CN117787450A - Clutch temperature prediction method, device, electronic equipment and storage medium - Google Patents
Clutch temperature prediction method, device, electronic equipment and storage medium Download PDFInfo
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Abstract
The application provides a clutch temperature prediction method, a device, electronic equipment and a storage medium, wherein the method calculates a clutch temperature prediction value according to a cooling parameter through a pre-constructed temperature prediction model; continuously updating the cooling parameters based on a least square method according to the predicted value and the actually measured value of the clutch temperature; and outputting the target cooling parameter until the sum of squares of errors of the predicted value of the clutch temperature and the actually measured value of the clutch temperature is smaller than a set value or the current iteration number is larger than the set iteration number, inputting the output target cooling parameter into a temperature prediction model, and predicting to obtain the clutch temperature, so that the prediction precision can be improved.
Description
Technical Field
The application relates to the technical field of automobile clutches, in particular to a clutch temperature prediction method, a clutch temperature prediction device, electronic equipment and a storage medium.
Background
The clutch has wide application in automobiles, the temperature prediction of the clutch has important significance for automobiles, and the existing clutch temperature prediction methods have low precision and influence on the performance of automobiles.
Disclosure of Invention
The embodiment of the application mainly aims to provide a clutch temperature prediction method, a clutch temperature prediction device, electronic equipment and a storage medium. The method aims at continuously updating the cooling parameters based on a least square method according to the predicted value and the actually measured value of the clutch temperature to obtain target cooling parameters, and inputting the target cooling parameters into a temperature prediction model to predict the clutch temperature, so that the prediction accuracy can be improved, and the clutch temperature under different working conditions can be predicted.
To achieve the above object, a first aspect of an embodiment of the present application proposes a clutch temperature prediction method, including:
calculating a clutch temperature predicted value according to a cooling parameter of the clutch through a pre-constructed temperature predicted model;
updating the cooling parameter based on a least square method according to the predicted clutch temperature value and the actual clutch temperature value;
returning to a step of calculating a clutch temperature predicted value according to a cooling parameter of a clutch through a pre-constructed temperature predicted model, until an ending condition is met, outputting an updated target cooling parameter, wherein the ending condition comprises a first ending condition or a second ending condition, the first ending condition is that the current iteration number is larger than the set iteration number, and the second ending condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature actual measurement value is smaller than a set value;
and predicting the clutch temperature according to the target cooling parameter through the temperature prediction model.
In some embodiments, the calculating, by using a pre-constructed temperature prediction model, a predicted value of the clutch temperature according to a cooling parameter of the clutch includes:
calculating a convection heat transfer coefficient according to the cooling parameters of the clutch through a pre-constructed temperature prediction model;
and calculating a clutch temperature predicted value according to the convection heat transfer coefficient.
In some embodiments, the updating the cooling parameter based on a least squares method according to the clutch temperature predicted value and the clutch temperature measured value includes:
constructing an objective function according to the predicted clutch temperature value and the actual clutch temperature value;
and solving the objective function by using a least square method to update the cooling parameter.
In some embodiments, the clutch temperature includes a steel sheet temperature and a friction sheet temperature of the clutch, and the predicting, by the temperature prediction model, the clutch temperature according to the target cooling parameter includes:
calculating a steel sheet convective heat transfer coefficient and a friction plate convective heat transfer coefficient according to the target cooling parameters through the temperature prediction model;
according to the convection heat transfer coefficient of the steel sheet, calculating to obtain the steel sheet temperature of the clutch;
and calculating the temperature of the friction plate of the clutch according to the convection heat transfer coefficient of the friction plate.
In some embodiments, the calculating the steel sheet convective heat transfer coefficient and the friction plate convective heat transfer coefficient according to the target cooling parameter by the temperature prediction model is performed by the following formula:
h s ＝k s ·f(Q,Δw,T r )·g(T oil ,u oil )；
h f ＝k f ·f(Q,Δw,T r )·g(T oil ,u oil )；
wherein,
in the formula, h s Represents the convection heat transfer coefficient, k of the steel sheet s Represents the steel sheet constant, f (Q, deltaw, T) r ) Target cooling parameters, the targetThe cooling parameters are the volume flow Q of lubricating oil, the speed difference delta w of friction pair and the transmission torque T of friction pair r Related functions, g (T oil ,u oil ) Represents a function related to the temperature of the lubricating oil and the flow rate of the lubricating oil, h f Represents the convection heat transfer coefficient, k, of the friction plate f Represents the friction plate constant, T r The transmission torque of the friction pair is represented, and N represents the number of the friction pair; μ represents an equivalent friction factor of the friction pair; p is p i Representing the equivalent pressure of the ith friction pair; r represents the equivalent friction radius of the friction pair, R 1 Represents the inner radius, r 2 Representing the outer radius.
