Retired power battery pack consistency screening method based on temperature field detection

Abstract

The invention discloses a retired power battery consistency screening method based on a temperature field test technology. The retired power battery consistency screening method comprises the following steps: S1, collecting temperature field data; s2, acquiring the highest temperature change data in the area covered by the heat-conducting glue at the top of each single battery in the charge and discharge test; s3, obtaining a standardized temperature change data sequence of each single battery; and S4, processing the sequence in the step S3 by adopting a hierarchical clustering analysis method to obtain a clustering result, and obtaining single battery combinations with similar consistency. According to the non-contact dynamic detection retired battery consistency screening method, rapid and accurate battery sorting is achieved through thermal characteristic analysis, and the safety and reliability of cascade utilization battery packs are improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of power battery recycling and reuse, and particularly relates to a method for screening consistency of retired power battery pack based on infrared thermal imaging technology, which is particularly suitable for screening before cascade utilization of retired power battery of electric vehicles. BACKGROUND

[0002] With the rapid development of new energy vehicles, the demand for cascade utilization of a large number of retired power batteries is increasingly urgent. In the prior art, the consistency screening of retired batteries mainly relies on electrochemical parameter detection such as voltage and internal resistance, which has the following technical defects: the traditional detection method needs to disassemble and detect the battery pack, which is complex to operate and has safety hazards; the electrochemical parameters cannot directly reflect the thermal characteristic differences of the battery during operation; the static parameter detection cannot represent the consistency performance of the battery under dynamic working conditions; and the existing screening method has insufficient ability to identify the hidden defects of uneven heat generation in the battery.

[0003] Therefore, the present application provides a non-contact and dynamic detection method for screening the consistency of retired batteries, which realizes rapid and accurate battery sorting through thermal characteristic analysis and improves the safety and reliability of the cascade utilization battery pack. SUMMARY

[0004] The present application aims to overcome the deficiencies in the prior art and provide a method for screening the consistency of retired power batteries based on temperature field testing technology to solve the problems of long time consumption and low efficiency in the existing screening of the consistency of retired power batteries.

[0005] A method for screening the consistency of retired power batteries based on temperature field testing technology, comprising the following steps: Step S1: collecting temperature field data; Step S2: obtaining the highest temperature change data in the top heat-conducting adhesive covered area of each single battery during the charge and discharge test; Step S3: obtaining the standardized temperature change data sequence of each single battery; Step S4: processing the sequence of step S3 using hierarchical clustering analysis method to obtain the clustering result and the combination of single batteries with similar consistency.

[0006] Preferably, the specific process of step S1 of the present application is as follows: after removing the top shell of the retired power battery pack to be tested, a heat-conducting acrylic pressure-sensitive adhesive tape is pasted on the top end of each battery; the lens of the infrared thermal imager is directed downward, and the retired power battery pack is placed below the infrared thermal imager; the height of the thermal imager is adjusted according to the field of view of the infrared thermal imager; the infrared thermal imager collects temperature field data every 60 seconds, the emissivity is set to 0.90, and the captured data is stored by connecting a computer.

[0007] Preferably, the specific process of step S2 of the present application is as follows: a first charge-discharge test is performed on the retired power battery pack, the battery pack is connected to a charge-discharge tester, and the charge-discharge tester is connected to a computer to set the following charge-discharge parameters: constant current discharge (current size: single battery capacity × parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cutoff voltage × series battery number, constant current charging (current size: single battery capacity × parallel battery number ÷ 1h) to voltage ≥ single lithium ion battery charging cutoff voltage × series battery number, constant voltage charging (voltage: single lithium ion battery charging cutoff voltage × series battery number), to current < current size: single battery capacity × parallel battery number ÷ 1h × 0.02, constant current discharge (current size: single battery capacity × parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cutoff voltage × series battery number; the highest temperature change data in the top heat-conducting glue covered area of each single battery in the charge-discharge test is obtained.

[0008] Preferably, the specific process of step S3 of the present application is as follows: temperature correction is performed based on a standard battery pack thermal model, the mutual influence of battery heat production is removed, and the formula (1) is used to calculate the standardized treatment of the single battery independent temperature. For a battery pack with m columns and n rows of energy-saving batteries arranged: (1) In the formula, S is the standardized temperature, dimensionless; T is the actual test temperature, °C; ( x , y ) is the battery number, x =1,2,…, m and y =1,2,…, n , respectively, are the serial numbers of the batteries from the lower left corner to the upper right corner of the battery pack in the column and the row, for example, the lower left corner battery is numbered (1, 1), that is, x =1, y =1, the upper right corner battery is numbered (m, n), that is, x = m , y = n ; A, B, C, D, E, F, G, H, and I are respectively calculation coefficients, which are calculated from the overall temperature field parameters of the battery pack at the moment when the highest point is reached in the cycle process; after standardizing each temperature data, the standardized temperature change data sequence of each single battery is obtained.

