Method for optimizing parameters of a wet clutch temperature model and related device

Abstract

The embodiment of the present disclosure provides a kind of wet clutch temperature model parameter optimization method and related device, the optimization method includes: the calculated temperature of hot disc and / or cold disc is obtained by temperature model based on key parameter, key parameter includes at least one of distribution coefficient, hot disc heat exchange coefficient, cold disc heat exchange coefficient, clutch disc heat capacity;The actual temperature of hot disc and / or cold disc is obtained;The calculated temperature of hot disc and / or cold disc is input into iterative model based on key parameter, determine the value of key parameter when the mean square deviation of calculated temperature and corresponding actual temperature of hot disc and / or cold disc is minimum.This embodiment of the present disclosure is higher in efficiency compared with the mode of artificial calibration optimal value adopted by traditional technology;And, iterative operation is carried out based on iterative model established by key parameter, the optimal value of key parameter can be more accurately determined, and it has important significance for the research of wet clutch.

Description

Technical Field

[0001] This disclosure relates to the field of automotive clutch technology, and more specifically, to a method and related apparatus for optimizing temperature model parameters of a wet clutch. Background Technology

[0002] Currently, most on-demand four-wheel drive transfer cases on the market use a wet clutch as the central differential lock-up mechanism and torque distribution mechanism. Under different operating conditions, the temperature of the clutch disc is ultimately determined by the heat generated by slip friction, the heat dissipation of the cooling oil, and the heat exchange with the surrounding environment during the torque transmission process of the wet clutch. Therefore, identifying the heat generation power and heat dissipation weight coefficient, and clarifying the heat transfer coefficient and thermal calculation influence parameters are key points to ensure the calculated clutch disc temperature. Currently, the parameters used in wet clutch temperature models to calculate the clutch disc temperature are relatively simple, usually using manual verification. However, this method has a large error and low calculation efficiency. Summary of the Invention

[0003] The purpose of this disclosure is to provide a method and related apparatus for optimizing the temperature model parameters of a wet clutch, so as to solve the problems of large errors and low computational efficiency in the prior art.

[0004] To address the aforementioned technical problems, this disclosure provides a method for optimizing the temperature model parameters of a wet clutch. The wet clutch includes a housing, a clutch disc, and cooling oil. The clutch disc includes a hot disc and a cold disc. The optimization method includes: obtaining the calculated temperature of the hot disc and / or the cold disc through a temperature model established based on key parameters, wherein the key parameters include at least one of a distribution coefficient, a hot disc heat exchange coefficient, a cold disc heat exchange coefficient, and a clutch disc heat capacity; obtaining the actual temperature of the hot disc and / or the cold disc; inputting the calculated temperature of the hot disc and / or the cold disc into an iterative model established based on the key parameters; and determining the value of the key parameters when the root mean square error between the calculated temperature of the hot disc and / or the cold disc and the corresponding actual temperature is minimized.

[0005] Furthermore, obtaining the calculated temperature of the hot plate and / or the cold plate through a temperature model established based on key parameters includes: determining the cooling oil distribution power, the hot plate output power, and the cold plate output power based on clutch parameters, the distribution coefficient, and cooling oil parameters; and determining the calculated temperature of the hot plate and / or the cold plate based on the cooling oil distribution power, the hot plate output power, and the cold plate output power.

[0006] Further, determining the cooling oil distribution power, hot plate output power, and cold plate output power based on clutch parameters, the distribution coefficient, and cooling oil parameters includes: determining the hot plate distribution power, cold plate distribution power, and cooling oil distribution power based on the clutch parameters and the distribution coefficient; determining the hot plate output power based on the hot plate distribution power, the hot plate heat exchange coefficient, and the cooling oil quality; and determining the cold plate output power based on the cold plate distribution power, the hot plate output power, the cold plate heat exchange coefficient, and the cooling oil quality.

[0007] Furthermore, the quality of the cooling oil is determined by the cooling oil temperature and the cooling oil flow rate.

[0008] Further, the step of inputting the calculated temperatures of the hot plate and / or the cold plate into an iterative model established based on key parameters, and determining the values ​​of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized, includes: inputting the calculated temperature of the hot plate into a first iterative model, the first iterative model being determined based on the energy balance equation of the wet clutch and the energy balance equation of the hot plate; or, inputting the calculated temperature of the cold plate into a second iterative model, the second iterative model being determined based on the energy balance equation of the wet clutch and the energy balance equation of the cold plate.

