Methods for the cascade utilization of decommissioned batteries from energy storage power stations

Abstract

This invention provides a method for the tiered utilization of retired batteries from energy storage power stations, relating to the fields of electrochemical energy storage and the tiered utilization of retired batteries. The steps of this invention are as follows: S1, rapidly assess and classify the consistency of retired batteries, eliminating unusable batteries; S2, perform grouping operations on the remaining retired batteries to obtain the optimal solution; S3, assemble the retired batteries into new battery packs according to the optimal solution; S4, perform online self-healing equalization control operations on the battery packs; S5, adjust the self-healing strategy parameters; S6, track and monitor the self-healed batteries. The beneficial effects are: voltage and internal resistance are corrected to avoid interference from ambient temperature; the objective optimization function can improve grouping efficiency; the tiered self-healing strategy improves battery repair speed; self-healing strategy parameter updates ensure that the selected parameters are suitable for the corresponding batteries; the tiered tracking strategy can reduce monitoring costs; and long-term and short-term evaluations can avoid the problem of false repair successes.

Description

Technical Field

[0001] This invention relates to the field of electrochemical energy storage and the cascade utilization of retired batteries, specifically to a method for the cascade utilization of retired batteries from energy storage power stations. Background Technology

[0002] With the rapid development of new energy power generation, large-scale energy storage power stations will generate a large number of retired batteries after long-term operation. Existing cascade utilization technologies mainly suffer from the following problems: 1. Low evaluation efficiency Traditional offline capacity testing or discharge methods have long cycles, making it difficult to meet the needs of rapid screening of large numbers of decommissioned batteries in energy storage power stations.

[0003] 2. Sorting and grouping are not intelligent. Currently, most operations rely on manual or semi-automatic methods, which cannot optimize module pairing based on battery health status, resulting in poor module consistency.

[0004] 3. Lack of online self-healing and balancing measures Some retired batteries have capacity decay or performance differences, and long-term operation may cause safety risks or performance instability. Existing methods lack real-time control means.

[0005] Therefore, there is an urgent need for a method that can achieve rapid, automated, and intelligent assessment, sorting, grouping, and online self-healing control at the energy storage power station site. Summary of the Invention

[0006] The main objective of this invention is to provide a method for the cascade utilization of retired batteries from energy storage power stations, thereby solving the problems mentioned in the background art.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for the cascade utilization of retired batteries from energy storage power stations, comprising the following steps: S1. Quickly assess and classify the consistency of retired batteries, and screen out unusable batteries; S2. Perform a matching operation on the remaining retired batteries to obtain the optimal solution; S3. Assemble the retired batteries into new battery packs according to the optimal solution; S4. Perform online self-healing equalization control on the battery pack; S5. Adjust the parameters of the self-healing strategy; S6. Monitor the self-healing battery.

[0008] Furthermore, the detailed process of step S1 is as follows: S101. Connect the individual battery cell to the edge acquisition terminal of the acquisition unit and apply a small pulse signal; S102. The acquisition unit synchronously records the electrical parameters of each battery during the pulse period. The electrical parameters include: voltage change, real-time internal resistance, temperature change, and pulse duration. S103. Extract transient features from the collected data, including: voltage change rate and temperature gradient; Voltage change rate The expression is as follows: (1); in, This represents the voltage difference between the later and earlier samples in two adjacent samplings. The sampling interval; Temperature gradient The expression is as follows: (2); in, This represents the temperature difference between the second and first consecutive samples in two adjacent samplings. S104. Correct electrical parameters and transient characteristics based on ambient temperature; The internal resistance is corrected using the following expression: (3); in, , These are the corrected internal resistance value and the original value, respectively. This is the internal resistance correction factor. , These are the real-time ambient temperature and the ambient temperature reference value, respectively. The voltage change rate is corrected using the following expression: (4); in, , These are the corrected value and the original value for the rate of change of voltage, respectively. This is the voltage change rate correction factor; The rate of change of internal resistance is calculated based on the internal resistance correction value, as expressed below: (5); in, The rate of change of internal resistance, This is the first internal resistance value collected; S105. Perform consistency scoring and classify batteries according to consistency scores, then remove unusable batteries. The detailed process is as follows: First , , Normalization is performed, and the score range is defined as [0, 100]. The evaluation formula is as follows: (6); in, For consistency score, , , They are respectively , , The corresponding score , , They are respectively , , The corresponding scoring weights; when At that time, the battery was rated A, indicating high performance; when At that time, the battery was rated B, indicating medium performance; when At that time, the battery was rated C, indicating low performance; Discard the C-grade batteries and record the data information of the A-grade and B-grade batteries.

