Temperature-OCV-SOC response surface construction method for battery pack

Abstract

The present invention relates to the technical field of electric vehicle power battery management, and specifically to a method for constructing a temperature-OCV-SOC response surface for a battery pack, including: collecting battery characteristic data of each single cell in a power battery pack, generating an OCV-SOC curve of each single cell at different ambient temperatures; performing parameter identification on the ohmic internal resistance of each single cell in the power battery pack based on the collected battery characteristic data; performing inconsistency analysis on each single cell in the power battery pack, and selecting the single cell with the worst consistency as a characteristic single cell; constructing an OCV-SOC curve cluster based on the OCV-SOC curve of the characteristic single cell at different ambient temperatures; performing two-dimensional temperature interpolation on the OCV-SOC curve cluster to generate a corresponding temperature-OCV-SOC three-dimensional response surface to achieve SOC estimation. The present invention can accurately construct a temperature-OCV-SOC three-dimensional response surface of a power battery pack, so as to complete SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle power battery management, and in particular to a method for constructing a temperature-OCV-SOC response surface for a battery pack. Background Art

[0002] As an important energy storage component of electric vehicles, the performance of power batteries is closely related to the normal operation and good working of the vehicle. Unlike fuel vehicles, the power batteries in electric vehicles need to undergo continuous charging and discharging during use. Different charging and discharging strategies have a certain impact on the performance and life of the battery.

[0003] The state of charge (SOC) of a power battery indicates the ratio of the remaining power in the power battery to its rated capacity, which can clearly and accurately characterize the current state of the power battery. In the prior art, the OCV (i.e., battery open circuit voltage)-SOC relationship of the battery is generally obtained through an open circuit voltage experiment, and then the SOC state of the battery is estimated through the OCV-SOC relationship.

[0004] The applicant has found that in actual application, it is often necessary to combine battery cells in series and parallel to form a power battery pack for use, so as to meet the dual requirements of high voltage and large capacity of new energy vehicles. However, the management and analysis of the power battery status in the prior art are mostly concentrated at the single-cell level, that is, obtaining the OCV-SOC relationship of the battery cell, and then combining the filtering algorithm to perform SOC estimation. However, the existing single-cell battery SOC estimation can only reflect the status of a single battery, without considering the mutual influence between batteries, and the influence of each branch or different connection methods on the battery pack, resulting in poor accuracy and comprehensiveness of the power battery pack SOC estimation. Therefore, how to design a method that can improve the accuracy and comprehensiveness of the power battery pack SOC estimation is a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the deficiencies of the above-mentioned prior art, the technical problem to be solved by the present invention is: how to provide a method for constructing a temperature-OCV-SOC response surface for a battery pack, so as to accurately construct a temperature-OCV-SOC three-dimensional response surface of a power battery pack, so as to facilitate SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack, thereby improving the accuracy and comprehensiveness of SOC estimation of the power battery pack.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions:

[0007] The method for constructing a temperature-OCV-SOC response surface for a battery pack includes the following steps:

[0008] S1: Perform an open circuit voltage test on the power battery pack at different ambient temperatures; then collect battery characteristic data of each single cell in the power battery pack at set sampling time intervals to generate OCV-SOC curves of each single cell at different ambient temperatures;

[0009] S2: Parameter identification of the ohmic internal resistance of each single cell in the power battery pack based on the collected battery characteristic data;

[0010] S3: Based on the parameter identification results of the ohmic internal resistance, the inconsistency analysis of each single battery in the power battery pack is performed in combination with the cosine similarity, and the single battery with the worst consistency is selected as the characteristic single battery;

[0011] S4: Based on the OCV-SOC curves of characteristic single cells at different ambient temperatures, construct an OCV-SOC curve cluster of the power battery pack at different ambient temperatures;

[0012] S5: Perform two-dimensional temperature interpolation on the OCV-SOC curve clusters at different ambient temperatures of the power battery pack to generate a corresponding temperature-OCV-SOC three-dimensional response surface, so as to achieve SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

[0013] Preferably, in step S1, the battery characteristic data of the single battery includes terminal voltage, charge and discharge current and surface temperature data.

[0014] Preferably, in step S1, for each single cell, the corresponding charging OCV, discharging OCV and corresponding SOC value are recorded respectively; then the charging OCV and the discharging OCV are averaged to obtain the corresponding OCV value; finally, based on multiple OCV values ​​and corresponding SOC values, the corresponding OCV-SOC curve is obtained by linear interpolation.

