Method and device for calculating internal temperature of vehicle battery
By constructing a battery equivalent circuit model and a lumped parameter model, and combining the LSTM model, the internal temperature of the vehicle battery is accurately calculated, which solves the problem that external sensors in the prior art cannot accurately capture the internal temperature gradient of the battery, and improves the calculation accuracy.
Patent Information
- Application Number
- CN202411528065.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-30
- Publication Date
- 2025-02-18
AI Technical Summary
Existing vehicle battery temperature measurement methods rely on external sensors and cannot accurately capture the internal temperature gradient of the battery, making it difficult to clearly express the process from the battery to the heat transfer process, affecting the accuracy of the internal temperature calculation of the battery.
By constructing a battery equivalent circuit model, obtaining the internal parameters of the battery, establishing a battery lumped parameter model, performing dynamic working condition tests, calculating parameter vectors, using the LSTM model to determine the temperature relationship, calculate the error correction value, and accurately calculate the internal temperature of the battery.
It improves the accuracy of internal temperature calculation of the battery, can clearly express the process of heat generation to heat transfer of the battery, and solves the problem that external sensors cannot accurately capture the internal temperature gradient.
Smart Images
Figure CN119475992A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of lithium batteries, and in particular to a method and device for calculating the internal temperature of a vehicle battery. Background Art
[0002] The battery's charge and discharge performance, capacity characteristics and cycle life are all affected by temperature. Under high temperature conditions, the battery's chemical reaction rate accelerates, which may cause the battery to age faster and threaten the battery's safety.
[0003] However, existing vehicle battery temperature measurement methods often rely on the layout of external sensors, but these sensors cannot accurately capture the temperature gradient inside the battery, and it is difficult to clearly express the process of battery heat generation to heat transfer, which greatly affects the calculation accuracy of the internal battery temperature and needs to be solved urgently. Summary of the invention
[0004] The present application provides a method and device for calculating the internal temperature of a vehicle battery to solve the problems that the existing vehicle battery temperature measurement technology often relies on the arrangement of external sensors, cannot accurately capture the temperature gradient inside the battery, and has difficulty in clearly expressing the process from battery heat generation to heat transfer, which greatly affects the calculation accuracy of the internal battery temperature.
[0005] The first aspect of the present application provides a method for calculating the internal temperature of a vehicle battery, comprising the following steps: constructing a battery equivalent circuit model of a square shell battery in the current vehicle, and obtaining the battery internal parameters of the square shell battery based on the battery equivalent circuit model; constructing a battery lumped parameter model of the square shell battery according to the battery internal parameters, and performing a dynamic operating condition test on the square shell battery to obtain the temperature value and current value of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery; based on the temperature value and the current value, and in combination with the battery lumped parameter model, respectively calculating the parameter vectors corresponding to the inside of the shell, the positive and negative poles, and the shell part, and determining the temperature relationship between the inside of the shell, the positive and negative poles, and the shell part according to the parameter vector and a pre-trained LSTM model, and calculating an error correction value through the temperature relationship, so as to calculate the temperature value of the inside of the shell using the error correction value.
[0006] Optionally, in one embodiment of the present application, constructing a battery equivalent circuit model of the square shell battery in the current vehicle, and obtaining the battery internal parameters of the square shell battery based on the battery equivalent circuit model, includes: constructing a battery equivalent circuit model of the square shell battery in the current vehicle based on a preset Thevenin model; performing an HPPC operating condition test on the square shell battery based on the battery equivalent circuit model to obtain the battery internal parameters, and establishing a mapping relationship between the battery internal parameters and the battery remaining power and temperature.
[0007] Optionally, in one embodiment of the present application, the battery lumped parameter model of the square shell battery is constructed according to the internal parameters of the battery, and the square shell battery is subjected to a dynamic operating condition test to obtain the temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery, including: based on a preset Bernardi heat generation model, calculating the internal heat of the battery of the square shell battery, and constructing the heat generation model of the square shell battery according to the internal heat of the battery and the mapping relationship; calculating the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface, and the air convection heat dissipation of the square shell battery, and constructing the heat dissipation model of the square shell battery according to the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface, and the air convection heat dissipation; based on the heat generation model and the heat dissipation model, determining the heat conduction equation of the square shell battery, and performing a CLTC operating condition test on the square shell battery according to the heat conduction equation to record the temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part under the CLTC operating condition.
[0008] Optionally, in one embodiment of the present application, based on the temperature value and the current value, and in combination with the battery lumped parameter model, to respectively calculate the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part, including: determining a matrix form heat generation model based on the heat generation model, the heat conduction equation, the temperature value, and the current value; calculating the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part according to the matrix form heat generation model and a preset least squares strategy.