In some embodiments, the calculating the temperature of the steel sheet of the clutch according to the convective heat transfer coefficient of the steel sheet is performed by the following formula:
wherein,
wherein T is S (k+1) represents the temperature of the steel sheet at time k+1, T S (k) Represents the temperature of the steel sheet at the moment k, epsilon s The heat distribution coefficient of the steel sheet, deltaw represents the speed difference, m s Representing the mass of the steel sheet c s Indicating the heat specific volume of the steel sheet, h s Representing the convection heat transfer coefficient of the steel sheet, A s The heat exchange area of the steel sheet is represented by T oil (k) Represents the temperature of lubricating oil at time k, lambda s Representing the heat conductivity coefficient, ρ, of the steel sheet s Representing the density of the steel sheet c f Represents the heat specific volume lambda of the friction plate f Indicating the coefficient of thermal conductivity, ρ, of the friction plate f Indicating the density of the friction plate.
In some embodiments, the calculating the friction plate temperature of the clutch according to the friction plate heat convection coefficient is performed by the following formula:
wherein,
wherein T is f (k+1) represents the temperature of the friction plate at time k+1, T f (k) Represents the temperature of the friction plate at the moment k, epsilon f The heat distribution coefficient of the friction plate, deltaw represents the speed difference, m f Representing the mass of the friction plate c f Indicating the heat specific volume, h of the friction plate f Represents the convection heat transfer coefficient of the friction plate, A f T represents the heat exchange area of the friction plate oil (k) Represents the temperature of lubricating oil at time k, lambda s Representing the heat conductivity coefficient, ρ, of the steel sheet s Representing the density of the steel sheet c s Indicating the heat specific volume lambda of the steel sheet f Indicating the coefficient of thermal conductivity, ρ, of the friction plate f Indicating the density of the friction plate.
To achieve the above object, a second aspect of the embodiments of the present application proposes a clutch temperature prediction apparatus, the apparatus comprising:
the calculation module is used for calculating a clutch temperature predicted value according to the cooling parameters of the clutch through a pre-constructed temperature predicted model;
the updating module is used for updating the cooling parameters based on a least square method according to the clutch temperature predicted value and the clutch temperature measured value;
the output module is used for returning to the step of obtaining a clutch temperature predicted value through calculation according to the cooling parameters of the clutch through a pre-constructed temperature predicted model until an ending condition is met, outputting updated target cooling parameters, wherein the ending condition comprises a first ending condition or a second ending condition, the first ending condition is that the current iteration number is larger than the set iteration number, and the second ending condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature actual measurement value is smaller than a set value;
and the prediction module is used for predicting the clutch temperature according to the target cooling parameter through the temperature prediction model.
To achieve the above object, a third aspect of the embodiments of the present application proposes an electronic device, which includes a memory and a processor, the memory storing a computer program, the processor implementing the method according to the first aspect when executing the computer program.
To achieve the above object, a fourth aspect of the embodiments of the present application proposes a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method of the first aspect.
According to the clutch temperature prediction method, the device, the electronic equipment and the storage medium, a clutch temperature prediction value is obtained through calculation according to cooling parameters of a clutch through a pre-constructed temperature prediction model; updating the cooling parameters based on a least square method according to the predicted clutch temperature value and the actual clutch temperature value; returning to the step of calculating a clutch temperature predicted value according to the cooling parameters of the clutch through a pre-constructed temperature predicted model until an ending condition is met, outputting updated target cooling parameters, wherein the ending condition comprises a first ending condition or a second ending condition, the first ending condition is that the current iteration number is larger than the set iteration number, and the second ending condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature measured value is smaller than the set value; and predicting the clutch temperature according to the target cooling parameter by a temperature prediction model. According to the method, cooling parameters are continuously updated based on a least square method according to a predicted clutch temperature value and an actual clutch temperature value to obtain target cooling parameters, and the obtained target cooling parameters are input into a temperature prediction model to be predicted to obtain the clutch temperature, so that prediction accuracy can be improved.