[0015] Preferably, in step S2, the parameter identification method is selected from Kalman filtering, H-infinity Kalman filtering, genetic algorithm, particle swarm algorithm, recursive least squares algorithm or least mean square algorithm.

[0016] Preferably, in step S3, the inconsistency analysis of the single battery is performed through the following steps:

[0017] S301: Calculating the average ohmic internal resistance of all single cells in the series circuit of the power battery pack;

[0018] S302: Calculating the cosine similarity of the corresponding single battery based on the average ohmic internal resistance and the internal resistance of the corresponding single battery;

[0019] S303: Quantitatively analyzing the inconsistency of the corresponding single battery cells based on cosine similarity: the greater the cosine similarity, the worse the consistency; the smaller the cosine similarity, the better the consistency.

[0020] Preferably, in step S301, the average ohmic internal resistance is calculated by the following formula:

[0021]

[0022] Where: R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

[0023] Preferably, in step S302, the cosine similarity of the single battery is calculated by the following steps:

[0024]

[0025] Where: C k,i Represents cosine similarity; R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

[0026] Preferably, in step S4, after obtaining the OCV-SOC curves of the characteristic single cells at different ambient temperatures, the OCV-SOC curves at different ambient temperatures are transformed into the same three-dimensional coordinate system to obtain OCV-SOC curve clusters of the power battery pack at different ambient temperatures.

[0027] Preferably, in step S5, the temperature-OCV-SOC three-dimensional response surface is represented by the following formula:

[0028] U OC (x,T)=a 0,n ·x 5 +a 1,n ·x 4 +a 2,n ·x 3 +a 3,n ·x 2 +a 4,n ·x+a 5,n ;

[0029] Among them, [a 0,n a 1,n a 2,n a 3,n a 4,n a 5,n ] T =A×[T 3 T 2 T 1] T ;

[0030] Where: U OC (x,T) represents the open circuit voltage, i.e., the OCV value, which is a function of the ambient temperature and the SOC value; x represents the SOC value of the single cell; T represents the ambient temperature; a 0,n , a 1,n , …, a 5,n represents the coefficient; Λ represents the 6×4 constant matrix; the superscript T represents the transpose of the matrix.

[0031] Preferably, in step S5, SOC estimation is completed by combining an extended Kalman filter algorithm with a temperature-OCV-SOC three-dimensional response surface of the power battery pack.

[0032] The temperature-OCV-SOC response surface construction method for a battery pack in the present invention has the following beneficial effects:

[0033] The present invention selects characteristic single cells for characterizing the state of the power battery pack by performing inconsistency analysis on the single cells of the power battery pack, and constructs an OCV-SOC curve cluster of the power battery pack based on the OCV-SOC curves of the characteristic single cells at different ambient temperatures, and then interpolates to obtain the temperature-OCV-SOC three-dimensional response surface of the power battery pack, so that the SOC of the power battery pack can be accurately estimated based on the temperature-OCV-SOC three-dimensional response surface. That is, the present invention can accurately and effectively construct the temperature-OCV-SOC three-dimensional response surface of the power battery pack, so as to complete the SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack, thereby improving the accuracy and comprehensiveness of the SOC estimation of the power battery pack.

[0034] At the same time, the temperature-OCV-SOC three-dimensional response surface constructed by the present invention is not only applicable to the OCV-SOC relationship of the power battery pack, but also to the OCV-SOC relationship of each single cell in the power battery pack, so that the time for matching the OCV-SOC of each single cell can be saved during the SOC estimation process, thereby improving the efficiency of the SOC estimation of the power battery pack. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to make the purpose, technical solution and advantages of the invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings, in which:

[0036] Figure 1 A logical block diagram of the method for constructing a temperature-OCV-SOC response surface for a battery pack;

[0037] Figure 2 It is a series-parallel connection structure of power battery packs;

[0038] Figure 3It is the inconsistency analysis result between the single cells in each branch of the power battery pack;

[0039] Figure 4 It is the temperature-OCV-SOC three-dimensional response surface of the power battery pack;

[0040] Figure 5 The SOC estimation results are based on the constructed temperature-OCV-SOC three-dimensional response surface. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but only represents selected embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the scope of protection of the present invention.

[0042] It should be noted that similar numbers and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In the description of the present invention, it should be noted that the orientation or position relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inside", "outside", etc. is based on the orientation or position relationship shown in the drawings, or the orientation or position relationship in which the invention product is usually placed when used, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance. In addition, the terms "horizontal", "vertical", etc. do not mean that the components are absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0043] The following is a further detailed description through specific implementation methods:

[0044] Example:

[0045] This embodiment discloses a method for constructing a temperature-OCV-SOC response surface for a battery pack.