[0009] Preferably, the specific process of step S4 of the present application is as follows: the hierarchical clustering analysis method is used to calculate the distance between each sequence, the two sequences with the smallest distance are combined into one cluster, and the calculation and combination are repeated until a cluster containing all sequences is generated. The cluster type is variable, the cluster method is average, the distance type is correlation, and the cluster center point is found according to the distance sum; the number of clusters is set to multiple numbers for different situations and compared and analyzed by calculation, when the number of single batteries in the battery pack is less than 100, the number of clusters is set to 2; when the number of single batteries in the battery pack is greater than or equal to 100 and less than 500, the number of clusters is set to 3; when the number of single batteries in the battery pack is greater than or equal to 500 and less than 100, the number of clusters is set to 4; when the number of single batteries in the battery pack is greater than or equal to 1000 and less than 2000, the number of clusters is set to 5; when the number of single batteries in the battery pack is greater than or equal to 2000 and less than 5000, the number of clusters is set to 6; when the number of single batteries in the battery pack is greater than or equal to 500, the number of clusters is set to 7; according to the obtained cluster result, a consistent similar single battery combination is obtained.

[0010] Compared with the prior art, the present application has the following beneficial effects: first, non-contact detection can avoid the risk caused by battery pack disassembly, and there is no need to recombine the batteries; second, the present method can perform consistency screening after one cycle test of multiple batteries, and the higher the consistency screening efficiency, the shorter the time. BRIEF DESCRIPTION OF DRAWINGS

[0011] The present application will be further described below in combination with the drawings: Figure 1 is a flow chart of the implementation method of the present application; Figure 2 is a schematic diagram of the position of the battery to be corrected; Figure 3 is the temperature change sequence of each battery in the battery pack after standardization processing; Figure 4 is a hierarchical clustering analysis result diagram; Figure 5 is an infrared thermal imaging diagram.

[0012] In the figure: 1, battery number (1, 1); 2, battery number (3, 2); 3, battery number (5, 4). DETAILED DESCRIPTION

[0013] The method of the present application will be described in detail below in combination with the drawings and specific embodiments.

[0014] Referring to the drawings Figures 1-4The application provides a technical scheme: a retired power battery pack consistency screening method based on temperature field detection, which comprises the following steps: battery top shell disassembly, battery top adhesive thermal adhesive tape, battery pack cycle test, temperature standardization treatment, hierarchical clustering method screening, and good consistency part forming a battery pack, and poor consistency part re-screening.

[0015] A retired power battery consistency screening method based on temperature field test technology, comprising the following steps: Step S1: collecting temperature field data; the specific process is as follows: after the top shell of the retired power battery pack to be tested is disassembled, a thermal acrylic pressure-sensitive adhesive tape is pasted on the top end of each battery; the lens of an infrared thermal imager is directed downward, and the retired power battery pack is placed below the infrared thermal imager, the height of the thermal imager is adjusted according to the field size of the infrared thermal imager; the infrared thermal imager collects temperature field data every 60 seconds, the emissivity is set to 0.90, and the captured data is connected to a computer for storage.

[0016] Step S2: obtaining the highest temperature change data in the top thermal adhesive covering area of each single battery in the charge-discharge test; the specific process is as follows: a charge-discharge test is performed on the retired power battery pack, the battery pack is connected to a charge-discharge tester, and the charge-discharge tester is connected to a computer to set the following charge-discharge parameters: constant current discharge (current size: single battery capacity x parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cut-off voltage x series battery number, constant current charging (current size: single battery capacity x parallel battery number ÷ 1h) to voltage ≥ single lithium ion battery charging cut-off voltage x series battery number, constant voltage charging (voltage: single lithium ion battery charging cut-off voltage x series battery number) to current < current size: single battery capacity x parallel battery number ÷ 1h x 0.02, constant current discharge (current size: single battery capacity x parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cut-off voltage x series battery number; the highest temperature change data in the top thermal adhesive covering area of each single battery in the charge-discharge test is obtained.

