can be set according to the experience of the staff, or historical values ​​can be used, which is not done in the present invention.

[0067] In an optional embodiment, if multiple measured temperatures of the motor stator in a preset operating period gradually increase, the initial value of the steady-state temperature can be set to be greater than the initial value of the initial temperature; in another optional embodiment, if multiple measured temperatures of the motor stator in a preset operating period gradually decrease, the initial value of the steady-state temperature can be set to be less than the initial value of the initial temperature.

[0068] S1004. According to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, a plurality of predicted temperatures of the motor stator in a preset operating period are obtained; the plurality of predicted temperatures correspond one to one with the plurality of measured temperatures.

[0069] Specifically, according to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, the specific formula of the prediction model can be determined. By substituting the theoretical operating time, the predicted temperature of the motor stator after the theoretical operating time of the motor stator can be calculated, that is, the temperature value of the motor stator predicted by the prediction model.

[0070] Among them, the substituted theoretical operating time can be the time interval between the moment when the measured temperature is collected and the starting moment of the operating time period. For example, if the measured temperature is collected in the first minute of the operating time period, the predicted temperature when the theoretical operating time of the motor stator is one minute is calculated; if the measured temperature is collected in the i-th minute of the operating time period, the predicted temperature when the theoretical operating time of the motor stator is i minutes is calculated by the prediction model, i is greater than or equal to zero, and less than or equal to the duration of the preset operating time period, so that the predicted temperature can correspond one-to-one to the measured temperature.

[0071] S1005. Determine the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature.

[0072] The predicted value of the steady-state temperature is the temperature value of the motor stator predicted when the motor runs from a cold state to a thermally stable state under a stable load using the embodiment of the present invention. The optimal value of the constant coefficient is the constant coefficient of the improved prediction model.

[0073] Exemplarily, the motor can be controlled to operate under a certain stable working condition, for example, the motor can be controlled to operate from cold state to a preset operating time under a stable load, that is, a preset operating period, for example, the preset operating time is 40 minutes, that is, the duration of the preset operating period is 40 minutes. In the preset operating period, multiple temperature values ​​of the motor stator can be collected at a specific time (such as the start time of each minute) as the measured temperature; at the same time, the prediction model can also be used to calculate multiple predicted temperatures of the motor stator at a specific time (same as the measured temperature, also at the start time of each minute), and by comparing multiple groups of measured temperatures and predicted temperatures at the same time, the accuracy of the prediction model can be determined, and the parameters of the prediction model can also be adjusted according to the comparison results to improve the accuracy of the prediction model, thereby further optimizing the prediction model until the best model of the prediction model is obtained, and the predicted value of the steady-state temperature and the optimal value of the constant coefficient can also be obtained.

[0074] Optionally, the prediction model includes: T(t)=(ad)×f(t)+d; wherein t is the theoretical operating time, T(t) is the predicted temperature; a is the initial temperature; d is the steady-state temperature; f(t) is a functional relationship related to the theoretical operating time, f(t) includes at least one constant coefficient, and f(0)=1, f(∞)=0.

[0075] Among them, f(t) includes but is not limited to exponential functions, logarithmic functions, etc. The initial temperature can be the measured temperature in the cold state, or the measured temperature of the motor stator after the motor has been running in a stable condition for a period of time. The initial temperature can also be the measured temperature of the motor stator in a thermally stable condition. The prediction model can predict the temperature value of the motor stator under a certain stable condition. For example, it can predict the steady-state temperature value of the motor stator when it theoretically runs from a cold state to a thermally stable condition under a stable load; predict the steady-state temperature value of the motor stator when it theoretically runs from one thermally stable condition to another thermally stable condition after switching to another load (the load of the motor has stabilized); predict the steady-state temperature value from theoretical operation of a thermally stable condition to a thermally stable condition under a higher load, etc.

[0076] Specifically, the shorter the theoretical running time of the motor stator starting from the initial temperature, the closer the predicted temperature of the motor stator is to the initial temperature, and the longer the theoretical running time of the motor stator starting from the initial temperature, the closer the predicted temperature of the motor stator is to the steady-state temperature. The prediction model provided by the embodiment of the present invention can not only predict the steady-state temperature after temperature rise, but also predict the steady-state temperature after temperature drop, which is applicable to various situations, and is conducive to assisting the performance test of the motor in the production process or the research and development process, and improving product performance and yield.