[0009] Furthermore, the first iterative model is represented by the following equation:

[0010]

[0011] Where k is the number of iterations; T clu hot T is the calculated temperature of the hot plate. oil bulk T represents the temperature of the cooling oil. s Sampling time; α is the heat ratio of the hot plate; β is the distribution coefficient; m clu For the mass of the clutch disc; c clu The clutch disc heat capacity; Trq clu For torque; n clu For the speed difference; The heat transfer coefficient between the heat plate and the shell; The heat transfer coefficient of the hot plate to the oil; The heat transfer coefficient between the hot plate and the cold plate.

[0012] Furthermore, the second iterative model is represented by the following equation:

[0013]

[0014]

[0015] Where k is the number of iterations; Tclu cool T is the calculated temperature of the cold plate. oil bulk T represents the temperature of the cooling oil. s Sampling time; α represents the heat transfer percentage of the hot plate; β represents the heat transfer percentage of the cooling oil; m clu For the mass of the clutch disc; c clu The clutch disc heat capacity; Trq clu For torque; n clu For the speed difference; The heat transfer coefficient between the cold plate and the shell; The coefficient of heat transfer from the cold plate to the oil is denoted as .

[0016] Another aspect of this disclosure provides an apparatus for optimizing the temperature model parameters of a wet clutch, comprising:

[0017] The processing module is used to obtain the calculated temperature of the hot plate and / or the cold plate through a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0018] The acquisition module is used to acquire the actual temperature of the hot plate and / or the cold plate;

[0019] An iterative calculation module is used to input the calculated temperatures of the hot plate and / or the cold plate into an iterative model established based on key parameters, and to determine the value of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized.

[0020] This disclosure also provides a storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described optimization method.

[0021] This disclosure also provides an electronic device, which includes at least a memory and a processor. The memory stores a computer program, and the processor implements the steps of the above-described optimization method when executing the computer program in the memory.

[0022] This disclosure focuses on heat exchange modeling and analysis for wet clutches. Based on a temperature model established using key parameters, the calculated temperatures of the hot and / or cold discs are obtained. The actual temperatures of the hot and / or cold discs are then acquired. The calculated temperatures are input into an iterative model based on the key parameters for iterative calculation. When the mean square error between the calculated and actual temperatures reaches its minimum, the optimization objective is considered achieved. The values ​​of key parameters at this calculated temperature are determined, such as at least one of the following: distribution coefficient, hot disc heat exchange coefficient, cold disc heat exchange coefficient, and clutch disc heat capacity. Compared to the traditional method of manually verifying optimal values, this optimization method can be directly implemented using computers and other equipment, resulting in higher efficiency. Furthermore, the iterative calculation based on the key parameters allows for more accurate determination of the optimal values ​​of the key parameters, which is of significant importance for the research of wet clutches. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram illustrating the steps of the method for optimizing the temperature model parameters of a wet clutch according to an embodiment of the present disclosure.

[0025] Figure 2 This is a schematic diagram of the structure of a wet clutch according to an embodiment of the present disclosure;

[0026] Figure 3 This is a schematic diagram of the heat exchange of a wet clutch according to an embodiment of the present disclosure;

[0027] Figure 4 This is a schematic diagram of an optimization processing device for the temperature model parameters of a wet clutch according to an embodiment of the present disclosure;

[0028] Figure 5 This is a schematic diagram illustrating the steps of the method for optimizing the temperature model parameters of a wet clutch according to an embodiment of the present disclosure.

[0029] Figure 6 This is a schematic diagram illustrating the steps of the method for optimizing the temperature model parameters of a wet clutch according to an embodiment of this disclosure.

[0030] The above figures include the following reference numerals:

[0031] 1. Housing; 2. Clutch disc; 3. Steel plate; 4. Inner hub; 5. Pressure plate; 6. Return spring; 7. Thrust bearing; 8. Input shaft. Detailed Implementation

[0032] Various embodiments and features of this disclosure are described herein with reference to the accompanying drawings.

[0033] It should be understood that various modifications can be made to the embodiments described herein. Therefore, the above description should not be considered as limiting, but merely as an example of embodiments. Other modifications within the scope and spirit of this disclosure will be apparent to those skilled in the art.

[0034] The accompanying drawings, which are included in and form part of this specification, illustrate embodiments of the present disclosure and, together with the general description of the disclosure given above and the detailed description of the embodiments given below, serve to explain the principles of the disclosure.

[0035] These and other features of this disclosure will become apparent from the following description of preferred forms of embodiments given as non-limiting examples, with reference to the accompanying drawings.

[0036] It should also be understood that although this disclosure has been described with reference to some specific examples, those skilled in the art can certainly implement many other equivalent forms of this disclosure, which have the features described in the claims and are therefore all within the scope of protection defined herein.