Drawings
FIG. 1 is a flow chart of a clutch temperature prediction method provided by an embodiment of the present application;
FIG. 2 is a schematic illustration of a clutch friction pair segmented according to an embodiment of the present application;
FIG. 3 is a flow chart of updating cooling parameters provided by an embodiment of the present application;
FIG. 4 is a schematic diagram of all updated cooling parameters Map provided by an embodiment of the present application;
fig. 5 is a schematic structural diagram of a clutch temperature prediction device according to an embodiment of the present application;
fig. 6 is a schematic hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
It should be noted that although functional block division is performed in a device diagram and a logic sequence is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart. The terms first, second and the like in the description and in the claims and in the above-described figures, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the present application.
According to the clutch temperature prediction method, according to the clutch temperature prediction value and the clutch temperature actual measurement value, cooling parameters are continuously updated based on a least square method to obtain target cooling parameters, the obtained target cooling parameters are input into a temperature prediction model, the clutch temperature is predicted to be obtained, and prediction accuracy can be improved.
Referring to fig. 1, fig. 1 is a flowchart of a clutch temperature prediction method provided in an embodiment of the present application, and the method in fig. 1 may include, but is not limited to, steps S101 to S104.
Step S101, calculating a clutch temperature predicted value according to a cooling parameter of a clutch through a pre-constructed temperature predicted model;
step S102, updating cooling parameters based on a least square method according to a predicted clutch temperature value and an actual clutch temperature value;
step S103, returning to the step of calculating a clutch temperature predicted value according to the cooling parameters of the clutch through a pre-constructed temperature predicted model, until an end condition is met, outputting updated target cooling parameters, wherein the end condition comprises a first end condition or a second end condition, the first end condition is that the current iteration number is larger than the set iteration number, and the second end condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature measured value is smaller than the set value;
step S104, predicting the clutch temperature according to the target cooling parameters through a temperature prediction model.
In this embodiment, referring to fig. 2, the friction pair of the clutch is segmented, then the transmission torque and the heat distribution coefficient are calculated based on the segmented friction pair, and then the clutch temperature can be calculated according to the transmission torque, the heat distribution and the convective heat transfer coefficient. Thus, a clutch temperature prediction model can be constructed.
Illustratively, friction pairs are divided into 5 equal parts, wherein each friction pair comprises a steel sheet and a friction plate, and the temperatures on each steel sheet and each friction plate segment are uniformly distributed. The clutch transfer torque can be calculated by equation 1:
wherein,
in formula 1, T r The transmission torque of the friction pair is represented, and N represents the number of the friction pair; mu tableShowing the equivalent friction factor of the friction pair; p is p i Representing the equivalent pressure of the ith friction pair; r represents the equivalent friction radius of the friction pair, R 1 Represents the inner radius, r 2 Representing the outer radius.
Then, the heat distribution coefficient of the steel sheet can be calculated according to the formula 2, and the heat distribution coefficient of the friction plate can be calculated according to the formula 3. Wherein:
in formula 2, lambda s Representing the heat conductivity coefficient of the steel sheet c s Representing the heat specific volume, ρ of the steel sheet s Represents the density of the steel sheet lambda f Representing the coefficient of thermal conductivity of the friction plate, c f Indicating the specific heat capacity, ρ, of the friction plate f Indicating the density of the friction plate.
In formula 3, lambda f Representing the coefficient of thermal conductivity of the friction plate, c f Indicating the specific heat capacity, ρ, of the friction plate f Represents the density of the friction plate lambda s Representing the heat conductivity coefficient of the steel sheet c s Representing the heat specific volume, ρ of the steel sheet s Indicating the density of the steel sheet.
The heat distributed to the friction plate and the steel plate can be calculated correspondingly according to the heat distribution coefficients of the steel plate and the friction plate, and then the clutch outlet oil temperature is calculated according to the heat distributed to the friction plate and the steel plate through a formula 4. Wherein:
wherein Q is covf (k)＝ε f ·T r ·Δw，Q covs (k)＝ε s ·T r ·Δw；
Wherein T is i-oilout (k+1) represents the outlet oil temperature at time k+1, T i-oilout (k) Represents the outlet oil temperature at time k, Q covf (k) Indicating that the sliding friction work at time k generates heat distributed to the friction plate, Q covs (k) Indicating that the sliding friction work at time k generates heat distributed to the steel sheet, m oil Representing the mass of the lubricating oil c oil Indicating the specific heat capacity epsilon of the lubricating oil f Indicating the heat distribution coefficient, T, of the friction plate r Represents the transmission torque of the friction pair, deltaw represents the speed difference and epsilon s The heat distribution coefficient of the steel sheet is shown.