[0046] like Figure 1 As shown, the temperature-OCV-SOC response surface construction method for a battery pack includes the following steps:

[0047] S1: Perform an open circuit voltage test on the power battery pack at different ambient temperatures; then collect battery characteristic data of each single cell in the power battery pack at set sampling time intervals to generate OCV-SOC curves of each single cell at different ambient temperatures;

[0048] In this embodiment, the battery characteristic data of the single battery includes terminal voltage, charge and discharge current, and surface temperature data.

[0049] The sampling time is set to Δt, and the ambient temperatures are T1, T2, ..., Tn ℃.

[0050] For a single cell, the corresponding charging OCV, discharging OCV and SOC values ​​are recorded respectively; then the corresponding OCV value is obtained by taking the average value of the charging OCV and the discharging OCV; finally, based on multiple OCV values ​​and corresponding SOC values, the corresponding OCV-SOC curve is obtained by linear interpolation.

[0051] S2: Parameter identification of the ohmic internal resistance of each single cell in the power battery pack based on the collected battery characteristic data;

[0052] In this embodiment, the parameter identification method is selected from Kalman filtering, H-infinity Kalman filtering, genetic algorithm, particle swarm algorithm, recursive least squares algorithm or least mean square root algorithm.

[0053] S3: Based on the parameter identification results of the ohmic internal resistance, the inconsistency analysis of each single battery in the power battery pack is performed in combination with the cosine similarity, and the single battery with the worst consistency is selected as the characteristic single battery;

[0054] S4: Based on the OCV-SOC curves of characteristic single cells at different ambient temperatures, construct an OCV-SOC curve cluster of the power battery pack at different ambient temperatures;

[0055] S5: Perform two-dimensional temperature interpolation on the OCV-SOC curve clusters at different ambient temperatures of the power battery pack to generate a corresponding temperature-OCV-SOC three-dimensional response surface, so as to achieve SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

[0056] In this embodiment, SOC estimation is completed by combining the extended Kalman filter algorithm with the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

[0057] The specific steps of the extended Kalman algorithm are as follows:

[0058] Build a battery pack model and discretize it:

[0059]

[0060] Where x = [U D S] T , S is soc); u=i L ; y=U t ;

[0061]

[0062] B k =[(1-e -Δt / τ )R D ; ηi Δt / C max ];

[0063]

[0064] D k =U OC,k -U D,k -R i u k -C k x k ;

[0065] Specific steps for SOC estimation using the extended Kalman filter algorithm:

[0066] 1. Initialization

[0067] Set the initial values ​​of the state observer: x0, P0, Q, R;

[0068] 2. Time update

[0069] System status estimation:

[0070] State estimation error covariance matrix update:

[0071] 3. Measurement Update

[0072] Innovation matrix:

[0073] Kalman gain matrix:

[0074] System status correction:

[0075] State estimation error covariance matrix correction:

[0076] 4. Set the time (k) + The state and covariance matrix of is taken as the final output as the SOC state estimation at the (k+1) moment;

[0077] Among them, U OC,k The relationship between the open circuit voltage and the SOC is represented by replacing the temperature-OCV-SOC three-dimensional response surface in the present invention with it.

[0078] The present invention selects characteristic single cells for characterizing the state of the power battery pack by performing inconsistency analysis on the single cells of the power battery pack, and constructs an OCV-SOC curve cluster of the power battery pack based on the OCV-SOC curves of the characteristic single cells at different ambient temperatures, and then interpolates to obtain the temperature-OCV-SOC three-dimensional response surface of the power battery pack, so that the SOC of the power battery pack can be accurately estimated based on the temperature-OCV-SOC three-dimensional response surface. That is, the present invention can accurately and effectively construct the temperature-OCV-SOC three-dimensional response surface of the power battery pack, so as to complete the SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack, thereby improving the accuracy and comprehensiveness of the SOC estimation of the power battery pack.

[0079] At the same time, the temperature-OCV-SOC three-dimensional response surface constructed by the present invention is not only applicable to the OCV-SOC relationship of the power battery pack, but also to the OCV-SOC relationship of each single cell in the power battery pack, so that the time for matching the OCV-SOC of each single cell can be saved during the SOC estimation process, thereby improving the efficiency of the SOC estimation of the power battery pack.