[0009] Optionally, in one embodiment of the present application, the temperature relationship between the inside of the shell, the positive and negative poles and the shell part is determined according to the parameter vector and the pre-trained LSTM model, and the error correction value is calculated through the temperature relationship to calculate the temperature value inside the shell using the error correction value, including: based on the parameter vector, the temperature value and the current value, and in combination with the pre-trained LSTM model, to obtain the temperature relationship; obtain the pole temperature and the ambient temperature of the square shell battery, and calculate the error correction value corresponding to the LSTM model according to the pole temperature and the ambient temperature; determine the temperature parameters inside the shell according to the temperature relationship, and calculate the temperature value inside the shell based on the pole temperature, the error correction value and the temperature parameters inside the shell.
[0010] A second aspect of the present application provides a device for calculating the internal temperature of a vehicle battery, comprising: a modeling module, used to construct a battery equivalent circuit model of a square shell battery in the current vehicle, and based on the battery equivalent circuit model, obtain the battery internal parameters of the square shell battery; a testing module, used to construct a battery lumped parameter model of the square shell battery according to the battery internal parameters, and perform a dynamic operating condition test on the square shell battery to obtain the temperature value and current value of the inside of the shell, the positive and negative poles and the shell part of the square shell battery; a calculation module, used to calculate the parameter vectors corresponding to the inside of the shell, the positive and negative poles and the shell part respectively based on the temperature value and the current value and in combination with the battery lumped parameter model, and determine the temperature relationship between the inside of the shell, the positive and negative poles and the shell part according to the parameter vector and a pre-trained LSTM model, and calculate the error correction value through the temperature relationship, so as to calculate the temperature value of the inside of the shell using the error correction value.
[0011] Optionally, in one embodiment of the present application, the modeling module includes: a first construction unit, used to construct a battery equivalent circuit model of the square shell battery in the current vehicle based on a preset Thevenin model; an establishment unit, used to perform an HPPC operating condition test on the square shell battery based on the battery equivalent circuit model to obtain the internal parameters of the battery, and establish a mapping relationship between the internal parameters of the battery and the remaining power and temperature of the battery.
[0012] Optionally, in one embodiment of the present application, the test module includes: a second construction unit, used to calculate the internal heat of the square shell battery based on a preset Bernardi heat generation model, and construct the heat generation model of the square shell battery according to the internal heat of the battery and the mapping relationship; a first calculation unit, used to calculate the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface and the heat dissipation of air convection of the square shell battery, and construct the heat dissipation model of the square shell battery according to the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface and the heat dissipation of air convection; a recording unit, used to determine the heat conduction equation of the square shell battery based on the heat generation model and the heat dissipation model, and perform a CLTC operating condition test on the square shell battery according to the heat conduction equation to record the temperature values and current values of the inside of the shell, the positive and negative poles and the shell part under the CLTC operating condition.
[0013] Optionally, in one embodiment of the present application, the calculation module includes: a first determination unit, used to determine the matrix form heat generation model based on the heat generation model, the heat conduction equation, the temperature value and the current value; a second operation unit, used to calculate the parameter vectors corresponding to the interior of the shell, the positive and negative poles and the shell part according to the matrix form heat generation model and a preset least squares strategy.
[0014] Optionally, in one embodiment of the present application, the calculation module also includes: a first acquisition unit, used to acquire the temperature relationship based on the parameter vector, the temperature value and the current value, and combined with a pre-trained LSTM model; a second acquisition unit, used to acquire the pole temperature and the ambient temperature of the square shell battery, and calculate the error correction value corresponding to the LSTM model based on the pole temperature and the ambient temperature; a second determination unit, used to determine the internal temperature parameters of the shell according to the temperature relationship, and calculate the temperature value inside the shell based on the pole temperature, the error correction value and the internal temperature parameters of the shell.
[0015] A third aspect of the present application provides a vehicle, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating the internal temperature of a vehicle battery as described in the above embodiment.
[0016] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, implements the above method for calculating the internal temperature of a vehicle battery.
[0017] A fifth aspect of the present application provides a computer program product, including a computer program, which is executed to implement the above-mentioned method for calculating the internal temperature of a vehicle battery.
