Power battery cell level health status assessment method, system, equipment and medium

Abstract

The present application discloses a method, system, device and medium for evaluating the health status of a power battery at the single-cell level. The method includes: periodically collecting the terminal voltage sequence, current sequence, and vehicle speed sequence of all single cells to identify the period when the vehicle is in an acceleration condition; calculating the equivalent impedance characteristic parameters of all single cells under acceleration conditions; respectively estimating the single-cell-level ohmic internal resistance through an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics; integrating the staged estimation results of the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics to achieve online evaluation of the health status of the battery. The advantage of the present application is that it evaluates the health status of the battery single-cell level online, providing data support for ensuring safe, reliable and stable operation of the vehicle and efficient operation and maintenance of the battery system.

Description

Technical Field

[0001] The present application relates to the technical field of power batteries, and in particular to a method, system, device and medium for evaluating the health status of a power battery cell. Background Art

[0002] Lithium batteries have the advantages of long cycle life, high power density, and low self-discharge rate. They are widely used in the field of distributed energy storage and have become an important source of energy for new energy electric vehicles. However, with the changes in the environment in which lithium batteries are located and the continuous chemical reactions within themselves, the battery performance is reduced, the capacity is irreversibly degraded, and the inconsistency between cells is aggravated. When individual cells in a battery pack have exceeded their service life limit, continuing to serve may cause serious safety accidents. Therefore, it is of great theoretical research significance and engineering application value to accurately evaluate the battery health status of in-service power batteries of new energy electric vehicles to ensure the safe, reliable and stable operation of the vehicle and the efficient operation and maintenance of the battery system. Summary of the invention

[0003] The present application provides a method, system, device and medium for evaluating the health status of a power battery cell level, which has the advantage of online evaluation of the health status of the battery cell level, providing data support for ensuring safe, reliable and stable operation of the vehicle and efficient operation and maintenance of the battery system.

[0004] In a first aspect, the present application provides a method for evaluating the health status of a power battery cell, comprising the following steps:

[0005] Periodically collect the terminal voltage sequence of all monomers {U i,k-1 ,U i,k ,U i,k+1}、Current sequence {I i,k -1,I i,k ,I i,k+1}, and the vehicle speed sequence {v k-1 ,v k ,v k+1}, where i represents the monomer number and the sampling time k≥1;

[0006] Real-time working condition identification, identifying the period when the vehicle is in acceleration condition;

[0007] Estimation of the equivalent impedance characteristic parameters of the monomer level, calculation of the equivalent impedance characteristic parameters R of all monomers under acceleration conditions i,k ;

[0008] The ohmic internal resistance of the monomer level is estimated respectively by an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics;

[0009] The online evaluation of battery health status is achieved by integrating the phased estimation results of the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics.

[0010] Based on the above scheme, the time period of identifying the vehicle in acceleration condition specifically includes: if |v k -v k-1 |v k+1 -v k |If the difference in value is less than a preset value and both are less than the design threshold, the vehicle is considered to be in a stable operating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and satisfy v k+1 >v k >v k-1 , the vehicle is considered to be in an accelerating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and meet The vehicle is considered to be in a deceleration condition.

[0011] Based on the above scheme, the equivalent impedance characteristic parameter R i,k satisfy:

[0012]

[0013] In the formula, R i,0 is the initial value of the equivalent impedance characteristic parameter of the i-th monomer, R EOL is the impedance value at the end of battery life.

[0014] On the basis of the above scheme, the ohmic internal resistance estimation method based on the equivalent impedance characteristic parameters includes:

[0015] According to the equivalent impedance characteristic parameter table R i = {R i,0 ,R i,1 ,…,R i,k ,…} to draw the point cloud map, based on R i The sliding average estimation strategy estimates the single-cell ohmic internal resistance. The specific steps are as follows:

[0016] Step 11: Design a sliding time window STW r , used to select R i Medium STW r The data set of interval is denoted as

[0017] Step 12: Remove outliers using the box plot method The outliers in

[0018] Step 13: Calculation The average value of is used to indirectly estimate the ohmic internal resistance of the single cell at the current stage p, that is, The average value r i,p as the ohmic internal resistance of the i-th monomer in the p-stage;

[0019] Step 14: Move STW along the time axis regularly r , and move forward p one step, that is, p=p+1, and repeat Step 11-Step 13 to realize the online estimation of the monomer-level ohmic internal resistance.