[0077] In an alternative embodiment, f(t)=1 / [1+(t / c) b]; where b and c are constant coefficients. Specifically, the prediction model is T(t) = (ad) / [1+(t / c) b ]+d.

[0078] Based on the above embodiment, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient are obtained, including: obtaining the initial values ​​of a, b, c, and d; wherein the initial values ​​of a, b, c, and d are all positive numbers, and a<b.

[0079] Wherein, a, b, c, d can be set according to experience, or historical values, or any positive number, which is not limited by the present invention. In an optional embodiment, a is the ambient temperature, b is a value of 0.8-1.2, c is a value of 1-10, and d is a value greater than a.

[0080] Specifically, a, b, c, and d are all positive numbers, such that 1+(t / c) b ≥1, that is, 0≤1 / [1+(t / c) b ]≤1, so that the predicted temperature T(t) of the prediction model is greater than or equal to the initial temperature a and less than or equal to the steady-state temperature d, which is beneficial to improving the accuracy of the predicted temperature T(t) of the prediction model.

[0081] For example, when performing a temperature rise test, multiple measured temperatures of the motor stator in a preset operating period gradually increase, indicating that the temperature of the motor stator gradually increases during the process of the motor running to a thermally stable condition under a stable load, and the steady-state temperature is greater than the initial temperature, and a<b can be set;

[0082] In other embodiments, a temperature drop test may also be performed. If multiple measured temperatures of the motor stator gradually decrease during a preset operating period, it means that the temperature of the motor stator gradually decreases during the process of the motor running under a stable load to a thermally stable condition, and the steady-state temperature is lower than the initial temperature. Therefore, a>b can be set.

[0083] Optionally, based on the measured temperature and the predicted temperature, the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model are determined, including: based on multiple measured temperatures and multiple predicted temperatures that correspond one to one, obtaining the sum of the squares of the differences between all corresponding measured temperatures and predicted temperatures; defining the sum of the squares of the differences as the minimum value, the steady-state temperature and the constant coefficient as variables, and performing planning and solving; determining the steady-state temperature obtained by the planning and solving as the predicted value of the steady-state temperature, and the constant coefficient obtained by the planning and solving as the optimal value of the constant coefficient.

[0084] For example, a total of k groups of corresponding measured temperatures and predicted temperatures are included, and the measured temperature of the nth group is Y n , the predicted temperature of the nth group is T n(t), n is an integer, and 1≤n≤k, the sum of the squares of the differences between all corresponding measured temperatures and predicted temperatures is T n (t) = (ad) / [1+(t / c) b ]+d, you can use the numerical planning tool of Excel to set Δ as the minimum value, a, b, c, d are all variables, and after planning and solving, you can get the optimized a, b, c, d, the optimized d is the predicted value of the steady-state temperature, and the optimized b, c are the best values ​​of the constant coefficients.

[0085] In other optional implementations, the variance, standard deviation, average value, etc. of the squared differences between all corresponding measured temperatures and predicted temperatures can be obtained based on multiple measured temperatures and multiple predicted temperatures that correspond one to one, and then the variance, standard deviation, and average value of the squared differences are defined as minimum values, and the steady-state temperature and the constant coefficient are defined as variables, and the solution is performed by planning; the steady-state temperature obtained by the planning solution is determined as the predicted value of the steady-state temperature, and the constant coefficient obtained by the planning solution is defined as the optimal value of the constant coefficient.

[0086] In the first embodiment of the present invention, by obtaining multiple measured temperatures of the motor stator in a preset operating period and calculating multiple predicted temperatures of the motor stator in a preset operating period through a prediction model, the prediction model can be optimized, and the temperature value of the motor stator when the motor runs to a thermally stable condition is predicted according to the optimized prediction model. There is no need to control the motor to actually run to a thermally stable condition, which can greatly shorten the test time, save energy consumed in the test, improve test safety, reduce risks, and avoid the steady-state temperature of the motor stator being too high when the motor actually runs to a thermally stable condition, thereby damaging the motor and causing irreparable losses.

[0087] In addition, the prediction model includes an initial temperature and a steady-state temperature, as well as at least one constant coefficient, which can make the predicted temperature obtained by the prediction model more accurate and obtain a more accurate predicted value of the steady-state temperature. The constant coefficient can be adjusted according to the test object, test conditions or test environment so that the predicted temperature obtained by the prediction model is closer to the actual measured temperature, which is conducive to improving the accuracy of the prediction model.