[0018] Therefore, the embodiments of the present application have the following beneficial effects:
[0019] The embodiments of the present application can construct a battery equivalent circuit model of the square shell battery in the current vehicle, and obtain the battery internal parameters of the square shell battery based on the battery equivalent circuit model; construct a battery lumped parameter model of the square shell battery according to the internal parameters of the battery, and perform a dynamic working condition test on the square shell battery to obtain the temperature value and current value of the shell interior, positive and negative poles and shell part of the square shell battery; based on the temperature value and current value, and in combination with the battery lumped parameter model, respectively calculate the parameter vectors corresponding to the shell interior, positive and negative poles and shell part, and determine the temperature relationship between the shell interior, positive and negative poles and shell part according to the parameter vector and the pre-trained LSTM model, and calculate the error correction value through the temperature relationship, so as to calculate the temperature value inside the shell using the error correction value. The present application models the heat generation and heat dissipation of the battery by using the lumped parameter model, establishes the electric and thermal coupling model of the battery, and divides the battery temperature into three parts: internal temperature, pole temperature and shell temperature, calculates the thermal conduction of the battery respectively, and dynamically corrects the heat generation and heat dissipation model coefficients through different working condition data, so as to clearly express the process from heat generation to heat transfer of the battery, and improve the calculation accuracy of the internal temperature of the battery. This solves the problem that existing vehicle battery temperature measurement technology often relies on the layout of external sensors, cannot accurately capture the temperature gradient inside the battery, has difficulty clearly expressing the process of heat generation to heat transfer in the battery, and greatly affects the calculation accuracy of the internal battery temperature.
[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:
[0022] Figure 1 A flow chart of a method for calculating the internal temperature of a vehicle battery provided according to an embodiment of the present application;
[0023] Figure 2 A schematic diagram of a Thevenin model provided for one embodiment of the present application;
[0024] Figure 3 A schematic diagram of the execution logic of a method for calculating the internal temperature of a vehicle battery provided by one embodiment of the present application;
[0025] Figure 4 A schematic diagram of the internal, pole and shell temperatures of a battery provided for one embodiment of the present application;
[0026] Figure 5 A schematic diagram of a long short-term memory neural network model provided for one embodiment of the present application;
[0027] Figure 6 This is an example diagram of a device for calculating the internal temperature of a vehicle battery according to an embodiment of the present application;
[0028] Figure 7 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application.
[0029] Among them, 10 is a calculation device for the internal temperature of the vehicle battery, 100 is a modeling module, 200 is a testing module, 300 is a calculation module, 701 is a memory, 702 is a processor, and 703 is a communication interface. DETAILED DESCRIPTION
[0030] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.
[0031] The following describes the method and device for calculating the internal temperature of the vehicle battery of the embodiment of the present application with reference to the accompanying drawings. In response to the problems mentioned in the above background technology, the present application provides a method for calculating the internal temperature of the vehicle battery, in which the battery equivalent circuit model of the square shell battery in the current vehicle is constructed, and the battery internal parameters of the square shell battery are obtained based on the battery equivalent circuit model; the battery lumped parameter model of the square shell battery is constructed according to the internal parameters of the battery, and the square shell battery is subjected to a dynamic working condition test to obtain the temperature value and current value of the shell interior, positive and negative poles and shell part of the square shell battery; based on the temperature value and current value, and in combination with the battery lumped parameter model, the parameter vectors corresponding to the shell interior, positive and negative poles and shell part are calculated respectively, and the temperature relationship between the shell interior, positive and negative poles and shell part is determined according to the parameter vector and the pre-trained LSTM model, and the error correction value is calculated by the temperature relationship, so as to calculate the temperature value of the shell interior using the error correction value. This application uses a lumped parameter model to model the heat generation and heat dissipation of the battery, establishes an electrothermal coupling model of the battery, and divides the battery temperature into three parts: internal temperature, pole temperature, and shell temperature. The thermal conduction of the battery is calculated separately, and the heat generation and heat dissipation model coefficients are dynamically corrected through different operating condition data, so that the process from battery heat generation to heat transfer can be clearly expressed, and the calculation accuracy of the internal temperature of the battery can be improved. In this way, the existing vehicle battery temperature measurement technology often relies on the arrangement of external sensors, cannot accurately capture the temperature gradient inside the battery, and is difficult to clearly express the process from battery heat generation to heat transfer, which greatly affects the calculation accuracy of the internal temperature of the battery.
[0032] Specifically, Figure 1 A flow chart of a method for calculating the internal temperature of a vehicle battery provided in an embodiment of the present application.
[0033] like Figure 1 As shown, the method for calculating the internal temperature of the vehicle battery includes the following steps:
[0034] In step S101, a battery equivalent circuit model of the square shell battery in the current vehicle is constructed, and based on the battery equivalent circuit model, the battery internal parameters of the square shell battery are obtained.
[0035] The embodiments of the present application may first select the square shell battery corresponding to the current vehicle, and use the Thevenin equivalent model to establish a battery equivalent circuit model; thereafter, the embodiments of the present application may perform HPPC testing on the battery at different temperatures to obtain the internal parameters of the battery, thereby establishing the relationship between the battery internal resistance and SOC (State Of Charge, remaining battery capacity) and temperature.