[0037] The above and other aspects, features and advantages of this disclosure will become more apparent when taken in conjunction with the accompanying drawings and in view of the following detailed description.

[0038] Specific embodiments of this disclosure are described thereafter with reference to the accompanying drawings; however, it should be understood that the claimed embodiments are merely examples of this disclosure, which may be implemented in various ways. Well-known and / or repeated functions and structures are not described in detail to avoid unnecessary or redundant details that could obscure this disclosure. Therefore, the specific structural and functional details claimed herein are not intended to be limiting, but merely to serve as the basis and representative basis for the claims to teach those skilled in the art to use this disclosure in a variety of substantially any suitable detailed structures.

[0039] This specification may use the phrases “in one embodiment,” “in another embodiment,” “in yet another embodiment,” or “in still another embodiment,” all of which may refer to one or more of the same or different embodiments according to this disclosure.

[0040] Combination Figure 2As shown, the clutch includes a housing 1, a clutch disc 2, and cooling oil. It typically also includes a steel plate 3, an inner hub 4, a pressure plate 5, a return spring 6, a thrust bearing 7, and an input shaft 8. The clutch disc 2 comprises a hot disc and a cold disc, grouped based on heat simulation results, with the hot disc having a higher temperature than the cold disc. The heat generated by slippage is proportionally distributed between the hot and cold discs. This is considered in conjunction with the arrangement of the clutch housing 1, the cooling oil, and the surrounding environment. Figure 3 As shown, the hot plate and cold plate transfer heat through thermal conduction, the hot plate and cooling oil transfer heat through convection, the hot plate and shell 1 transfer heat through convection, the cold plate and cooling oil transfer heat through convection, the cold plate and shell 1 transfer heat through convection, and the shell 1 and the environment transfer heat through convection and radiation.

[0041] Combination Figure 1 As shown, the first aspect of this disclosure provides a method for optimizing the parameters of a wet clutch temperature model, including:

[0042] S100, the calculated temperature of the hot plate and / or the cold plate is obtained by a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0043] S200, obtain the actual temperature of the hot plate and / or the cold plate;

[0044] S300, input the calculated temperature of the hot plate and / or the cold plate into an iterative model established based on key parameters, and determine the value of the key parameters when the root mean square error between the calculated temperature of the hot plate and / or the cold plate and the corresponding actual temperature is minimized.

[0045] Specifically:

[0046] S100, the calculated temperature of the hot plate and / or the cold plate is obtained by a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0047] In step S100, the key parameters include at least the distribution coefficient, the hot plate heat exchange coefficient, the cold plate heat exchange coefficient, and the clutch disc heat capacity. These key parameters have a significant impact on the calculation of the disc temperature. Combined with information such as temperature changes, the power output of the cold plate, hot plate, and cooling oil to other parts can be calculated. This allows for the calculation of the individual temperatures of the cold plate, hot plate, and cooling oil based on the law of conservation of energy (the calculation temperature of the cooling oil is optional, and at least one of the calculation temperatures of the hot plate and cold plate should be calculated to calculate the mean square error between the calculated temperature and the actual temperature in subsequent steps). Since the study of wet clutches is more sensitive to the structural parts with the highest temperature, and the hot plate obviously has a higher temperature, it is preferable to calculate the calculation temperature of the hot plate here. The other calculation temperatures (i.e., the calculation temperatures of the cold plate and cooling oil) can be considered for calculation according to the needs of the study.

[0048] In step S100, the calculated temperature of the hot plate and / or the cold plate is obtained through a temperature model established based on key parameters, combined with... Figure 5 As shown, it specifically includes:

[0049] S101, based on the clutch parameters, the distribution coefficient, and the cooling oil parameters, determine the cooling oil distribution power, the hot plate output power, and the cold plate output power;

[0050] S102, determine the calculated temperature of the hot plate and / or the cold plate based on the cooling oil distribution power, the hot plate output power, and the cold plate output power.

[0051] In step S101, the clutch parameters typically include parameters such as the clutch speed difference and torque. Combined with the distribution coefficient, the power distributed to the hot plate, cold plate, and cooling oil can be calculated. The output power of the hot plate and the output power of the cold plate are obtained by combining the cooling oil parameters.