The sliding friction work generated by the setting is all converted into heat. According to the heat balance principle and the Newton cooling formula, the convective heat transfer coefficient is introduced, the temperature of the steel sheet at the current moment can be obtained through calculation in the formula 5, and the temperature of the friction sheet at the current moment can be obtained through calculation in the formula 5. Wherein:
in formula 5, T S (k+1) represents the temperature of the steel sheet at time k+1, T S (k) Represents the temperature of the steel sheet at the moment k, epsilon s The heat distribution coefficient of the steel sheet, deltaw represents the speed difference, m s Representing the mass of the steel sheet c s Indicating the heat specific volume of the steel sheet, h s Representing the convection heat transfer coefficient of the steel sheet, A s The heat exchange area of the steel sheet is represented by T oil (k) The temperature of the lubricating oil at time k is indicated.
In 6, T f (k+1) represents the temperature of the friction plate at time k+1, T f (k) Represents the temperature of the friction plate at the moment k, epsilon f The heat distribution coefficient of the friction plate, deltaw represents the speed difference, m f Representing the mass of the friction plate c f Indicating the heat specific volume, h of the friction plate f Represents the convection heat transfer coefficient of the friction plate, A f T represents the heat exchange area of the friction plate oil (k) The temperature of the lubricating oil at time k is indicated.
In equations 5 and 6, the heat convection coefficient h is due to the steel sheet s And the convection heat exchange coefficient h of the friction plate f Is not a physical parameter of the clutch and cannot be obtained, and the convection heat transfer coefficient h of the steel sheet is used s For example, the convective heat transfer coefficient h s Can be calculated by equation 7:
wherein,
in the formula, h s Represents the convection heat transfer coefficient of the steel sheet lambda oil Indicating the heat conductivity coefficient of the lubricating oil; lambda (lambda) s Representing the characteristic length of the steel sheet; re (Re) s At Reynolds number, p r Being Plantt number, u s Is the relative speed of lubricating oil and steel sheet, v oil Is the dynamic viscosity of lubricating oil; ρ oil For lubricating oil density, c oil Is the specific heat capacity of the lubricating oil.
Wherein the Plantain number p r The numerical value of the parameter related to the physical property parameter of the lubricating oil is related to the temperature of the lubricating oil, and the parameter can be obtained through calculation by looking up a table of the clutch oil temperature. Reynolds number Re s Is related to the flow speed and temperature of lubricating oil, but is difficult to directly measure, thereby leading to the convective heat transfer coefficient h of the steel sheet s And cannot be directly calculated from the measured values. Likewise, the friction plate has a coefficient of convective heat transfer h f And cannot be directly calculated from the measured values.
Based on the above, the embodiment of the application needs to firstly heat convection coefficient h of the steel sheet s And the convection heat exchange coefficient h of the friction plate f Conversion is carried out, and the convection heat transfer coefficient h of the steel sheet is also used s For example, the convection heat transfer coefficient h of the steel sheet s The conversion formula of (2) is formula 8:
h s ＝k s ·f(Q,Δw,T r )·g(T oil ,u oil ) (formula 8);
in the formula, h s Represents the convection heat transfer coefficient, k of the steel sheet s Represents the steel sheet constant, f (Q, deltaw, T) r ) Target cooling parameters, which are the volume flow Q of the lubricating oil, the friction pair speed difference Deltaw and the friction pair transmission torque T r Related functions, g (T oil ,u oil ) Representing a function related to the temperature of the lubricating oil and the flow rate of the lubricating oil.
Wherein the function g (T oil ,u oil ) Can be calculated from the physical properties of the lubricating oil and from the data of the oil temperature look-up table, thus calculating the target cooling parameters f (Q, deltaw, T r ) The convective heat transfer coefficient h of the steel sheet can be calculated s And the heat convection coefficient of the steel sheet is calculated, so that the temperature of the steel sheet can be further calculated.
It will be appreciated that, as such, the friction plate will have a coefficient of heat convection h f The transformation can also be performed in the same way so that the target cooling parameters f (Q, deltaw, T) are calculated r ) The convection heat exchange coefficient h of the friction plate can be calculated f And the heat convection coefficient of the friction plate is calculated, so that the temperature of the friction plate can be further calculated.