[0036] Optionally, in one embodiment of the present application, a battery equivalent circuit model of the square shell battery in the current vehicle is constructed, and based on the battery equivalent circuit model, the battery internal parameters of the square shell battery are obtained, including: constructing a battery equivalent circuit model of the square shell battery in the current vehicle based on a preset Thevenin model; based on the battery equivalent circuit model, performing an HPPC operating condition test on the square shell battery to obtain the battery internal parameters, and establishing a mapping relationship between the battery internal parameters and the battery remaining power and temperature.
[0037] It should be noted that the embodiment of the present application uses square shell batteries and adopts the Thevenin model to construct a battery equivalent circuit model, such as Figure 2 As shown, the battery is tested under HPPC conditions at different temperatures (experimental temperature range is -20℃~45℃) and different SOCs (experimental SOC range is 5%~95%) to obtain the internal resistance at different temperatures and battery remaining capacity, and the mapping relationship R of the internal resistance is obtained. (SOC,T) , thereby providing reliable data guidance and basis for the subsequent estimation of the internal temperature of the battery.
[0038] In step S102, a battery lumped parameter model of the square shell battery is constructed according to the internal parameters of the battery, and a dynamic operating condition test is performed on the square shell battery to obtain the temperature and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery.
[0039] Furthermore, if Figure 3 As shown, the embodiment of the present application also needs to construct a battery lumped parameter model of a square shell battery according to the internal parameters of the battery, and divide the battery into three parts: the inside of the battery shell, the positive and negative poles of the battery, and the battery shell part, such as Figure 4 As shown; thereafter, the embodiments of the present application need to perform charging, discharging and static tests at different temperatures to record the temperature values and current values of the three parts of the battery.
[0040] Optionally, in one embodiment of the present application, a battery lumped parameter model of a square shell battery is constructed according to the internal parameters of the battery, and a dynamic operating condition test is performed on the square shell battery to obtain the temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery, including: based on a preset Bernardi heat generation model, calculating the internal heat of the battery of the square shell battery, and constructing a heat generation model of the square shell battery according to the internal heat of the battery and the mapping relationship; calculating the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface, and the air convection heat dissipation of the square shell battery, and constructing a heat dissipation model of the square shell battery according to the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface, and the air convection heat dissipation; based on the heat generation model and the heat dissipation model, determining the heat conduction equation of the square shell battery, and performing a CLTC operating condition test on the square shell battery according to the heat conduction equation to record the temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part under the CLTC operating condition.
[0041] It should be noted that the embodiments of the present application can establish a heat generation model of the battery and use the Bernardi heat generation model to calculate the heat generated inside the battery, as shown in the following formula:
[0042]
[0043] Among them, Q gen is the battery heat, U is the battery terminal voltage; U oc is the battery OCV curve voltage. Under different SOC and temperature conditions of the battery, the heat generation will also be different. The U in the above will change with different internal resistances. The final heat generation equation is:
[0044]
[0045] Secondly, the embodiment of the present application needs to establish a battery heat dissipation model, which includes the heat dissipation Q of the positive and negative poles of the battery pole 、Battery surface heat dissipation Q surf And air convection heat dissipation Q amb Combining the three parts with the above heat generation equation, we can get the following heat conservation equation:
[0046] Q gen =Q pole +Q surf +Q amb
[0047] Among them, Q pole Q is the heat change of the positive and negative poles; surf Q is the heat change on the battery shell surface; amb is the heat of air convection.
[0048] Furthermore, the heat transfer model expression equation can be obtained in the embodiment of the present application:
[0049]
[0050] Among them, C batt is the internal heat capacity of the battery; C surf is the surface heat capacity of the battery; R batt is the internal thermal resistance of the battery; R amb is the battery surface thermal resistance; R pole is the thermal resistance of the positive and negative poles; Q batt is the heat generation power per unit volume.
[0051] In addition, the embodiment of the present application can be based on the equation of heat conduction rate:
[0052]
[0053] Among them, Q represents the amount of heat transferred within a certain period of time t; k is the thermal conductivity constant of the material; A is the cross-sectional area of the material for heat transfer; ΔT is the temperature difference between the two materials; and d is the thickness of the material.
[0054] The battery surface serves as the boundary condition for heat transfer between the battery and the outside air. The air heat convection equation can be expressed as:
[0055] Q amb =hA(T amb -T surf )
[0056] Among them, Q amb is the heat transfer quantity per unit time on area A, in W; h represents the surface convection heat transfer coefficient. For the convenience of calculation, the above heat conduction equation can be simplified as follows in the present embodiment:
[0057] ΔQ=KΔT
[0058] Among them, K is the centralized expression coefficient of all parameters.