[0052] Step S101 describes determining the cooling oil distribution power, hot plate output power, and cold plate output power based on clutch parameters, the distribution coefficient, and cooling oil parameters, combined with... Figure 6 As shown, it specifically includes:

[0053] S1011, Determine the hot plate distribution power, cold plate distribution power, and cooling oil distribution power based on the clutch parameters and the distribution coefficient;

[0054] Specifically, based on the clutch speed difference, torque, and distribution coefficient, the hot plate distribution power, cold plate distribution power, and cooling oil distribution power are calculated and determined. The distribution coefficient includes the heat ratio between the hot plate and the cold plate, as well as the heat transfer ratio between the clutch disc 2 and the cooling oil. The heat ratio of the hot plate is defined as α, and the heat ratio of the cold plate is (1-α). The heat transfer ratio of the cooling oil is defined as β, and the heat transfer ratio of the clutch disc 2 is (1-β). Therefore, the hot plate distribution power, cold plate distribution power, and cooling oil distribution power can be calculated.

[0055] S1012, the output power of the hot plate is determined based on the hot plate distribution power, the hot plate heat exchange coefficient and the cooling oil quality;

[0056] Specifically, the cooling oil mass can be calculated by combining the cooling oil density corresponding to the cooling oil temperature (which can be measured by a sensor) with the cooling oil flow rate. The heat transfer coefficient of the hot plate includes the heat transfer coefficient from the hot plate to the shell, the heat transfer coefficient from the hot plate to the cold plate, and the heat transfer coefficient from the hot plate to the oil. In this paper, the heat transfer coefficient from the hot plate to the shell is expressed as... The heat transfer coefficient from hot plate to cold plate is expressed as: The heat transfer coefficient of the hot plate to the oil is expressed as: Based on the aforementioned heat exchange coefficient of the hot plate, the power distribution of the hot plate, and the quality of the cooling oil, the output power of the hot plate can be calculated. The output power of the hot plate includes the output power of the hot plate to the cold plate, the output power of the hot plate to the oil, and the output power of the hot plate to the casing.

[0057] S1013, the output power of the cold plate is determined based on the cold plate distribution power, the output power of the hot plate, the heat exchange coefficient of the cold plate, and the quality of the cooling oil.

[0058] Specifically, the heat exchange coefficient of the cold plate includes the heat transfer coefficient of the cold plate to the shell and the heat transfer coefficient of the cold plate to the oil, wherein the heat transfer coefficient of the cold plate to the shell is: The heat transfer coefficient of the cold plate to oil is Based on the aforementioned heat exchange coefficient of the cold plate, the power distribution of the cold plate, the output power of the hot plate to the cold plate in the output power of the hot plate, and the quality of the cooling oil, the output power of the cold plate can be calculated. The output power of the cold plate includes the output power of the cold plate to the oil and the output power of the cold plate to the shell.

[0059] In step S102, the cooling oil distribution power, hot plate output power, and cold plate output power are calculated based on the relevant equations of energy conservation to obtain the calculated temperatures of the hot and cold plates. At least one of the calculated temperatures of the hot and cold plates can be selected for calculation to perform a mean square error calculation with the corresponding actual temperature. In this embodiment, the calculated temperature of the hot plate is preferably calculated, while the calculated temperature of the cold plate can be considered for calculation based on actual research needs.

[0060] S200, obtain the actual temperature of the hot plate and / or the cold plate.

[0061] In step S200, the actual temperatures of the hot plate and the cold plate are usually obtained directly by instruments and equipment such as sensors. Of course, those skilled in the art can also use other methods to obtain more accurate actual temperatures, which will not be elaborated here.

[0062] Step S300: Input the calculated temperature of the hot plate and / or the cold plate into an iterative model established based on key parameters, and determine the value of the key parameters when the root mean square error between the calculated temperature of the hot plate and / or the cold plate and the corresponding actual temperature is minimized.

[0063] In step S300, an iterative model is established based on key parameters. The corresponding calculated temperature is iteratively calculated using the iterative model. At the same time, the mean square error is calculated between the iterative calculated temperature and the actual temperature. When the mean square error reaches its minimum value, the calculated temperature at the corresponding iteration number can be used as the data closest to the actual temperature. Under the operating condition of this calculated temperature, the values ​​of the key parameters are determined, and the optimization of the wet clutch temperature model parameters is completed, thus obtaining the optimal key parameters.

[0064] It should be noted that the calculated and actual temperatures can be calculated using at least one of the hot and cold discs, depending on the specific research requirements. For example, when studying the location of the highest temperature in a wet clutch, only the calculated and actual temperatures of the hot disc can be considered. Alternatively, to ensure greater accuracy of key parameters, both the calculated and actual temperatures of the hot and cold discs can be considered, meaning the mean square error includes both the mean square error of the hot and cold disc temperatures. Those skilled in the art can assign appropriate weights to the mean square errors of the hot and cold disc temperatures according to research needs to find the key parameters corresponding to the condition where the calculated temperature is closest to the actual temperature.