[0080] During the specific implementation process, the inconsistency analysis of the single battery is carried out through the following steps:

[0081] S301: Calculating the average ohmic internal resistance of all single cells in the series circuit of the power battery pack;

[0082] The average ohmic internal resistance is calculated using the following formula:

[0083]

[0084] Where: R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

[0085] S302: Calculating the cosine similarity of the corresponding single battery based on the average ohmic internal resistance and the internal resistance of the corresponding single battery;

[0086] The cosine similarity of the single battery is calculated by the following steps:

[0087]

[0088] Where: C k,i Represents cosine similarity; R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

[0089] S303: Quantitatively analyzing the inconsistency of the corresponding single battery cells based on cosine similarity: the greater the cosine similarity, the worse the consistency; the smaller the cosine similarity, the better the consistency.

[0090] The present invention calculates cosine similarity based on the average ohmic internal resistance and the internal resistance of the single cell to analyze the inconsistency of the corresponding single cell, so that the characteristic single cell used to characterize the state of the power battery pack can be selected more accurately, and then the OCV-SOC curve cluster of the power battery pack can be accurately constructed based on the characteristic battery OCV-SOC curve, thereby further improving the accuracy and comprehensiveness of the power battery pack SOC estimation.

[0091] In the specific implementation process, after obtaining the OCV-SOC curves of the characteristic single cells at different ambient temperatures, the OCV-SOC curves at different ambient temperatures are transformed into the same three-dimensional coordinate system to obtain the OCV-SOC curve clusters of the power battery pack at different ambient temperatures.

[0092] The temperature-OCV-SOC three-dimensional response surface is expressed by the following formula:

[0093] U OC (x,T)=a 0,n ·x 5 +a 1,n ·x 4 +a 2,n ·x 3 +a 3,n ·x 2 +a 4,n ·x+a 5,n ;

[0094] Among them, [a 0,n a 1,n a 2,n a 3,n a 4,n a 5,n ] T =Λ×[T 3 T 2 T 1] T ;

[0095] Where: U OC (x,T) represents the open circuit voltage, i.e., the OCV value, which is a function of the ambient temperature and the SOC value; x represents the SOC value of the single cell; T represents the ambient temperature; a 0,n , a 1,n , …, a 5,n represents the coefficient; Λ represents the 6×4 constant matrix; the superscript T represents the transpose of the matrix.

[0096] The present invention can effectively generate a temperature-OCV-SOC three-dimensional response surface of a power battery pack by means of two-dimensional temperature interpolation, and can then accurately estimate the SOC of the power battery pack based on a more accurate temperature-OCV-SOC three-dimensional response surface, thereby further improving the accuracy and comprehensiveness of the power battery pack SOC estimation.

[0097] In order to better illustrate the advantages of the technical solution of the present invention, the following experiments are disclosed in this embodiment.

[0098] In this experiment, the series-parallel connection method of the power battery pack is as follows Figure 2 shown.

[0099] For a single cell, the corresponding charging OCV, discharging OCV and SOC values ​​are recorded respectively; then the corresponding OCV value is obtained by taking the average value of the charging OCV and the discharging OCV; finally, based on multiple OCV values ​​and corresponding SOC values, the corresponding OCV-SOC curve is obtained by linear interpolation.

[0100] The results of the inconsistency analysis of each single battery using cosine similarity are as follows Figure 3 shown.

[0101] Figure 3 (a) is the inconsistency analysis result of the single cell of branch 1 under different ambient temperatures. Figure 3 (b) is the inconsistency analysis result of the single battery of branch 2 under different ambient temperatures. Figure 3 (c) is the inconsistency analysis result of the single cells of branch 3 at different ambient temperatures. It can be seen that the single cells with poor consistency at different ambient temperatures in branch 1 are No. 2, No. 8, No. 2 and No. 3, No. 24, No. 21, No. 13 and No. 19, and No. 36, No. 27, No. 35 and No. 36 in branch 3.

[0102] Construct the temperature-OCV-SOC three-dimensional response surface of the power battery pack as follows Figure 4 shown.