[0059] Then, the energy conservation equation can be obtained in the embodiment of the present application as follows:
[0060] Q gen =K1(T inn -T pole )+K2(T inn -T surf )+K3(T pole -T surf )+K4(T pole -T amb )+K5(T surf -T amb )
[0061] Afterwards, the embodiments of the present application can perform dynamic working condition tests on the battery at different ambient temperatures (at 45°C, 35°C, 10°C, 5°C, 0°C, -5°C, -10°C, -15°C, -20°C), the test working condition uses the CLTC working condition, and records the battery remaining capacity SOC, T inn , T pole , T surf , T amb and current I.
[0062] Therefore, the embodiment of the present application divides the battery into three parts: internal temperature, pole temperature and shell temperature, and calculates the thermal conduction of the battery separately, so as to clearly express the process from heat generation to heat transfer of the battery.
[0063] In step S103, based on the temperature value and the current value, and in combination with the battery lumped parameter model, the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part are calculated respectively, and the temperature relationship between the interior of the shell, the positive and negative poles, and the shell part is determined according to the parameter vector and the pre-trained LSTM model, and the error correction value is calculated through the temperature relationship, so as to use the error correction value to calculate the temperature value inside the shell.
[0064] Furthermore, the embodiment of the present application also needs to construct a long short-term memory neural network model (Long Short-Term Memory, LSTM) to record the remaining battery capacity SOC, T inn , T pole , T surf , T amb and current I, etc. are input into the long short-term memory neural network model, coupled with the battery thermal model, the parameters K of each part are calculated, and the K matrix is solved by the least bisection method; then, the embodiment of the present application uses the long short-term memory neural network to obtain the relationship between the various temperature points, and in the actual temperature measurement, the error ΔK is calculated, and the temperature value is substituted into the formula to obtain the internal temperature of the battery.
[0065] Optionally, in one embodiment of the present application, based on the temperature value and the current value, and in combination with the battery lumped parameter model, the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part are calculated respectively, including: based on the heat generation model, the heat conduction equation, the temperature value and the current value, determining the matrix form of the heat generation model; calculating the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part according to the matrix form of the heat generation model and the preset least squares strategy.
[0066] It should be noted that after obtaining n T values and Q gen After the value is obtained, the embodiment of the present application can be rewritten into a matrix form:
[0067] Q gen =X*K
[0068] Among them, K represents the vector containing all unknown coefficients, and X represents the design matrix, which contains all temperature difference terms. Specifically, the mathematical expressions of K and X are as follows:
[0069]
[0070] Wherein, the superscript i represents the data of the i-th experiment. Thus, the embodiment of the present application can obtain a series of Q gen The value and the corresponding temperature difference can be used to estimate the coefficient K using the least squares method, so that the predicted Q gen The difference between the actual observed value and the actual observed value is the smallest; the embodiment of the present application can obtain the solution of the least squares method by solving the normal equation, as shown in the following formula:
[0071] K=(X T X) -1 X T Q gen
[0072] Among them, X T represents the transpose of matrix X, (X T X) -1 Represents X T The inverse matrix of X.
[0073] Therefore, the embodiment of the present application calculates the coefficients of each part by the least square method, which effectively ensures the acquisition of the subsequent temperature value inside the shell.
[0074] Optionally, in one embodiment of the present application, the temperature relationship between the inside of the shell, the positive and negative poles, and the shell part is determined according to the parameter vector and the pre-trained LSTM model, and the error correction value is calculated through the temperature relationship, so as to use the error correction value to calculate the temperature value inside the shell, including: based on the parameter vector, temperature value and current value, and in combination with the pre-trained LSTM model, to obtain the temperature relationship; obtain the pole temperature and ambient temperature of the square shell battery, and calculate the error correction value corresponding to the LSTM model according to the pole temperature and the ambient temperature; determine the temperature parameters inside the shell according to the temperature relationship, and calculate the temperature value inside the shell based on the pole temperature, the error correction value and the temperature parameters inside the shell.
[0075] In practical applications, it is difficult to place the temperature sensor inside the battery pack, and only the pole temperature T can be obtained. pole 、Ambient temperature T amb Therefore, the embodiments of the present application may utilize LSTM, such as Figure 5 As shown, calculate T inn , T pole , T surf and T amb The relationship between.