[0020] On the basis of the above scheme, the ohmic internal resistance estimation method based on charging characteristics includes:

[0021] Step 21: Identify charging conditions and fit U i (k) and v(k) change curve, if v(k) is 0 for a period of time, and U i (k) If the value shows an increasing trend, it is considered that the vehicle is in charging condition during this period;

[0022] Step 22: Capture the steep rise in single cell voltage at the initial stage of charging and design a sliding time window (STW) c , follow STW c All charging initial stages in the interval U i (k) Mark the starting and ending points of each part of the curve where the curve rises sharply, and calculate the average pressure difference between all the starting and ending points in satisfy

[0023]

[0024] Where M represents STW c The number of charges within the interval, Indicates the initial stage of the jth charging U i (k) The pressure difference between the starting point and the end point of the steep rise portion of the curve;

[0025] Step 23: Normalization. Since the monomers are connected in series, the charging current of each monomer is the same, so the normalized To indirectly characterize the relative size of the monomer ohmic internal resistance;

[0026] Step 24: Move STW along the time axis regularly c, and move forward p one step, that is, p=p+1, and repeat Step 21-Step 23 to realize the online estimation of the monomer-level ohmic internal resistance.

[0027] On the basis of the above scheme, the single-cell ohmic internal resistance obtained by the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics is normalized to obtain the single-cell health status, which step includes:

[0028] Use the staged normalized ohmic internal resistance to perform online assessment of the health status of the single-cell battery:

[0029]

[0030] In the formula, SOH i,p represents the aging degree of monomer i in stage p, with a value range of [0%, 100%], Norm{·} represents the normalization function, and w1 and w2 are design weights;

[0031] Draw the r of each stage separately i,p , The bar chart marks the cells with relatively large internal resistance, providing reference and guidance for the remote operation and maintenance of in-service automotive power batteries.

[0032] In the second aspect, the present application provides a power battery single-cell health status assessment system for implementing the power battery single-cell health status assessment method as described above, including an edge main control unit and a power battery Internet of Things platform, the power battery Internet of Things platform including a cloud database, the edge main control unit is used to monitor the battery status of the vehicle, collect the terminal voltage sequence, current sequence, and vehicle speed sequence of all single cells, complete real-time operating condition identification and single-cell equivalent impedance characteristic parameter estimation, and upload the single-cell equivalent impedance characteristic parameters to the cloud database, the power battery Internet of Things platform is used to estimate the single-cell ohmic internal resistance respectively through an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics, and normalize the obtained single-cell ohmic internal resistance to obtain the single-cell health status.

[0033] In a third aspect, the present application provides an electronic device, characterized in that it includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is called and executed by the processor, the power battery cell-level health status assessment method as described above is implemented.

[0034] In a fourth aspect, the present application provides a computer-readable medium, characterized in that a computer program is stored in the computer-readable medium, and when the computer program is called and executed by a processor, the power battery cell-level health status assessment method as described above is implemented.

[0035] In summary, the beneficial effects of the present application are as follows: the present application can evaluate the health status of battery cells online, and provide data support to ensure safe, reliable and stable operation of the vehicle and efficient operation and maintenance of the battery system. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a schematic diagram of a power battery cell-level health status assessment system in a specific implementation manner of the present application. DETAILED DESCRIPTION

[0037] The specific implementation of the present application is described in detail below with reference to the accompanying drawings.