[0103] In order to better illustrate the accuracy of the temperature-OCV-SOC three-dimensional response surface constructed by the present invention, this experiment discloses the following Figure 5 The results of SOC estimation of the power battery pack using the extended Kalman filter algorithm based on the constructed temperature-OCV-SOC three-dimensional response surface are shown. Figure 5 (a) is the comparison result of the predicted value and the actual value of the power battery pack SOC estimation. Figure 5(b) is the error analysis of the SOC estimation of the power battery pack. When the SOC is between 100% and 50%, the estimation error is always maintained at 0.0025±0.0005; when the SOC is lower than 20%, the maximum error is estimated to be 0.0047. The results show that the temperature-OCV-SOC three-dimensional response surface constructed by the present invention can better meet the use requirements of series-parallel battery packs.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit the technical solution. Those skilled in the art should understand that those modifications or equivalent substitutions of the technical solution of the present invention that do not depart from the purpose and scope of the technical solution should be included in the scope of the claims of the present invention.

Claims

1. A method for constructing a temperature-OCV-SOC response surface for a battery pack, characterized in that: The following steps are involved: S1: Perform an open circuit voltage test on the power battery pack at different ambient temperatures; then collect battery characteristic data of each single cell in the power battery pack at set sampling time intervals to generate OCV-SOC curves of each single cell at different ambient temperatures; S2: Parameter identification of the ohmic internal resistance of each single cell in the power battery pack based on the collected battery characteristic data; S3: Based on the parameter identification results of the ohmic internal resistance, the inconsistency analysis of each single battery in the power battery pack is performed in combination with the cosine similarity, and the single battery with the worst consistency is selected as the characteristic single battery; S4: Based on the OCV-SOC curves of characteristic single cells at different ambient temperatures, construct OCV-SOC curve clusters of power battery packs at different ambient temperatures; S5: Perform two-dimensional temperature interpolation on the OCV-SOC curve clusters at different ambient temperatures of the power battery pack to generate a corresponding temperature-OCV-SOC three-dimensional response surface, so as to achieve SOC estimation based on the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

2. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S1 , the battery characteristic data of the single battery includes terminal voltage, charge and discharge current and surface temperature data.

3. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S1, for a single cell, the corresponding charging OCV and discharging OCV and the corresponding SOC value are recorded respectively; then the charging OCV and the discharging OCV are averaged to obtain the corresponding OCV value; finally, based on multiple OCV values ​​and corresponding SOC values, the corresponding OCV-SOC curve is obtained by linear interpolation.

4. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S2, the parameter identification method is selected from Kalman filtering, H-infinity Kalman filtering, genetic algorithm, particle swarm algorithm, recursive least squares algorithm or least mean square root algorithm.

5. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S3, the inconsistency analysis of the single battery is performed through the following steps: S301: Calculating the average ohmic internal resistance of all single cells in the series circuit of the power battery pack; S302: Calculating the cosine similarity of the corresponding single battery based on the average ohmic internal resistance and the internal resistance of the corresponding single battery; S303: Quantitatively analyzing the inconsistency of the corresponding single battery cells based on cosine similarity: the greater the cosine similarity, the worse the consistency; the smaller the cosine similarity, the better the consistency.

6. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 5, characterized in that: In step S301, the average ohmic internal resistance is calculated by the following formula: Where: R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

7. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 5, characterized in that: In step S302, the cosine similarity of the single battery is calculated by the following steps: Where: C k,i represents cosine similarity; R avg,i represents the average ohmic internal resistance; K represents the number of single cells in the series circuit of the power battery pack; R k,i It represents the ohmic internal resistance of the kth single cell in the i-th branch of the power battery pack.

8. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S4, after obtaining the OCV-SOC curves of the characteristic single cells at different ambient temperatures, the OCV-SOC curves at different ambient temperatures are transformed into the same three-dimensional coordinate system to obtain OCV-SOC curve clusters of the power battery pack at different ambient temperatures.

9. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S5, the temperature-OCV-SOC three-dimensional response surface is expressed by the following formula: U oC (x,T)=a 0,n ·x 5 +a 1,n ·x 4 +a 2,n ·x 3 +a 3,n ·x 2 +a 4,n ·x+a 5,n ; Among them, [a 0,n a 1,n a 2,n a 3,n a 4,n a 5,n T = Λ × [T 3 T 2 T 1] T ;​ Where: U OC (x,T) represents the open circuit voltage, i.e., the OCV value, which is a function of the ambient temperature and the SOC value; x represents the SOC value of the single cell; T represents the ambient temperature; a 0,n , a 1,n , …, a 5,n represents coefficient; Λ represents a 6×4 constant matrix; the superscript T represents the transpose of the matrix.

10. The method for constructing a temperature-OCV-SOC response surface for a battery pack according to claim 1, characterized in that: In step S5, SOC estimation is completed by combining the extended Kalman filter algorithm with the temperature-OCV-SOC three-dimensional response surface of the power battery pack.

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