[0065] In addition, the minimum value of the mean square error can be determined based on the actual accuracy requirements. For example, a target value of the mean square error can be set in advance. When the mean square error between the actual temperature and the calculated temperature reaches the target value, the iterative calculation can be considered to have achieved the optimization goal.

[0066] Step S300, which involves inputting the calculated temperatures of the hot plate and / or the cold plate into an iterative model based on key parameters to determine the values ​​of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized, specifically includes:

[0067] The calculated temperature of the hot plate is input into the first iterative model, which is determined based on the energy balance equation of the wet clutch and the energy balance equation of the hot plate.

[0068] And / or, the calculated temperature of the cold plate is input into a second iterative model, which is determined based on the energy balance equation of the wet clutch and the energy balance equation of the cold plate.

[0069] Specifically, the first and second iteration models are derived from a genetic algorithm, and their derivation process is as follows:

[0070] Based on the law of conservation of energy, heat exchange is modeled as follows: the heat generated by the slippage of the clutch equals the heat power flowing out of the clutch plus the heat power flowing into the clutch and the heat storage power of the clutch, resulting in Formula 1:

[0071]

[0072] in, The heat generated by clutch slippage; The heat power flowing out of the clutch; The heat power flowing into the clutch; This is for the heat storage power of the clutch.

[0073] Formula 2:

[0074]

[0075] in, C is the flow rate of cooling oil through the clutch. oil The heat capacity of the cooling oil (which is the same as the heat capacity of the cooling oil in the corresponding calculations of this disclosure); T oilout The temperature of the cooling oil flowing out of the clutch; T oilin This refers to the temperature of the cooling oil flowing into the clutch.

[0076] Assuming that all changes in cooling oil temperature are due to heat transfer from the clutch disc, then Formula 2 can be expanded into Formula 3:

[0077]

[0078] Where h is the convective heat transfer coefficient; A is the clutch disc area; T plate T represents the clutch disc temperature. oil mean This is the average temperature of the cooling oil in the clutch.

[0079] Assuming that all the heat generated is stored in the clutch disc, then we can obtain Formula 4:

[0080]

[0081] Where, m plate For the mass of the clutch disc; c plate This refers to the heat capacity of the clutch disc.

[0082] Formula 5 can be derived from Formulas 1, 3, and 4:

[0083]

[0084] Based on the heat exchange modeling described above, the first iterative model is represented by the following equation:

[0085]

[0086] The second iterative model is represented by the following equation:

[0087]

[0088]

[0089] Where k is the number of iterations; T clu hot Calculate the temperature of the hot plate; T clu cool Calculate the temperature of the cold plate; T oil bulk T represents the oil temperature. s Sampling time; α represents the heat transfer percentage of the hot plate; β represents the heat transfer percentage of the cooling oil; m clu c is the mass of the clutch disc; clu The clutch disc heat capacity; Trq clu The torque is n; clu The speed difference; The heat transfer coefficient of the heat plate to the shell; The heat transfer coefficient of the hot plate to the oil; The heat transfer coefficient from the hot plate to the cold plate; The heat transfer coefficient of the cold plate to the shell; The heat transfer coefficient of the cold plate to the oil is denoted as .

[0090] Key parameters include the distribution coefficient (the heat transfer ratio of the hot plate and the heat transfer ratio of the cooling oil mentioned above), the heat exchange coefficient of the hot plate (the heat transfer coefficient of the hot plate to the housing, the heat transfer coefficient of the hot plate to the oil, and the heat transfer coefficient of the hot plate to the cold plate mentioned above), the heat exchange coefficient of the cold plate (the heat transfer coefficient of the cold plate to the housing and the heat transfer coefficient of the cold plate to the oil mentioned above), the heat capacity of the cooling oil, and the heat capacity of the clutch disc.