[0088] Embodiment 2

[0089] Figure 2 1 is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in the second embodiment of the present invention. Compared with the above embodiment, this embodiment can further shorten the test time. Figure 2 As shown, the method includes:

[0090] S2001. Acquire multiple measured temperatures of the motor stator in a preset operating period; wherein the duration of the preset operating period is shorter than the operating time for the motor stator to reach a steady-state temperature from an initial temperature.

[0091] S2002. Obtain a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the parameters of the prediction model include an initial temperature, a steady-state temperature, and at least one constant coefficient.

[0092] S2003. Obtain an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient.

[0093] S2004. According to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, a plurality of predicted temperatures of the motor stator in a preset operating period are obtained; the plurality of predicted temperatures correspond one to one with the plurality of measured temperatures.

[0094] S2005. According to the multiple measured temperatures and the multiple predicted temperatures that correspond one to one, obtain the sum of the squares of the differences between all the corresponding measured temperatures and the predicted temperatures.

[0095] S2006. Define the sum of squared differences as the minimum value, the steady-state temperature and the constant coefficient as variables, and solve the problem.

[0096] S2007, averaging the minimum values ​​of the sum of squared differences obtained by the planning solution to obtain an average value of squared differences, and determining whether the average value of squared differences is less than or equal to a first threshold or whether the duration of the preset running time period is greater than or equal to a second threshold. If any one of them is yes, execute S2008; if both are no, execute S2009.

[0097] S2008. Determine the steady-state temperature obtained by the planning solution as the predicted value of the steady-state temperature, and determine the constant coefficient obtained by the planning solution as the optimal value of the constant coefficient.

[0098] S2009: Increase the duration of the preset running time period by a preset increment. Return to S2001.

[0099] Among them, the first threshold value can be set according to actual needs, such as test accuracy requirements. Generally, the higher the test accuracy requirements, the smaller the first threshold value. For example, the first threshold value can be a value between 2 and 5. The second threshold value is less than the running time for the motor stator to reach the steady-state temperature from the initial temperature. Generally, the running time for the motor stator to reach the steady-state temperature from the initial temperature is, and the running time for the motor stator to run from the cold state to the thermal stable working condition is generally 90-120min. The second threshold value is less than 90min. For example, the second threshold value can be a value between 40-50min. The preset time without increasing the preset increment is less than the second threshold. For example, the preset time without increasing the preset increment can be a value between 20-40min. The preset increment is set according to experience or demand, including but not limited to 2min, 5min, 7min, etc.

[0100] For example, the motor can be controlled to actually run under a certain stable working condition. During the operation, multiple temperature values ​​of the motor stator can be collected at a specific time (such as the start time of each minute) as multiple measured temperatures, and multiple predicted temperatures of the motor stator at a specific time (the start time of each minute) are calculated through the prediction model. When the actual operation reaches 20 minutes, the sum of the squares of the differences between the multiple measured temperatures and the multiple predicted temperatures that have been obtained one by one is calculated, and the planning solution is calculated to calculate the average value of the minimum value of the sum of the squares of the differences. By judging whether the average value of the squares of the differences is less than or equal to the first threshold, it is determined whether the prediction model has been optimized to a sufficient accuracy. If the average value of the square of the difference is less than or equal to the first threshold, it means that the prediction model has been optimized to a sufficient accuracy, the motor can be controlled to stop running, and the obtained prediction model can accurately predict the steady-state temperature of the motor stator under thermal stability conditions; if the average value of the square of the difference is greater than the first threshold, it means that the prediction model is not accurate enough, and it is necessary to continue to control the actual operation of the motor. After the motor continues to run for 5 minutes, the sum of the square of the difference between all the one-to-one corresponding measured temperatures and multiple predicted temperatures is recalculated, and it is determined whether the average value of the minimum sum of the square of the difference is less than or equal to the first threshold, so that the prediction model continues to be optimized until the prediction model is optimized to a sufficient accuracy or the actual running time of the motor is greater than or equal to 40 minutes. Among them, the sum of the square of the difference between multiple measured temperatures and multiple predicted temperatures, the planning solution, and the process of determining whether the average value of the square of the difference is less than or equal to the first threshold are very fast, and whether the motor is controlled to stop running or continue running after the judgment, it will not affect the state of the motor.