In the embodiment of the application, in order to obtain the target cooling parameters f (Q, deltaw, T r ) Firstly, initializing each parameter in a temperature prediction model, then starting operation, calculating a clutch temperature prediction value according to the initial cooling parameter through the temperature prediction model, and then obtaining a clutch temperature actual measurement value under the current working condition, wherein the clutch temperature actual measurement value can be obtained through the following test measurement:
the measured clutch temperature value can be measured by a clutch steel sheet temperature remote measuring device. The clutch steel sheet temperature telemetry equipment comprises a plurality of temperature sensor signal lines which are respectively connected with temperature sensors arranged at the positions of the steel sheets so as to measure and obtain the temperature of each steel sheet. Illustratively, a temperature sensor is embedded at the steel plate of the clutch, wherein the inner radius of the clutch friction pair is r 1 External radius of clutch friction pair r =64 mm 2 The radial maximum temperature during sliding grinding can be acquired by the method of =90 mm, and the flow of the clutch cooling lubricating oil is set to be 12.5L +.min, the transmission torque was 50Nm, 100Nm, 150Nm, and the friction pair speed difference was 750rpm, 1500rpm, 2500rpm (friction plate rotational speed was 0). The temperature profile of the clutch at a transmitted torque of 50Nm and friction pair speed differential of 750rpm, 1500rpm, 2500rpm, respectively, can be measured. Meanwhile, the temperature change curve of the clutch under the working conditions of 100Nm of transmission torque and 750rpm, 1500rpm and 2500rpm of friction pair speed difference can be measured. The temperature profile of the clutch at a transmission torque of 150Nm and friction pair speed differential of 750rpm, 1500rpm, 2500rpm, respectively, can also be measured.
Specifically, the measurement test steps are: the method comprises the steps of firstly setting the rotation speeds of a driving motor and a load motor, such as by setting the rotation speeds of the driving motor and the load motor to enable the friction pair speed difference to be 750rpm, setting the cooling flow, then gradually increasing the clutch pressure until reaching the target transmission torque, such as 50Nm, performing slip grinding for a period of time, then releasing the clutch, entering a clutch cooling stage, and finally adjusting the motor rotation speed to 0, thus completing one test. Then, by setting the rotation speeds of the driving motor and the load motor to make the friction pair speed difference be 1500rpm, setting the cooling flow, then gradually increasing the clutch pressure until reaching the target transmission torque, for example, after reaching 50Nm, sliding and grinding for a period of time, then releasing the clutch, entering the clutch cooling stage, and finally adjusting the motor rotation speed to 0, thus completing one test. In this way, all experiments were completed.
It can be understood that the temperature change of the clutch under different working conditions can be measured through a test, so that after the temperature predicted value of the clutch is calculated through a temperature prediction model, the clutch temperature actual measurement value under the same working condition can be obtained through the test.
And further constructing an objective function after the temperature predicted value and the clutch temperature measured value of the clutch are obtained, and optimally solving the objective function by using a least square method so as to update the cooling coefficient. Specifically, the objective function constructed is shown in formula 9:
in formula 9, F (x) represents an objective function, F (x) i ) For the ith clutch temperature prediction value, y i And the measured value is the ith clutch temperature, m is the sampling point number, and x is the cooling parameter. The meaning of the objective function is to solve for a target cooling parameter such that the sum of squares of the errors between the predicted and measured clutch temperature values is minimized.
In the embodiment of the application, a nonlinear least square method based on a trust domain algorithm is adopted to carry out optimal solution on the objective function. Based on the definition of trust domain algorithm, at each feasible point x k At a given trust zone radius r k The search direction d is solved by 10:
wherein s.t d is less than or equal to r k 。
After obtaining the search direction d according to the method 10, the search direction d is then used for determining the radius r of the trust zone k And (5) carrying out correction, and continuously iterating until the convergence condition is met or the maximum iteration number is reached, and ending the calculation.
Wherein, using equation 11, according to coefficient ρ k Whether the search direction d is reasonable or not is judged by the size of (2).
In the kth iterative calculation, u is the lower bound of the trusted region, and η is the upper bound of the trusted region, where η= (r-r) 1 )/(r 2 -r 1 ) And r is the position of the sensor measuring point. Specifically, according to the calculated ρ k Comparing with the lower boundary u of the trust domain and the upper boundary eta of the trust domain, whether the search area is suitable or not can be determined, and corresponding adjustment can be carried out according to the judgment result.