[0091] The optimization method disclosed herein is for heat exchange modeling and analysis of wet clutches. Based on a temperature model established using key parameters, the calculated temperatures of the hot and / or cold discs are obtained; the actual temperatures of the hot and / or cold discs are also obtained; the calculated temperatures of the hot and / or cold discs are input into an iterative model established based on the key parameters for iterative calculation. When the mean square error between the calculated temperature and the corresponding actual temperature reaches its minimum, the optimization objective can be considered achieved. The values ​​of the key parameters at this calculated temperature are then determined, such as the distribution coefficients (the proportion of heat transferred from the hot disc and the proportion of heat transferred from the cooling oil, as described in this paper), the hot disc heat exchange coefficient, and the heat exchange system. The present invention discloses at least one of the following: heat transfer coefficients (hot plate to housing, hot plate to oil, and hot plate to cold plate as described herein), heat exchange coefficient of cold plate (cold plate to housing and cold plate to oil as described herein), heat capacity of cooling oil, and heat capacity of clutch disc; compared with the manual verification of optimal values ​​used in traditional technologies, the optimization method disclosed herein can be directly implemented by computers and other equipment, which is more efficient; furthermore, iterative calculations based on the iterative model established by the key parameters can more accurately determine the optimal values ​​of the key parameters, which is of great significance for the research of wet clutches.

[0092] Based on the same inventive concept, the second embodiment of this disclosure also provides a device for optimizing the temperature model parameters of a wet clutch, combined with... Figure 4 As shown, it includes:

[0093] The processing module is used to obtain the calculated temperature of the hot plate and / or the cold plate through a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0094] The acquisition module is used to acquire the actual temperature of the hot plate and / or the cold plate;

[0095] An iterative calculation module is used to input the calculated temperatures of the hot plate and / or the cold plate into an iterative model established based on key parameters, and to determine the value of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized.

[0096] Furthermore, the processing module includes:

[0097] The power balance calculation module calculates the power distribution for hot plate, cold plate, and cooling oil based on the speed difference, torque, and distribution coefficient.

[0098] The cooling oil quality calculation module calculates the cooling oil quality based on the cooling oil flow rate and cooling oil temperature.

[0099] The hot plate power balance calculation module determines the output power of the hot plate based on the cooling oil quality, the hot plate power distribution, the heat transfer coefficient of the hot plate to the shell, the heat transfer coefficient of the hot plate to the cold plate, and the heat transfer coefficient of the hot plate to the oil.

[0100] The cold plate power balance calculation module determines the output power of the cold plate based on the cooling oil quality, the power distribution of the cold plate, the output power of the hot plate to the cold plate, the heat transfer coefficient of the cold plate to the shell, and the heat transfer coefficient of the cold plate to the oil.

[0101] Furthermore, the iterative calculation module includes:

[0102] The temperature update calculation module determines the calculated temperature of the hot plate and / or cold plate based on the output power of the hot plate, the output power of the cold plate, and the power of the cooling oil distribution.

[0103] The mean square error calculation module performs mean square error calculation based on the calculated temperature and the corresponding actual temperature.

[0104] The optimization processing apparatus disclosed herein employs the aforementioned optimization method to perform heat exchange modeling and analysis on wet clutches. Based on a temperature model established using key parameters, it obtains the calculated temperatures of the hot and / or cold discs; it also obtains the actual temperatures of the hot and / or cold discs; and it inputs the calculated temperatures of the hot and / or cold discs into an iterative model established based on the key parameters for iterative calculation. When the mean square error between the calculated temperature and the corresponding actual temperature reaches its minimum, the optimization objective can be considered achieved. The values ​​of the key parameters at this calculated temperature are then determined, such as the distribution coefficients (the proportion of heat transferred from the hot disc and the proportion of heat transferred from the cooling oil as described herein). The present invention discloses at least one of the following: hot plate heat exchange coefficient (the heat transfer coefficient between the hot plate and the housing, the heat transfer coefficient between the hot plate and the oil, and the heat transfer coefficient between the hot plate and the cold plate as described herein), cold plate heat exchange coefficient (the heat transfer coefficient between the cold plate and the housing, and the heat transfer coefficient between the cold plate and the oil as described herein), cooling oil heat capacity, and clutch disc heat capacity. Compared with the manual verification of optimal values ​​used in traditional technologies, the optimization method disclosed herein can be directly implemented using computers and other equipment, which is more efficient. Furthermore, iterative calculations based on an iterative model established using key parameters can more accurately determine the optimal values ​​of key parameters, which is of great significance for the research of wet clutches.

[0105] A third embodiment of this disclosure also provides a storage medium storing a computer program, which, when executed by a processor, implements the optimized method in the above embodiments, including the following steps:

[0106] S11, the calculated temperature of the hot plate and / or the cold plate is obtained by a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0107] S12, obtain the actual temperature of the hot plate and / or the cold plate;

[0108] S13, input the calculated temperature of the hot plate and / or the cold plate into the iterative model established based on key parameters, and determine the value of the key parameters when the root mean square error between the calculated temperature of the hot plate and / or the cold plate and the corresponding actual temperature is minimized.