[0101] In the second embodiment of the present invention, by comparing the average value of the square of the difference and the first threshold, the test can be stopped when the average value of the square of the difference is less than or equal to the first threshold, and the obtained prediction model can accurately predict the steady-state temperature of the motor stator under thermal stability conditions, which is conducive to further shortening the test time and reducing the energy consumed by the test. At the same time, it can also improve the accuracy of the predicted temperature obtained by the prediction model.

[0102] Embodiment 3

[0103] Figure 3 1 is a flow chart of a method for predicting the steady-state temperature of a motor stator provided in the third embodiment of the present invention. Compared with the above embodiments, this embodiment can predict the running time for the motor stator to reach the preset temperature. Figure 3 As shown, the method includes:

[0104] S3001. Acquire multiple measured temperatures of the motor stator in a preset operating period; wherein the duration of the preset operating period is shorter than the operating time for the motor stator to reach a steady-state temperature from an initial temperature.

[0105] S3002. Obtain a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the parameters of the prediction model include an initial temperature, a steady-state temperature, and at least one constant coefficient.

[0106] S3003. Obtain an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient.

[0107] S3004. According to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, multiple predicted temperatures of the motor stator in a preset operating period are obtained; the multiple predicted temperatures correspond one-to-one to the multiple measured temperatures.

[0108] S3005. Determine the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model based on the measured temperature and the predicted temperature.

[0109] S3006. Determine an optimal prediction model according to the initial value of the initial temperature, the predicted value of the steady-state temperature, and the optimal value of the constant coefficient.

[0110] S3007. Determine, based on the optimal prediction model, a predicted value of the running time for the motor stator to reach a preset temperature from an initial temperature; wherein the preset temperature is less than the predicted value of the steady-state temperature.

[0111] Specifically, after obtaining the optimal prediction model, the theoretical running time for the motor stator to reach the temperature from the initial temperature can be predicted according to the preset temperature, that is, the theoretical running time for the motor stator to reach the temperature from the initial temperature can be predicted.

[0112] For example, when the temperature fluctuation of the motor stator is acceptable within ±k under thermally stable working conditions, the predicted value of the steady-state temperature minus k can be used to obtain the theoretical running time when the motor stator reaches the steady-state temperature from the initial temperature minus the predicted value of the steady-state temperature, and the theoretical running time when the motor stator reaches the steady-state temperature from the initial temperature minus k can be approximately identified as the theoretical running time when the motor stator reaches the steady-state temperature from the initial temperature. The performance of the motor can be judged based on the theoretical running time, which is helpful for assisting the performance test of the motor in the production process or the research and development process, and improving product performance and yield.

[0113] In the third embodiment of the present invention, by determining the best prediction model and determining the running time for the motor stator to reach the preset temperature from the initial temperature according to the best prediction model, the theoretical running time when the motor stator reaches the preset temperature can be predicted, thereby judging the motor performance. Moreover, there is no need to control the actual operation of the motor stator to the preset temperature, which can greatly shorten the test time and save energy. It can also improve the test safety and reduce the risk, and avoid the motor actually running to the preset temperature, the temperature is too high, the motor is damaged, and irreparable losses are caused.

[0114] Embodiment 4

[0115] Figure 4 Schematic diagram of the structure of a device for predicting the steady-state temperature of a motor stator provided in the fourth embodiment of the present invention. Figure 4 As shown, the device comprises:

[0116] The measuring module 410 is used to obtain a plurality of measured temperatures of the motor stator in a preset operating period; wherein the duration of the preset operating period is less than the operating time for the motor stator to reach a steady-state temperature from an initial temperature;

[0117] A modeling module 420 is used to obtain a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the prediction model includes an initial temperature, a steady-state temperature and at least one constant coefficient;

[0118] An assignment module 430, for obtaining an initial value of an initial temperature, an initial value of a steady-state temperature, and an initial value of a constant coefficient;

[0119] A first calculation module 440 is used to obtain a plurality of predicted temperatures of the motor stator in a preset operation period according to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient; the plurality of predicted temperatures correspond one to one with the plurality of measured temperatures;

[0120] The prediction module 450 is used to determine the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature.