[0076] The internal temperature T under the test condition inn , pole temperature T pole , surface temperature T surf 、Ambient temperature T amb 、Battery heat generation Q gen And test current I and other data are input into the LSTM neural network model to obtain the following relationship:
[0077] K inn T pole =T inn
[0078] K surf T pole =T surf
[0079] K amb T pole =T amb
[0080] During the use of the battery, the embodiment of the present application can measure the pole temperature T Mpole and ambient temperature T Mamb , then calculate the computational error in the neural network:
[0081]
[0082] The corrected battery surface temperature is:
[0083] (K surf +ΔK)T Mpole =T surf
[0084] Through the above process, the temperature T pole , T surf , T amb Substitute the values into the energy conservation equation shown below:
[0085] Q gen =K1(T inn -T pole )+K2(T inn -T surf )+K3(T pole -T surf )+K4(T pole -T amb )
[0086] +K5(T surf -T amb )
[0087] This allows the final internal temperature of the battery to be determined.
[0088] Therefore, the embodiments of the present application utilize a lumped parameter model and model the heat generation and heat dissipation of the battery to establish an electrothermal coupling model of the battery, and dynamically correct the heat generation and heat dissipation model coefficients through different operating condition data, thereby effectively improving the model accuracy.
[0089] According to the method for calculating the internal temperature of a vehicle battery proposed in an embodiment of the present application, a battery equivalent circuit model of a square shell battery in the current vehicle is constructed, and based on the battery equivalent circuit model, the battery internal parameters of the square shell battery are obtained; a battery lumped parameter model of the square shell battery is constructed according to the internal battery parameters, and a dynamic operating condition test is performed on the square shell battery to obtain the temperature value and current value of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery; based on the temperature value and the current value, and in combination with the battery lumped parameter model, the parameter vectors corresponding to the inside of the shell, the positive and negative poles, and the shell part are calculated respectively, and the temperature relationship between the inside of the shell, the positive and negative poles, and the shell part is determined according to the parameter vector and a pre-trained LSTM model, and an error correction value is calculated through the temperature relationship, so as to calculate the temperature value of the inside of the shell using the error correction value. This application uses a lumped parameter model to model the heat generation and heat dissipation of the battery, establishes an electrothermal coupling model of the battery, and divides the battery temperature into three parts: internal temperature, pole temperature and shell temperature, and calculates the thermal conduction of the battery respectively. Through different operating condition data, the heat generation and heat dissipation model coefficients are dynamically corrected, so as to clearly express the process of heat generation to heat transfer of the battery and improve the calculation accuracy of the internal temperature of the battery.
[0090] Next, a device for calculating the internal temperature of a vehicle battery according to an embodiment of the present application will be described with reference to the accompanying drawings.
[0091] Figure 6 It is a block diagram of a device for calculating the internal temperature of a vehicle battery according to an embodiment of the present application.
[0092] like Figure 6 As shown, the calculation device 10 for the internal temperature of a vehicle battery includes: a modeling module 100 , a testing module 200 and a calculation module 300 .
[0093] Among them, the modeling module 100 is used to construct a battery equivalent circuit model of the square shell battery in the current vehicle, and obtain the battery internal parameters of the square shell battery based on the battery equivalent circuit model.
[0094] The test module 200 is used to construct a battery lumped parameter model of the square shell battery according to the internal parameters of the battery, and to perform a dynamic operating condition test on the square shell battery to obtain the temperature and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery.
[0095] The calculation module 300 is used to calculate the parameter vectors corresponding to the inside of the shell, the positive and negative poles, and the shell part respectively based on the temperature value and the current value and in combination with the battery lumped parameter model, and determine the temperature relationship between the inside of the shell, the positive and negative poles, and the shell part according to the parameter vector and the pre-trained LSTM model, and calculate the error correction value through the temperature relationship, so as to calculate the temperature value inside the shell using the error correction value.
[0096] Optionally, in one embodiment of the present application, the modeling module 100 includes: a first construction unit and a building unit.
[0097] Among them, the first construction unit is used to construct a battery equivalent circuit model of the square shell battery in the current vehicle based on a preset Thevenin model.
[0098] A unit is established for performing an HPPC condition test on a square shell battery based on a battery equivalent circuit model to obtain internal parameters of the battery and establish a mapping relationship between the internal parameters of the battery and the remaining power and temperature of the battery.
[0099] Optionally, in one embodiment of the present application, the test module 200 includes: a second construction unit, a first operation unit and a recording unit.
[0100] Among them, the second construction unit is used to calculate the internal heat of the square shell battery based on the preset Bernardi heat generation model, and construct the heat generation model of the square shell battery according to the internal heat of the battery and the mapping relationship.
[0101] The first computing unit is used to calculate the heat dissipation of the positive and negative poles of the square shell battery, the heat dissipation of the battery surface and the heat dissipation of air convection, and to build a heat dissipation model of the square shell battery according to the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface and the heat dissipation of air convection.