[0109] The storage medium disclosed herein stores a computer program capable of executing the aforementioned optimization method. It performs heat exchange modeling and analysis on a wet clutch, obtaining the calculated temperatures of the hot and / or cold discs based on a temperature model established using key parameters; obtaining the actual temperatures of the hot and / or cold discs; inputting the calculated temperatures of the hot and / or cold discs into an iterative model established using key parameters for iterative calculation; and determining the optimal target when the mean square error between the calculated temperature and the corresponding actual temperature reaches its minimum. The program then determines the values ​​of the key parameters at this calculated temperature, such as the distribution coefficients (the heat ratio of the hot disc and the cooling oil transfer coefficients mentioned herein). The optimization method disclosed herein includes at least one of the following: heat ratio, hot plate heat exchange coefficient (the heat transfer coefficient between the hot plate and the housing, the heat transfer coefficient between the hot plate and the oil, and the heat transfer coefficient between the hot plate and the cold plate), cold plate heat exchange coefficient (the heat transfer coefficient between the cold plate and the housing, and the heat transfer coefficient between the cold plate and the oil, as described in this paper), cooling oil heat capacity, and clutch disc heat capacity. Compared with the manual verification of optimal values ​​used in traditional technologies, the optimization method disclosed herein can be directly implemented using computers and other equipment, which is more efficient. Furthermore, iterative calculations based on an iterative model established using key parameters can more accurately determine the optimal values ​​of key parameters, which is of great significance for the research of wet clutches.

[0110] A fourth embodiment of this disclosure provides an electronic device, which includes at least a memory and a processor. The memory stores a computer program, and the processor, when executing the computer program in the memory, implements the method provided in any embodiment of this disclosure. Exemplarily, the computer program steps of the electronic device are as follows: S21 to S23:

[0111] S21, the calculated temperature of the hot plate and / or the cold plate is obtained by a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity.

[0112] S22, Obtain the actual temperature of the hot plate and / or the cold plate;

[0113] S23, input the calculated temperature of the hot plate and / or the cold plate into an iterative model established based on key parameters, and determine the value of the key parameters when the root mean square error between the calculated temperature of the hot plate and / or the cold plate and the corresponding actual temperature is minimized.

[0114] Furthermore, the processor also executes the computer program described in the third embodiment above.

[0115] The electronic device disclosed herein implements the aforementioned computer program to perform heat exchange modeling and analysis on a wet clutch. Based on a temperature model established using key parameters, it obtains the calculated temperatures of the hot and / or cold discs; it also obtains the actual temperatures of the hot and / or cold discs; and it inputs the calculated temperatures of the hot and / or cold discs into an iterative model established using key parameters for iterative calculation. When the mean square error between the calculated temperature and the corresponding actual temperature reaches its minimum, the optimization objective can be considered achieved. The values ​​of the key parameters at this calculated temperature are then determined, such as the distribution coefficients (the proportion of heat transferred from the hot disc and the proportion of heat transferred from the cooling oil as described herein). The hot plate heat exchange coefficient (the heat transfer coefficient between the hot plate and the housing, the heat transfer coefficient between the hot plate and the oil, and the heat transfer coefficient between the hot plate and the cold plate, as described in this paper), the cold plate heat exchange coefficient (the heat transfer coefficient between the cold plate and the housing, and the heat transfer coefficient between the cold plate and the oil, as described in this paper), the cooling oil heat capacity, and the clutch disc heat capacity are all included. Compared with the manual verification of optimal values ​​used in traditional technologies, the optimization method disclosed in this paper can be directly implemented by computers and other equipment, which is more efficient. Furthermore, the iterative calculation based on the iterative model established by the key parameters can more accurately determine the optimal values ​​of the key parameters, which is of great significance for the research of wet clutches.

[0116] The aforementioned storage medium may be included in the aforementioned electronic device; or it may exist independently and not be assembled into the electronic device.

[0117] The aforementioned storage medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to: acquire at least two Internet Protocol (IP) addresses; send a node evaluation request, including at least two IP addresses, to a node evaluation device, wherein the node evaluation device selects an IP address from the at least two IP addresses and returns it; and receive the IP address returned by the node evaluation device; wherein the acquired IP address indicates an edge node in the content delivery network.

[0118] Alternatively, the storage medium may carry one or more programs that, when executed by the electronic device, cause the electronic device to: receive a node evaluation request including at least two Internet Protocol (IP) addresses; select an IP address from the at least two IP addresses; and return the selected IP address; wherein the received IP address indicates an edge node in the content delivery network.