[0121] Optionally, the prediction model includes:

[0122] T(t)=(ad)×f(t)+d;

[0123] Wherein, t is the theoretical operating time, T(t) is the predicted temperature, a is the initial temperature, d is the steady-state temperature, f(t) is a functional relationship related to the theoretical operating time, f(t) includes at least one constant coefficient, and f(0)=1, f(∞)=0.

[0124] In an alternative embodiment, f(t)=1 / [1+(t / c) b ];

[0125] Where b and c are constant coefficients.

[0126] On the basis of the above embodiment, the assignment module 430 is further used to obtain the initial values ​​of a, b, c, and d; wherein the initial values ​​of a, b, c, and d are all positive numbers, and a<b.

[0127] Optionally, the prediction module 450 includes:

[0128] A first calculation unit is used to obtain the sum of squares of differences between all corresponding measured temperatures and predicted temperatures according to the multiple measured temperatures and the multiple predicted temperatures that correspond one to one;

[0129] The first planning and solving unit is used to define the sum of squared differences as a minimum value, the steady-state temperature and the constant coefficient as variables, and to plan and solve;

[0130] The first prediction unit is used to determine the steady-state temperature obtained by the planning solution as the predicted value of the steady-state temperature, and to determine the constant coefficient obtained by the planning solution as the optimal value of the constant coefficient.

[0131] Optionally, the prediction module 450 includes:

[0132] A first calculation unit is used to obtain the sum of squares of differences between all corresponding measured temperatures and predicted temperatures according to the multiple measured temperatures and the multiple predicted temperatures that correspond one to one;

[0133] The first planning and solving unit is used to define the sum of squared differences as a minimum value, the steady-state temperature and the constant coefficient as variables, and to plan and solve;

[0134] The second calculation unit is used to average the minimum value of the sum of the squares of the difference values ​​obtained by the planning solution to obtain an average value of the squares of the difference values;

[0135] A second prediction unit is used to determine the steady-state temperature obtained by the planning solution as the predicted value of the steady-state temperature when the average value of the square of the difference value is less than or equal to the first threshold value, and to determine the constant coefficient obtained by the planning solution as the optimal value of the constant coefficient;

[0136] An operating duration control unit is used to increase the duration of a preset operating period by a preset increment when the average value of the square of the difference is greater than a first threshold value, and return to the step of obtaining multiple measured temperatures of the motor stator in the preset operating period until the average value of the sum of the square of the difference is less than or equal to the first threshold value or the duration of the preset operating period is greater than or equal to a second threshold value.

[0137] Optionally, also include:

[0138] an optimization module for determining an optimal prediction model based on an initial value of the initial temperature, a predicted value of the steady-state temperature, and an optimal value of a constant coefficient;

[0139] The second calculation module is used to determine the predicted value of the running time of the motor stator from the initial temperature to the preset temperature according to the optimal prediction model; wherein the preset temperature is lower than the predicted value of the steady-state temperature.

[0140] The device for predicting the steady-state temperature of a motor stator provided in the embodiment of the present invention can execute the method for predicting the steady-state temperature of a motor stator provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0141] Embodiment 5

[0142] Figure 5 A schematic diagram of an electronic device that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0143] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0144] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0145] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the prediction of the steady-state temperature of the motor stator.

[0146] In some embodiments, the prediction of the motor stator steady-state temperature may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the prediction of the motor stator steady-state temperature described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the prediction of the motor stator steady-state temperature in any other appropriate manner (e.g., by means of firmware).

[0147] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0148] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0149] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0150] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0151] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0152] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0153] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0154] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for predicting the steady-state temperature of a motor stator, characterized in that: include: Acquire multiple measured temperatures of the motor stator in a preset operating period; wherein the duration of the preset operating period is less than the operating time for the motor stator to reach a steady-state temperature from an initial temperature; Obtaining a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the parameters of the prediction model include the initial temperature, the steady-state temperature and at least one constant coefficient; Acquire an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient; According to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient, a plurality of predicted temperatures of the motor stator in the preset operating period are obtained; the plurality of predicted temperatures correspond one to one with the plurality of measured temperatures; According to the measured temperature and the predicted temperature, the predicted value of the steady-state temperature of the prediction model and the optimal value of the constant coefficient are determined.