[0102] The recording unit is used to determine the heat conduction equation of the square shell battery based on the heat generation model and the heat dissipation model, and perform a CLTC working condition test on the square shell battery according to the heat conduction equation to record the temperature and current values of the inside of the shell, the positive and negative poles, and the shell part under the CLTC working condition.
[0103] Optionally, in one embodiment of the present application, the calculation module 300 includes: a first determination unit and a second calculation unit.
[0104] The first determination unit is used to determine the heat generation model in matrix form based on the heat generation model, the heat conduction equation, the temperature value and the current value.
[0105] The second operation unit is used to calculate the parameter vectors corresponding to the inside of the shell, the positive and negative poles and the shell part according to the matrix form heat generation model and the preset least squares method strategy.
[0106] Optionally, in one embodiment of the present application, the calculation module 300 further includes: a first acquisition unit, a second acquisition unit and a second determination unit.
[0107] The first acquisition unit is used to acquire the temperature relationship based on the parameter vector, the temperature value and the current value in combination with a pre-trained LSTM model.
[0108] The second acquisition unit is used to obtain the pole temperature and the ambient temperature of the square shell battery, and calculate the error correction value corresponding to the LSTM model according to the pole temperature and the ambient temperature.
[0109] The second determination unit is used to determine the temperature parameter inside the shell according to the temperature relationship, and calculate the temperature value inside the shell based on the pole temperature, the error correction value and the temperature parameter inside the shell.
[0110] It should be noted that the above explanation of the embodiment of the method for calculating the internal temperature of a vehicle battery is also applicable to the device for calculating the internal temperature of a vehicle battery in this embodiment, and will not be repeated here.
[0111] A device for calculating the internal temperature of a vehicle battery proposed in an embodiment of the present application includes a modeling module for constructing a battery equivalent circuit model of a square shell battery in the current vehicle, and obtaining the battery internal parameters of the square shell battery based on the battery equivalent circuit model; a testing module for constructing a battery lumped parameter model of the square shell battery according to the battery internal parameters, and performing a dynamic operating condition test on the square shell battery to obtain temperature values and current values of the inside of a shell, positive and negative poles, and a shell portion of the square shell battery; a calculation module for calculating parameter vectors corresponding to the inside of the shell, the positive and negative poles, and the shell portion, respectively, based on the temperature values and the current values, and in combination with the battery lumped parameter model, and determining the temperature relationship between the inside of the shell, the positive and negative poles, and the shell portion according to the parameter vectors and a pre-trained LSTM model, and calculating an error correction value through the temperature relationship, so as to calculate the temperature value of the inside of the shell using the error correction value. This application uses a lumped parameter model to model the heat generation and heat dissipation of the battery, establishes an electrothermal coupling model of the battery, and divides the battery temperature into three parts: internal temperature, pole temperature and shell temperature, and calculates the thermal conduction of the battery respectively. Through different operating condition data, the heat generation and heat dissipation model coefficients are dynamically corrected, so as to clearly express the process of heat generation to heat transfer of the battery and improve the calculation accuracy of the internal temperature of the battery.
[0112] Figure 7 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include:
[0113] A memory 701 , a processor 702 , and a computer program stored in the memory 701 and executable on the processor 702 .
[0114] When the processor 702 executes the program, the method for calculating the internal temperature of the vehicle battery provided in the above embodiment is implemented.
[0115] Furthermore, the vehicle also includes:
[0116] The communication interface 703 is used for communication between the memory 701 and the processor 702 .
[0117] The memory 701 is used to store computer programs that can be executed on the processor 702 .
[0118] The memory 701 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
[0119] If the memory 701, the processor 702 and the communication interface 703 are implemented independently, the communication interface 703, the memory 701 and the processor 702 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.
[0120] Optionally, in a specific implementation, if the memory 701, the processor 702 and the communication interface 703 are integrated on a chip, the memory 701, the processor 702 and the communication interface 703 can communicate with each other through an internal interface.
[0121] The processor 702 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.
[0122] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above method for calculating the internal temperature of a vehicle battery.
[0123] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, is used to implement the above-mentioned method for calculating the internal temperature of a vehicle battery.
[0124] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.
[0125] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.
[0126] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.
[0127] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.
[0128] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
[0129] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.
[0130] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.
[0131] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.
Claims
1. A method for calculating the internal temperature of a vehicle battery, characterized in that: The following steps are involved: Constructing a battery equivalent circuit model of the square shell battery in the current vehicle, and obtaining the battery internal parameters of the square shell battery based on the battery equivalent circuit model; A battery lumped parameter model of the square shell battery is constructed according to the internal parameters of the battery, and a dynamic operating condition test is performed on the square shell battery to obtain temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery; Based on the temperature value and the current value, and in combination with the battery lumped parameter model, the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part are calculated respectively, and the temperature relationship between the interior of the shell, the positive and negative poles, and the shell part is determined according to the parameter vector and the pre-trained LSTM model, and the error correction value is calculated through the temperature relationship, so as to use the error correction value to calculate the temperature value of the interior of the shell.