[0038] In one specific embodiment of the present application, a power battery cell level health status assessment system is provided. Figure 1 , including an edge main control unit and a power battery Internet of Things platform. The power battery Internet of Things platform includes a cloud database. The edge main control unit is used to monitor the state of the vehicle battery, collect the terminal voltage sequence, current sequence, and vehicle speed sequence of all cells, complete real-time working condition identification and cell-level equivalent impedance characteristic parameter estimation, and upload the cell-level equivalent impedance characteristic parameters to the cloud database. The power battery Internet of Things platform is used to estimate the cell-level ohmic internal resistance through an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics, and normalize the obtained cell-level ohmic internal resistance to obtain the cell-level health status.

[0039] In a specific embodiment of the present application, a method for evaluating the health status of a power battery cell is provided, which is described by taking its application in the above-mentioned power battery cell health status evaluation system as an example. As the number of charge and discharge cycles increases, the ohmic internal resistance of the cell will slowly increase, and the nominal capacity of the cell will gradually decay. Therefore, the health status of the cell can be indirectly quantified by the ohmic internal resistance of the cell. Figure 1 As shown, a method for evaluating the health status of a power battery cell proposed in this embodiment has the following specific steps:

[0040] (1) Edge side (i.e. edge master control unit side):

[0041] Step 01: Data collection. Periodically collect the terminal voltage sequence of all monomers {U i,k-1 ,U i,k ,U i,k+1}、Current sequence {I i,k-1 ,I i,k ,I i,k+1}, and the vehicle speed sequence {v k-1 ,v k ,v k+1}, where i represents the monomer number and the sampling time k≥1.

[0042] Step 02: Real-time working condition identification. k -v k-1 |v k+1 -v k | are close in value and both are smaller than the design threshold. Specifically, if |v k -v k-1 |v k+1 -v k | is less than a preset value and is less than the design threshold, the vehicle is considered to be in a stable operating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and satisfy v k+1 >v k >v k-1 , the vehicle is considered to be in an accelerating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and satisfy v k+1 <v k <v k-1 , the vehicle is considered to be in a deceleration condition.

[0043] Ste:03: Estimation of equivalent impedance characteristic parameters at the monomer level. Calculate the equivalent impedance characteristic parameters R of all monomers under acceleration conditions i,k , and upload it to the cloud database; R i,k satisfy

[0044]

[0045] In the formula, R i,0 is the initial value of the equivalent impedance characteristic parameter of the i-th monomer, R EOL It is the impedance value at the end of battery life. When the consistency of the monomers is high, the equivalent impedance characteristic parameter values ​​of each monomer are relatively close.

[0046] Step 4 repeats Step 1-Step 3 to achieve online estimation of the equivalent impedance characteristic parameters at the monomer level.

[0047] (2) Platform side (i.e., power battery IoT platform side):

[0048] Method 1: Estimation of ohmic internal resistance based on equivalent impedance characteristic parameters

[0049] According to the equivalent impedance characteristic parameter table R in the database i = {R i,0 ,R i,1 ,…,R i,k,…} to draw the point cloud map. As time goes by, the information on the point cloud map will become richer and richer, which can intuitively reflect the aging trend of each single battery and the relative changes between the monomers. In order to further quantify the aging degree of each single battery, a method based on R is designed. i The specific steps of the sliding average estimation strategy are as follows:

[0050] Step 11: Sliding time window design. As time goes by, R i,k The database will become larger and larger, making the traversal calculation method more and more inefficient. Considering the gradual aging of batteries, a sliding time window STW is designed r (such as consecutive days) to select R i Medium STW r The data set of interval is denoted as

[0051] Step 12: Remove outliers. Use the box plot method to remove outliers. The outliers in

[0052] Step 13: Estimation of the ohmic internal resistance at the cell level. Calculation The average value of is used to indirectly estimate the ohmic internal resistance of the single cell at the current stage p, that is, The average value r i,p As the ohmic internal resistance of the i-th monomer in the p stage, and r i,p Stored in the database.

[0053] Step 14: Move STW along the time axis regularly r , and move forward p one step, that is, p=p+1, and repeat Step 11-Step 13 to realize the online estimation of the monomer-level ohmic internal resistance.