[0017] Step S3: obtaining the standardized temperature change data sequence of each single battery; the specific process is as follows: based on the standard battery pack thermal model, the mutual influence of battery heat production is removed, and the independent temperature of the single battery is calculated according to formula (1) for standardization treatment, for a battery pack arranged in m columns and n rows: (1) In the formula, S is the standardized temperature, dimensionless; T is the actual test temperature, °C; x , y ) is the battery number, x =1,2,…, m and y= 1, 2, …, n , respectively, are the serial numbers of the cells in the column and row from the lower left corner to the upper right corner of the battery pack, and the lower left corner cell is numbered (1, 1), i.e. x = 1, y = 1, the upper right corner cell is numbered (m, n), i.e. x = m , y = n ; A, B, C, D, E, F, G, H, I are calculation coefficients, which are calculated from the overall temperature field parameters of the battery pack at the time when the highest point is reached during the cycle; after standardizing each temperature data, the standardized temperature change data sequence of each single battery is obtained.

[0018] Step S4: The sequences of step S3 are processed by using hierarchical clustering analysis method to obtain clustering results and obtain consistent similar single battery combinations. The specific process is as follows: The hierarchical clustering analysis method is used to calculate the distance between each sequence, the two sequences with the smallest distance are merged into one cluster, and the calculation and merging are repeated until a cluster containing all sequences is generated. The cluster type is variable, the cluster method is average, the distance type is correlation, and the cluster center point is found according to the distance sum; the number of clusters is set to multiple numbers for different situations and calculation comparison analysis, the number of single batteries in the battery pack is <100, the number of clusters is set to 2; the number of single batteries in the battery pack is ≥100, <500, the number of clusters is set to 3; the number of single batteries in the battery pack is ≥500, <100, the number of clusters is set to 4; the number of single batteries in the battery pack is ≥1000, <2000, the number of clusters is set to 5; the number of single batteries in the battery pack is ≥2000, <5000, the number of clusters is set to 6; the number of single batteries in the battery pack is ≥500, the number of clusters is set to 7; according to the obtained clustering results, consistent similar single battery combinations are obtained.

[0019] Example 1 Twenty lithium ion batteries are selected, the positive electrode material of each is lithium iron phosphate material, the nominal capacity is 1100 mAh, and the numbers are (1, 1), (2, 1), …, (5, 1), (1, 2), (2, 2), …, (5, 2), (1, 3), (2, 3), …, (5, 3), (1, 4), (2, 4), …, (5, 4), (1, 5), (2, 5), …, (5, 5) respectively. The 20 lithium ion batteries are arranged as shown in the following table: Figure 2Arranged in parallel into groups, paste the heat-conducting adhesive tape on the top, and place the infrared thermal imager lens downward, and place the lithium ion battery pack 20 cm below the infrared thermal imager, so that the center point of the lithium ion battery pack and the center point of the infrared thermal imager lens are on a vertical straight line, set the infrared thermal imager to collect infrared temperature data every 60 s, and the emissivity is set to 0.90.

[0020] Connect the lithium ion battery pack with the charge-discharge tester, and set the charge-discharge parameters as follows: constant current discharge (1.00C, 22A) to voltage <2V, constant current charge (1.00C, 22A) to voltage ≥3.6V, constant voltage charge (3.6V) to current <0.44A, and constant current discharge (1.00C, 22A) to voltage <2V.

[0021] Obtain the temperature change data of each lithium ion battery during the charge-discharge cycle of the battery pack, and standardize the battery temperature. For the case in Example 1, the parameters in formula (1) are as follows: A=114.685, B=-41.746, C=-34.169, D=6.691, E=11.856, F=3.475, G=-0.388, H=-0.779, and I=-0.725. Standardize the battery temperature according to formula (1), and the result is shown in Figure 3

[0022] Perform hierarchical cluster analysis on the standardized temperature change sequence, with variable clustering type, average value clustering method, correlation distance type, and distance sum as the basis for finding the cluster center point, and set the cluster number to 2. The cluster analysis result is shown in Figure 4

[0023] In combination with the infrared thermal images of Figure 5 , the infrared thermal images of the battery pack at four random times after the test started are shown: 01:56:02, 03:36:02, 04:31:05, and 05:18:06. From the figure, it can be seen that the temperature field information can be reflected, and the number of batteries can not be limited, which is not limited by the number of traditional sensors for temperature measurement. Secondly, the temperature field temperature change between the batteries with high consistency has spatial regularity and symmetry, which also verifies the derivation of formula (1).