If ρ k <u, the search area is considered to be too large, and at this time, the radius of the trust area needs to be reduced to makeUnadjusted search center point x k Is a value of (2);
if u<ρ k <η is the search area is considered to be moderate, and the radius r of the confidence area is not adjusted k Adjusting the value of x of the search center point k Value, let x k+1 ＝x k +d；
If ρ k >η, consider that the search area is too small, and enlarge the radius of the trust area to makeAdjusting the center point x k Let x be k+1 ＝x k +d。
In the embodiment of the present application, the iteration convergence and end conditions and the trust zone upper and lower bounds are set as shown in table 1.
Table 1 parameter settings of least squares method
| Tolerance to errors | Maximum number of iterations | Trust domain lower bound | Trust domain lower bound |
| 0.001 | 100 | 0.25 | 0.75 |
Referring to fig. 3, fig. 3 is a flowchart of updating cooling parameters provided in an embodiment of the present application, including but not limited to steps S301 to S307.
Step S301, initializing parameters of a temperature prediction model;
step S302, calculating a temperature prediction model to obtain a clutch temperature prediction value;
step S303, constructing an objective function according to the predicted clutch temperature value and the actual clutch temperature value;
step S304, solving an objective function by using a least square method to update cooling parameters;
step S305, judging whether the current iteration number is larger than the set maximum iteration number; if the current iteration times are greater than the set maximum iteration times, outputting target cooling parameters;
step S306, if the current iteration times are not greater than the set maximum iteration times, judging whether the error square sum of the predicted clutch temperature value and the actually measured clutch temperature value is smaller than a set value;
step S307, if the sum of the squares of the errors of the predicted clutch temperature value and the measured clutch temperature value is smaller than the set value, outputting the target cooling parameter, and if the sum of the squares of the errors of the predicted clutch temperature value and the measured clutch temperature value is not smaller than the set value, returning to step S302.
Referring to fig. 4, fig. 4 is a schematic diagram of all updated cooling parameters Map provided in the embodiment of the present application, where the local maximum value in fig. 4 is the maximum cooling parameter number corresponding to the speed difference of 1500rpm and 2600rpm, and the local maximum value indicates that, for the same speed difference, there is an optimal cooling parameter under different clutch pressure working conditions so that the friction pair temperature is the lowest, where the cooling parameter is only related to the lubricating oil volumetric flow Q, so that there is an optimal lubricating oil volumetric flow Q so that the cooling parameter is the highest.
In the embodiment of the application, the cooling parameters are continuously updated through the least square method to finally obtain the optimal target cooling parameters, so that the clutch temperature predicted by the temperature prediction model is closest to the actual temperature of the clutch. And inputting the updated target cooling parameters into a temperature prediction model, so that the temperature prediction model can predict and obtain clutch temperature according to the target cooling parameters, wherein the clutch temperature comprises the steel sheet temperature and the friction plate temperature of the clutch. By inputting the updated target cooling parameters, the prediction accuracy of the temperature prediction model can be improved.
Referring to fig. 5, an embodiment of the present application further provides a clutch temperature prediction apparatus 50, which may implement the above-mentioned clutch temperature prediction method, where the apparatus includes:
the calculating module 501 is configured to calculate a predicted clutch temperature value according to a cooling parameter of the clutch through a pre-constructed temperature prediction model;
the updating module 502 is configured to update the cooling parameter based on a least square method according to the predicted clutch temperature value and the measured clutch temperature value;
an output module 503, configured to return to the step of calculating, according to the cooling parameter of the clutch by using the pre-constructed temperature prediction model, a predicted value of the clutch temperature until an end condition is satisfied, and output an updated target cooling parameter, where the end condition includes a first end condition or a second end condition, the first end condition is that the current iteration number is greater than the set iteration number, and the second end condition is that a sum of squares of errors between the predicted value of the clutch temperature and the actually measured value of the clutch temperature is less than the set value;
the prediction module 504 is configured to predict a clutch temperature according to the target cooling parameter through a temperature prediction model.
The specific embodiment of the clutch temperature prediction device is basically the same as the specific embodiment of the clutch temperature prediction method, and will not be described herein.
The embodiment of the application also provides electronic equipment, which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the clutch temperature prediction method when executing the computer program. The electronic equipment can be any intelligent terminal including a tablet personal computer, a vehicle-mounted computer and the like.