[0054] Method 2: Estimation of Ohmic Internal Resistance Based on Charging Characteristics

[0055] Step 21: Data-driven charging condition identification. Based on the cloud database, fit U i (k) and v(k) change curve. If v(k) is 0 for a period of time, and U i (k) shows an increasing trend, it is considered that the vehicle is in charging condition during this period.

[0056] Step 22: Capture the steep rise in single cell voltage at the initial stage of charging. Design a sliding time window STW c , focus on STW c All charging initial stages in the interval U i(k) Mark the starting and ending points of each part of the curve where the curve rises sharply, and calculate the average pressure difference between all the starting and ending points and will Stored in the database. satisfy

[0057]

[0058] Where M represents STW c The number of charges within the interval, Indicates the initial stage of the jth charging U i (k) The pressure difference between the starting point and the end point of the steep rising part of the curve.

[0059] Step 23 Normalization. Considering the differences in charging pile specifications and charging strategies, the vehicle charging current is also different. However, since the cells are connected in series, the charging current of each cell is the same, so the normalized To indirectly characterize the relative size of the monomer ohmic internal resistance.

[0060] Step 24: Move STW along the time axis regularly c , and move forward p one step, that is, p=p+1, and repeat Step 21-Step 23 to realize the online indirect estimation of the monomer-level ohmic internal resistance.

[0061] Finally, the estimation results of methods 1 and 2 are comprehensively considered, and the phased estimation results of the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics are integrated to realize the online evaluation of the battery health status. The phased normalized ohmic internal resistance is used to perform online evaluation of the single-cell level battery health status:

[0062]

[0063] In the formula, SOH i,p represents the aging degree of monomer i in stage p, and its value range is [0%, 100%]. Norm{·} represents the normalization function, and w1 and w2 are design weights.

[0064] In addition, the r of each stage is plotted separately. i,p , The bar chart marks the cells with relatively large internal resistance, providing reference and guidance for the remote operation and maintenance of in-service automotive power batteries.

[0065] Another specific embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is called and executed by the processor, the power battery cell-level health status assessment method as described above is implemented.

[0066] Another specific embodiment of the present application provides a computer-readable medium, in which a computer program is stored. When the computer program is called and executed by a processor, the power battery cell-level health status assessment method as described above is implemented.

[0067] The above is only a preferred implementation of the present application. It should be pointed out that a person skilled in the art can make several modifications and improvements without departing from the inventive concept of the present application, and these all fall within the scope of protection of the present application.

Claims

1. A method for evaluating the health status of a power battery cell, characterized in that: The following steps are involved: Periodically collect the terminal voltage sequence of all monomers {U i,k-1 ,U i,k ,U i,k+1 }、Current sequence {I i,k-1 ,I i,k ,I i,k+1 }, and the vehicle speed sequence {v k-1 ,v k ,v k+1 }, where i represents the monomer number and the sampling time k≥1; Real-time working condition identification, identifying the period when the vehicle is in acceleration condition; Estimation of the equivalent impedance characteristic parameters of the monomer level, calculation of the equivalent impedance characteristic parameters R of all monomers under acceleration conditions i,k ; The ohmic internal resistance of the monomer level is estimated respectively by an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics; The online evaluation of battery health status is achieved by integrating the phased estimation results of the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics.

2. The method for evaluating the health status of a power battery cell according to claim 1, characterized in that: Identifying the period of time when the vehicle is in acceleration condition specifically includes: if |v k -v k-1 |v k+1 -v k |If the difference in value is less than a preset value and both are less than the design threshold, the vehicle is considered to be in a stable operating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and satisfy v k+1 >v k >v k-1 , the vehicle is considered to be in an accelerating condition; if |v k+1 -v k |v k -v k-1 | are greater than the design threshold and satisfy v k+1 <v k <v k-1 , the vehicle is considered to be in a deceleration condition.

3. The method for evaluating the health status of a power battery cell according to claim 1, characterized in that: The equivalent impedance characteristic parameter R of the monomer i,k satisfy: In the formula, R i,0 is the initial value of the equivalent impedance characteristic parameter of the i-th monomer, R EOL is the impedance value at the end of battery life.