[0024] ​​While embodiments of the application have been shown and described, it is to be understood that the embodiments described are merely exemplary of the principles and application of the present application. Numerous modifications and adaptions can be effected without departing from the spirit and scope of the present application, which is not limited to the exact construction and arrangement described. It is intended, therefore, to cover all modifications and adaptions that fall within the scope of the claims and their equivalents.

Claims

1. A method for screening consistency of retired power batteries based on temperature field test technology, characterized in that The method comprises the following steps: Step S1: collecting temperature field data; Step S2: obtaining the highest temperature change data in the top heat-conducting glue covered area of each single battery in the charge and discharge test; Step S3: obtaining the standardized temperature change data sequence of each single battery; Step S4: processing the sequence of step S3 by using hierarchical clustering analysis method to obtain the clustering result and obtain the consistent similar single battery combination.

2. The method of claim 1, wherein the temperature field test technique is used to screen the consistency of the retired power battery. The specific process of step S1 is as follows: after the top shell of the retired power battery pack to be tested is removed, a heat-conducting acrylic pressure-sensitive adhesive tape is pasted on the top end of each battery; the lens of the infrared thermal imager is directed downward, and the retired power battery pack is placed below the infrared thermal imager; the height of the thermal imager is adjusted according to the field of view of the infrared thermal imager; the infrared thermal imager collects temperature field data every 60 seconds, the emissivity is set to 0.90, and the captured data is stored by connecting a computer. 3.The method of claim 2, wherein The specific process of step S2 is as follows: a charge and discharge test is performed on the retired power battery pack; the battery pack is connected to a charge and discharge tester, and the charge and discharge tester is connected to a computer to set the following charge and discharge parameters: constant current discharge (current size: single battery capacity x parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cutoff voltage x series battery number, constant current charging (current size: single battery capacity x parallel battery number ÷ 1h) to voltage ≥ single lithium ion battery charging cutoff voltage x series battery number, constant voltage charging (voltage: single lithium ion battery charging cutoff voltage x series battery number) to current < current size: single battery capacity x parallel battery number ÷ 1h x 0.02, constant current discharge (current size: single battery capacity x parallel battery number ÷ 1h) to voltage < single lithium ion battery discharge cutoff voltage x series battery number; the highest temperature change data in the top heat-conducting glue covered area of each single battery in the charge and discharge test is obtained.

4. The method for screening the consistency of retired power batteries based on temperature field testing technology according to claim 3, characterized in that... The specific process of step S3 is as follows: based on the standard battery pack thermal model, the mutual influence of battery heat production is removed, and the independent temperature of the single battery is standardized according to formula (1); for a battery pack arranged in m columns and n rows, the formula is as follows: (1) where S is the normalized temperature, dimensionless; T is the actual test temperature, °C; x , y ) is the battery number, x = 1, 2, …, m and y = 1, 2, …, n , respectively, are the sequence numbers of the cells in the column and row from the lower left corner to the upper right corner of the battery pack, such as the lower left corner cell number (1, 1), that is x = 1, y = 1, the upper right corner cell number (m, n), that is x = m , y = n ; A, B, C, D, E, F, G, H, I are respectively the calculation coefficients, which are calculated by the overall temperature field parameters of the battery pack at the time when the highest point is reached during the cycle process; after standardizing each temperature data, the normalized temperature change data sequence of each single battery is obtained.

5. The method of claim 4, wherein the temperature field test technique is based on a temperature field test. The specific process of step S4 is as follows: the hierarchical clustering analysis method is used to calculate the distance between each sequence, the two sequences with the smallest distance are combined into one cluster, and the calculation and combination are repeated until a cluster containing all sequences is generated. The cluster type is variable, the cluster method is average, the distance type is correlation, and the cluster center point is found according to the distance sum; the number of clusters is set to multiple numbers for different situations and compared and analyzed, the number of clusters is set to 2 when the number of single batteries in the battery pack is <100; the number of clusters is set to 3 when the number of single batteries in the battery pack is ≥100 and <500; the number of clusters is set to 4 when the number of single batteries in the battery pack is ≥500 and <1000; the number of clusters is set to 5 when the number of single batteries in the battery pack is ≥1000 and <2000; the number of clusters is set to 6 when the number of single batteries in the battery pack is ≥2000 and <5000; The number of single batteries in the battery pack is greater than or equal to 500, and the number of clusters is set to 7; and according to the obtained clustering result, a consistent similar single battery combination is obtained.

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