Referring to fig. 6, fig. 6 illustrates a hardware structure of an electronic device according to another embodiment, the electronic device includes:
the processor 601 may be implemented by a general-purpose CPU (central processing unit), a microprocessor, an application-specific integrated circuit (ApplicationSpecificIntegratedCircuit, ASIC), or one or more integrated circuits, etc. for executing related programs to implement the technical solutions provided by the embodiments of the present application;
the memory 602 may be implemented in the form of read-only memory (ReadOnlyMemory, ROM), static storage, dynamic storage, or random access memory (RandomAccessMemory, RAM). The memory 602 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present application are implemented by software or firmware, relevant program codes are stored in the memory 602, and the processor 601 invokes the clutch temperature prediction method to execute the embodiments of the present application;
an input/output interface 603 for implementing information input and output;
the communication interface 604 is configured to implement communication interaction between the present device and other devices, and may implement communication in a wired manner (such as USB, network cable, etc.), or may implement communication in a wireless manner (such as mobile network, WI F I, bluetooth, etc.);
a bus 605 for transferring information between the various components of the device (e.g., the processor 601, memory 602, input/output interface 603, and communication interface 604);
wherein the processor 601, the memory 602, the input/output interface 603 and the communication interface 604 are communicatively coupled to each other within the device via a bus 605.
The embodiment of the application also provides a storage medium, wherein the storage medium is a computer readable storage medium, and a computer program is stored in the storage medium, and when the computer program is executed by a processor, the clutch temperature prediction method is realized.
The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The embodiments described in the embodiments of the present application are for more clearly describing the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application, and as those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are equally applicable to similar technical problems.
It will be appreciated by those skilled in the art that the technical solutions shown in the figures do not constitute limitations of the embodiments of the present application, and may include more or fewer steps than shown, or may combine certain steps, or different steps.
The above described apparatus embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Those of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof.
The terms "first," "second," "third," "fourth," and the like in the description of the present application and in the above-described figures, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the present application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in this application, "at least one" means one or more, and "a plurality" means two or more. "and/or" for describing the association relationship of the association object, the representation may have three relationships, for example, "a and/or B" may represent: only a, only B and both a and B are present, wherein a, B may be singular or plural. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one of" or the like means any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (one) of a, b or c may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the above-described division of units is merely a logical function division, and there may be another division manner in actual implementation, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including multiple instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the various embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing a program.
Preferred embodiments of the present application are described above with reference to the accompanying drawings, and thus do not limit the scope of the claims of the embodiments of the present application. Any modifications, equivalent substitutions and improvements made by those skilled in the art without departing from the scope and spirit of the embodiments of the present application shall fall within the scope of the claims of the embodiments of the present application.
Claims (10)
1. A method of clutch temperature prediction, the method comprising:
calculating a clutch temperature predicted value according to a cooling parameter of the clutch through a pre-constructed temperature predicted model;
updating the cooling parameter based on a least square method according to the predicted clutch temperature value and the actual clutch temperature value;
returning to a step of calculating a clutch temperature predicted value according to a cooling parameter of a clutch through a pre-constructed temperature predicted model, until an ending condition is met, outputting an updated target cooling parameter, wherein the ending condition comprises a first ending condition or a second ending condition, the first ending condition is that the current iteration number is larger than the set iteration number, and the second ending condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature actual measurement value is smaller than a set value;
and predicting the clutch temperature according to the target cooling parameter through the temperature prediction model.
2. The method according to claim 1, wherein the calculating the predicted clutch temperature value according to the cooling parameter of the clutch by the pre-constructed temperature prediction model includes:
calculating a convection heat transfer coefficient according to the cooling parameters of the clutch through a pre-constructed temperature prediction model;
and calculating a clutch temperature predicted value according to the convection heat transfer coefficient.
3. The method of claim 1, wherein updating the cooling parameter based on a least squares method based on the predicted clutch temperature value and the measured clutch temperature value comprises:
constructing an objective function according to the predicted clutch temperature value and the actual clutch temperature value;
and solving the objective function by using a least square method to update the cooling parameter.
4. The method of claim 1, wherein the clutch temperature comprises a steel plate temperature and a friction plate temperature of the clutch, and wherein predicting the clutch temperature from the target cooling parameter by the temperature prediction model comprises:
calculating a steel sheet convective heat transfer coefficient and a friction plate convective heat transfer coefficient according to the target cooling parameters through the temperature prediction model;
according to the convection heat transfer coefficient of the steel sheet, calculating to obtain the steel sheet temperature of the clutch;
and calculating the temperature of the friction plate of the clutch according to the convection heat transfer coefficient of the friction plate.