2. The method for predicting the steady-state temperature of a motor stator according to claim 1, characterized in that: The prediction model includes: T(t)=(ad)×f(t)+d; Wherein, t is the theoretical operating time, T(t) is the predicted temperature; a is the initial temperature; d is the steady-state temperature; f(t) is a functional relationship related to the theoretical operating time, f(t) includes at least one constant coefficient, and f(0)=1, f(∞)=0.

3. The method for predicting the steady-state temperature of a motor stator according to claim 2, characterized in that: f(t)=1 / [1+(t / c) b ]; Wherein, b and c are both constant coefficients.

4. The method for predicting the steady-state temperature of a motor stator according to claim 3, characterized in that: Obtaining an initial value of the initial temperature, an initial value of the steady-state temperature, and an initial value of the constant coefficient includes: Get the initial values ​​of a, b, c, and d; wherein the initial values ​​of a, b, c, and d are all positive numbers, and a<b.

5. The method for predicting the steady-state temperature of a motor stator according to claim 1, characterized in that: Determining the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature includes: According to the plurality of measured temperatures and the plurality of predicted temperatures that correspond one to one, respectively, a sum of squares of differences between all corresponding measured temperatures and predicted temperatures is obtained; The sum of the squares of the differences is defined as the minimum value, the steady-state temperature and the constant coefficient are defined as variables, and a planning solution is performed; The steady-state temperature obtained by the planning solution is determined as the predicted value of the steady-state temperature, and the constant coefficient obtained by the planning solution is determined as the optimal value of the constant coefficient.

6. The method for predicting the steady-state temperature of a motor stator according to claim 1, characterized in that: Determining the predicted value of the steady-state temperature and the optimal value of the constant coefficient of the prediction model according to the measured temperature and the predicted temperature includes: According to the plurality of measured temperatures and the plurality of predicted temperatures that correspond one to one, respectively, a sum of squares of differences between all corresponding measured temperatures and predicted temperatures is obtained; The sum of the squares of the differences is defined as the minimum value, the steady-state temperature and the constant coefficient are defined as variables, and a planning solution is performed; Averaging the minimum values ​​of the sum of squared differences obtained by the planning solution to obtain an average value of the squared differences; When the average value of the square of the difference is less than or equal to a first threshold, determining the steady-state temperature obtained by the planning solution as the predicted value of the steady-state temperature, and determining the constant coefficient obtained by the planning solution as the optimal value of the constant coefficient; When the average value of the square of the difference is greater than the first threshold, the duration of the preset operating period is increased by a preset increment, and the step of obtaining multiple measured temperatures of the motor stator in the preset operating period is returned to until the average value of the sum of the square of the difference is less than or equal to the first threshold or the duration of the preset operating period is greater than or equal to the second threshold.

7. The method for predicting the steady-state temperature of a motor stator according to claim 1, characterized in that: Also includes: Determining an optimal prediction model according to the initial value of the initial temperature, the predicted value of the steady-state temperature and the optimal value of the constant coefficient; According to the optimal prediction model, a predicted value of the running time for the motor stator to reach a preset temperature from an initial temperature is determined; wherein the preset temperature is less than the predicted value of the steady-state temperature.

8. A device for predicting the steady-state temperature of a motor stator, characterized in that: include: A measurement module, used to obtain a plurality of measured temperatures of the motor stator in a preset operation period; wherein the duration of the preset operation period is less than the operation duration for the motor stator to reach a steady-state temperature from an initial temperature; A modeling module, used to obtain a prediction model of the predicted temperature and theoretical operating time of the motor stator; wherein the prediction model includes the initial temperature, the steady-state temperature and at least one constant coefficient; An assignment module, used for obtaining an initial value of the initial temperature, an initial value of the steady-state temperature and an initial value of the constant coefficient; A first calculation module, for obtaining a plurality of predicted temperatures of the motor stator in the preset operating period according to the prediction model, the initial value of the initial temperature, the initial value of the initial temperature, the initial value of the steady-state temperature and the initial value of the constant coefficient; the plurality of predicted temperatures correspond one-to-one to the plurality of measured temperatures; A prediction module is used to determine the predicted value of the steady-state temperature of the prediction model and the optimal value of the constant coefficient according to the measured temperature and the predicted temperature.

9. An electronic device, characterized in that: The electronic device comprises: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for predicting the steady-state temperature of the motor stator according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for predicting the steady-state temperature of a motor stator according to any one of claims 1 to 7 when the processor executes the instructions.

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