4. The method for evaluating the health status of a power battery cell according to claim 3, characterized in that: The ohmic internal resistance estimation method based on equivalent impedance characteristic parameters includes: According to the equivalent impedance characteristic parameter table R i = {R i,0 ,R i,1 ,…,R i,k ,…} to draw the point cloud map, based on R i The sliding average estimation strategy estimates the single-cell ohmic internal resistance. The specific steps are as follows: Step 11: Design a sliding time window STW r , used to select R i Medium STW r The data set of interval is denoted as Step 12: Remove outliers using the box plot method The outliers in Step 13: Calculation The average value of is used to indirectly estimate the ohmic internal resistance of the single cell at the current stage p, that is, The average value r i,p as the ohmic internal resistance of the i-th monomer in the p-stage; Step 14: Move STW along the time axis regularly r , and move forward p one step, that is, p=p+1, and repeat Step 11-Step 13 to realize the online estimation of the monomer-level ohmic internal resistance.

5. The method for evaluating the health status of a power battery cell according to claim 4, characterized in that: The ohmic internal resistance estimation method based on charging characteristics includes: Step 21: Identify charging conditions and fit U i (k) and v(k) change curve, if v(k) is 0 for a period of time, and U i (k) If the value shows an increasing trend, it is considered that the vehicle is in charging condition during this period; Step 22: Capture the steep rise in single cell voltage at the initial stage of charging and design a sliding time window (STW) c , follow STW c All charging initial stages in the interval U i (k) Mark the starting and ending points of each part of the curve where the curve rises sharply, and calculate the average pressure difference between all the starting and ending points in satisfy Where M represents STW c The number of charges within the interval, Indicates the initial stage of the jth charging U i (k) The pressure difference between the starting point and the end point of the steep rise portion of the curve; Step 23: Normalization. Since the monomers are connected in series, the charging current of each monomer is the same, so the normalized To indirectly characterize the relative size of the monomer ohmic internal resistance; Step 24: Move STW along the time axis regularly c , and move forward p one step, that is, p=p+1, and repeat Step 21-Step 23 to realize the online estimation of the monomer-level ohmic internal resistance.

6. The method for evaluating the health status of a power battery cell according to claim 5, characterized in that: The single-cell-level ohmic internal resistance obtained by the ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and the ohmic internal resistance estimation method based on charging characteristics is normalized to obtain a single-cell-level health status, and the step includes: Use the staged normalized ohmic internal resistance to perform online assessment of the health status of the single-cell battery: In the formula, SOH i,p represents the aging degree of monomer i in stage p, with a value range of [0%, 100%], Norm{·} represents the normalization function, and w1 and w2 are design weights; Draw the r of each stage separately i,p , The bar chart marks the cells with relatively large internal resistance, providing reference and guidance for the remote operation and maintenance of in-service automotive power batteries.

7. A power battery cell level health status assessment system, characterized in that: Used to implement the power battery cell-level health status assessment method as described in any one of claims 1 to 6, including an edge main control unit and a power battery Internet of Things platform, the power battery Internet of Things platform includes a cloud database, the edge main control unit is used to monitor the vehicle battery status, collect terminal voltage sequences, current sequences, and vehicle speed sequences of all cells, complete real-time working condition identification and cell-level equivalent impedance characteristic parameter estimation, and upload the cell-level equivalent impedance characteristic parameters to the cloud database, the power battery Internet of Things platform is used to estimate the cell-level ohmic internal resistance respectively through an ohmic internal resistance estimation method based on equivalent impedance characteristic parameters and an ohmic internal resistance estimation method based on charging characteristics, and normalize the obtained cell-level ohmic internal resistance to obtain the cell-level health status.

8. An electronic device, characterized in that: It comprises a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is called and executed by the processor, the method for evaluating the health status of a power battery cell as described in any one of claims 1 to 6 is implemented.

9. A computer-readable medium, characterized in that The computer-readable medium stores a computer program, and when the computer program is called and executed by the processor, the method for evaluating the health status of a power battery cell as described in any one of claims 1 to 6 is implemented.

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