5. The method of claim 4, wherein said calculating by said temperature prediction model from said target cooling parameters to obtain a steel sheet heat convection coefficient and a friction sheet heat convection coefficient is performed by the following formula:
h s ＝k s ·f(Q,Δw,T r )·g(T oil ,u oil )；
h f ＝k f ·f(Q,Δw,T r )·g(T oil ,u oil )；
wherein,
in the formula, h s Represents the convection heat transfer coefficient, k of the steel sheet s Represents the steel sheet constant, f (Q, deltaw, T) r ) A target cooling parameter, which is the volume flow Q of the lubricating oil, the speed difference delta w of the friction pair and the transmission torque T of the friction pair r Related functions, g (T oil ,u oil ) Represents a function related to the temperature of the lubricating oil and the flow rate of the lubricating oil, h f Represents the convection heat transfer coefficient, k, of the friction plate f Represents the friction plate constant, T r The transmission torque of the friction pair is represented, and N represents the number of the friction pair; μ represents an equivalent friction factor of the friction pair; p is p i Representing the equivalent pressure of the ith friction pair; r represents the equivalent friction radius of the friction pair, R 1 Represents the inner radius, r 2 Representing the outer radius.
6. The method of claim 4, wherein calculating a sheet temperature of the clutch based on the sheet convective heat transfer coefficient is performed by the following equation:
wherein,
wherein T is S (k+1) represents the temperature of the steel sheet at time k+1, T S (k) Represents the temperature of the steel sheet at the moment k, epsilon s The heat distribution coefficient of the steel sheet, deltaw represents the speed difference, m s Representing the mass of the steel sheet c s Indicating the heat specific volume of the steel sheet, h s Representing the convection heat transfer coefficient of the steel sheet, A s The heat exchange area of the steel sheet is represented by T oil (k) Represents the temperature of lubricating oil at time k, lambda s Representing the heat conductivity coefficient, ρ, of the steel sheet s Representing the density of the steel sheet c f Represents the heat specific volume lambda of the friction plate f Indicating the coefficient of thermal conductivity, ρ, of the friction plate f Indicating the density of the friction plate.
7. The method of claim 4, wherein calculating a friction plate temperature of the clutch based on the friction plate convective heat transfer coefficient is performed by the following equation:
wherein,
wherein T is f (k+1) represents the temperature of the friction plate at time k+1, T f (k) Represents the temperature of the friction plate at the moment k, epsilon f The heat distribution coefficient of the friction plate, deltaw represents the speed difference, m f Representing the mass of the friction plate c f Indicating the heat specific volume, h of the friction plate f Represents the convection heat transfer coefficient of the friction plate, A f T represents the heat exchange area of the friction plate oil (k) Represents the temperature of lubricating oil at time k, lambda s Representing the heat conductivity coefficient, ρ, of the steel sheet s Representing the density of the steel sheet c s Indicating the heat specific volume lambda of the steel sheet f Indicating the coefficient of thermal conductivity, ρ, of the friction plate f Indicating the density of the friction plate.
8. A clutch temperature prediction apparatus, characterized in that the apparatus comprises:
the calculation module is used for calculating a clutch temperature predicted value according to the cooling parameters of the clutch through a pre-constructed temperature predicted model;
the updating module is used for updating the cooling parameters based on a least square method according to the clutch temperature predicted value and the clutch temperature measured value;
the output module is used for returning to the step of obtaining a clutch temperature predicted value through calculation according to the cooling parameters of the clutch through a pre-constructed temperature predicted model until an ending condition is met, outputting updated target cooling parameters, wherein the ending condition comprises a first ending condition or a second ending condition, the first ending condition is that the current iteration number is larger than the set iteration number, and the second ending condition is that the square sum of errors between the clutch temperature predicted value and the clutch temperature actual measurement value is smaller than a set value;
and the prediction module is used for predicting the clutch temperature according to the target cooling parameter through the temperature prediction model.
9. An electronic device comprising a memory storing a computer program and a processor implementing the method of any of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method of any one of claims 1 to 7.
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| CN202211152489.5A CN117787450A (en) | 2022-09-21 | 2022-09-21 | Clutch temperature prediction method, device, electronic equipment and storage medium |
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| CN202211152489.5A CN117787450A (en) | 2022-09-21 | 2022-09-21 | Clutch temperature prediction method, device, electronic equipment and storage medium |
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