[0119] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the passenger's computer, partially on the passenger's computer, as a standalone software package, partially on the passenger's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the passenger's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0120] It should be noted that the storage medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any storage medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the storage medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0121] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0122] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0123] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0124] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0125] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0126] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0127] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

[0128] The foregoing has provided a detailed description of several embodiments of this disclosure. However, this disclosure is not limited to these specific embodiments. Those skilled in the art can make various variations and modifications based on the concept of this disclosure, and all such variations and modifications should fall within the scope of protection claimed by this disclosure.

Claims

1. A method for optimizing the parameters of a wet clutch temperature model, characterized in that, The wet clutch includes a housing, a clutch disc, and cooling oil; the clutch disc includes a hot disc and a cold disc; the optimization method includes: The calculated temperatures of the hot plate and / or the cold plate are obtained by establishing a temperature model based on key parameters, including at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity. Obtain the actual temperature of the hot plate and / or the cold plate; The calculated temperatures of the hot plate and / or the cold plate are input into an iterative model based on key parameters to determine the values ​​of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized. The step of inputting the calculated temperatures of the hot plate and / or the cold plate into an iterative model established based on key parameters, and determining the values ​​of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized, includes: The calculated temperature of the hot plate is input into the first iterative model, which is determined based on the energy balance equation of the wet clutch and the energy balance equation of the hot plate. The first iterative model is represented by the following equation: ； in, This represents the number of iterations. The calculated temperature of the hot plate; This refers to the temperature of the cooling oil. Sampling time; This represents the percentage of heat generated by the hot plate. The allocation coefficient; For the quality of the clutch disc; The heat capacity of the clutch disc; Torque; For the speed difference; The heat transfer coefficient between the heat plate and the shell; The heat transfer coefficient of the hot plate to the oil; The heat transfer coefficient from the hot plate to the cold plate is given; or, the calculated temperature of the cold plate is input into the second iterative model, which is determined based on the energy balance equation of the wet clutch and the energy balance equation of the cold plate.

2. The optimization method according to claim 1, characterized in that, The step of obtaining the calculated temperature of the hot plate and / or the cold plate through a temperature model established based on key parameters includes: The cooling oil distribution power, hot plate output power, and cold plate output power are determined based on the clutch parameters, the distribution coefficient, and the cooling oil parameters. The calculated temperature of the hot plate and / or the cold plate is determined based on the cooling oil distribution power, the hot plate output power, and the cold plate output power.

3. The optimization method according to claim 2, characterized in that, The determination of cooling oil distribution power, hot plate output power, and cold plate output power based on clutch parameters, the distribution coefficient, and cooling oil parameters includes: The hot plate distribution power, cold plate distribution power, and cooling oil distribution power are determined based on the clutch parameters and the distribution coefficient. The output power of the hot plate is determined based on the hot plate's power distribution, the hot plate's heat exchange coefficient, and the cooling oil quality. The output power of the cold plate is determined based on the cold plate's allocated power, the hot plate's output power, the cold plate's heat exchange coefficient, and the quality of the cooling oil.

4. The optimization method according to claim 3, characterized in that, The quality of the cooling oil is determined by the cooling oil temperature and the cooling oil flow rate.

5. The optimization method according to claim 1, characterized in that, The second iterative model is represented by the following equation: ； in, This represents the number of iterations. The calculated temperature of the cold plate; is the cooling oil temperature; is the sampling time; This represents the percentage of heat generated by the hot plate. The proportion of heat transfer by cooling oil; For the quality of the clutch disc; is the heat capacity of the clutch disc; is the torque; is the speed difference; is the heat transfer coefficient from the cold disc to the housing; The coefficient of heat transfer from the cold plate to the oil is denoted as .

6. An optimization processing device for temperature model parameters of a wet clutch, characterized in that, The apparatus for implementing the optimization method according to any one of claims 1 to 5, comprising: The processing module is used to obtain the calculated temperature of the hot plate and / or the cold plate through a temperature model established based on key parameters, wherein the key parameters include at least one of the following: distribution coefficient, hot plate heat exchange coefficient, cold plate heat exchange coefficient, and clutch plate heat capacity. The acquisition module is used to acquire the actual temperature of the hot plate and / or the cold plate; An iterative calculation module is used to input the calculated temperatures of the hot plate and / or the cold plate into an iterative model established based on key parameters, and to determine the value of the key parameters when the root mean square error between the calculated temperatures of the hot plate and / or the cold plate and the corresponding actual temperatures is minimized.

7. A storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the optimization method according to any one of claims 1 to 5.

8. An electronic device, comprising at least a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program on the memory, it implements the steps of the optimization method according to any one of claims 1 to 5.

Images