2. The method according to claim 1, characterized in that The step of constructing a battery equivalent circuit model of the square shell battery in the current vehicle and obtaining the battery internal parameters of the square shell battery based on the battery equivalent circuit model includes: Based on a preset Thevenin model, a battery equivalent circuit model of the square shell battery in the current vehicle is constructed; Based on the battery equivalent circuit model, the square shell battery is subjected to an HPPC operating condition test to obtain the internal parameters of the battery, and a mapping relationship between the internal parameters of the battery and the remaining power and temperature of the battery is established.
3. The method according to claim 2, characterized in that The battery lumped parameter model of the square shell battery is constructed according to the internal parameters of the battery, and the square shell battery is subjected to a dynamic working condition test to obtain the temperature value and current value of the shell interior, the positive and negative poles, and the shell part of the square shell battery, including: Based on a preset Bernardi heat generation model, the internal heat of the square shell battery is calculated, and the heat generation model of the square shell battery is constructed according to the internal heat of the battery and the mapping relationship; Calculating the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface and the heat dissipation of air convection of the square shell battery, and constructing a heat dissipation model of the square shell battery according to the heat dissipation of the positive and negative poles of the battery, the heat dissipation of the battery surface and the heat dissipation of air convection; Based on the heat generation model and the heat dissipation model, the heat conduction equation of the square shell battery is determined, and the square shell battery is subjected to a CLTC operating condition test according to the heat conduction equation to record the temperature and current values of the inside of the shell, the positive and negative poles, and the shell part under the CLTC operating condition.
4. The method according to claim 3, characterized in that The method of calculating the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part based on the temperature value and the current value and combining the battery lumped parameter model includes: Determine a matrix-form heat generation model based on the heat generation model, the heat conduction equation, the temperature value, and the current value; The parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell portion are calculated according to the matrix-form heat generation model and a preset least squares method strategy.
5. The method according to claim 4, characterized in that The determining the temperature relationship between the interior of the shell, the positive and negative poles, and the shell portion according to the parameter vector and the pre-trained LSTM model, and calculating the error correction value through the temperature relationship, so as to calculate the temperature value of the interior of the shell using the error correction value, includes: Based on the parameter vector, the temperature value and the current value, and in combination with a pre-trained LSTM model, the temperature relationship is obtained; Obtaining the pole temperature and the ambient temperature of the square shell battery, and calculating the error correction value corresponding to the LSTM model according to the pole temperature and the ambient temperature; The temperature parameter inside the shell is determined according to the temperature relationship, and the temperature value inside the shell is calculated based on the pole temperature, the error correction value and the temperature parameter inside the shell.
6. A device for calculating the internal temperature of a vehicle battery, characterized in that: include: A modeling module, used to construct a battery equivalent circuit model of the square shell battery in the current vehicle, and obtain the battery internal parameters of the square shell battery based on the battery equivalent circuit model; A test module, used to construct a battery lumped parameter model of the square shell battery according to the internal parameters of the battery, and perform a dynamic operating condition test on the square shell battery to obtain temperature values and current values of the inside of the shell, the positive and negative poles, and the shell part of the square shell battery; A calculation module is used to calculate the parameter vectors corresponding to the interior of the shell, the positive and negative poles, and the shell part respectively based on the temperature value and the current value and in combination with the battery lumped parameter model, and determine the temperature relationship between the interior of the shell, the positive and negative poles, and the shell part according to the parameter vector and a pre-trained LSTM model, and calculate an error correction value through the temperature relationship, so as to calculate the temperature value of the interior of the shell using the error correction value.
7. The device according to claim 6, characterized in that The modeling module includes: A first construction unit is used to construct a battery equivalent circuit model of the square shell battery in the current vehicle based on a preset Thevenin model; An establishing unit is used to perform an HPPC operating condition test on the square shell battery based on the battery equivalent circuit model to obtain the internal parameters of the battery and establish a mapping relationship between the internal parameters of the battery and the remaining power and temperature of the battery.
8. A vehicle, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating the internal temperature of a vehicle battery as described in any one of claims 1 to 5.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for calculating the internal temperature of a vehicle battery as described in any one of claims 1 to 5.
10. A computer program product, comprising a computer program, characterized in that The computer program is executed to implement the method for calculating the internal temperature of a vehicle battery as claimed in any one of claims 1 to 5.