[0009] Furthermore, the battery data includes: consistency score, state of equilibrium (SOH), internal resistance correction value, voltage, capacity, cycle life, and service life.

[0010] Furthermore, the detailed process of step S2 is as follows: S201. Estimate the annual decay rate of battery cell capacity. The estimation formula is as follows: (7); in, , These are the number of cycles and the service life, respectively. , , These are the cyclic attenuation coefficient, the service attenuation coefficient, and the internal resistance attenuation coefficient, respectively. S202. Perform scenario determination; extract the cells with the highest and lowest consistency scores from the same batch of batteries, and record the highest consistency score as... The maximum consistency value is denoted as . ; Set scene judgment threshold When there is This refers to a typical scenario; When there is This is a scenario of significant inconsistency; S203. Group and match according to different scenarios to determine the optimal solution; The grouping must meet the following constraints: (8); in, This represents the difference between the maximum and minimum voltage values ​​among all batteries in the same group. , These are the minimum and maximum internal resistance values ​​for each battery in the same group, respectively. , These are the minimum and maximum values ​​of the current actual usable maximum capacity for each battery in the same group, respectively. , These are the minimum and maximum annual degradation rates for each battery in the same group, respectively.

[0011] Furthermore, the detailed process of step S203 is as follows: For typical scenarios, first determine the objective optimization function; the number of batteries in each group remains consistent with the number of batteries in the original battery group, therefore, the number of battery groups is determined based on the number of candidate batteries, and denoted as [missing information]. The number of batteries in each group is recorded as Then the expression for the objective optimization function is as follows: (9); in, The objective function value, , , , The first Group 1 The voltage, internal resistance, current usable maximum capacity, and annual degradation rate of each battery. , , , The first Average voltage, average internal resistance, average current usable maximum capacity, and average annual degradation rate of the battery pack; The objective of the optimization function is to make the objective function value The goal is to minimize the objective function. The optimal solution is the one that minimizes the objective function. The solution that minimizes the objective function within the constraints is the optimal solution, and the grouping and pairing scheme corresponding to this solution is called the optimal scheme. For cases of significant inconsistency, the batch of batteries will be reclassified. Grade A is divided into Grade A1 and Grade A2, and Grade B is divided into Grade B1 and Grade B2; The standard for Grade A1 is: ; The standard for A2 level is: ; The standard for B1 level is: ; The standard for B2 level is: ; The grouping method at each level is the same as in the conventional scenario, resulting in the optimal solution.

[0012] Furthermore, the detailed process of step S4 is as follows: S401: Real-time acquisition of battery pack operating data, combined with electrical data acquired during pulse periods, to calculate basic indicators; Operational data includes: battery, individual cell voltage, internal resistance correction value, real-time temperature, SOC, and cycle count increment; The basic indicators include: voltage deviation, SOC deviation, temperature rise rate, and internal resistance change rate. S402. Assess the risk level of the battery cell; the risk levels are divided into three levels from high to low: Level 3, Level 2, and Level 1. The rules for determining risk levels are as follows: By comparing the risk conditions, determine the basic indicators and SOH levels of the battery, and find the item with the highest risk level. The risk level corresponding to this parameter is the risk level of the battery. If the battery's basic indicators and SOH do not meet the risk conditions of Level 1, 2, or 3, the battery is considered to be in a state of no degradation. S403. Based on the risk level, provide a corresponding self-healing strategy to self-heal the control battery. The self-healing strategy corresponding to Level 1 risk is: Perform a mild discharge equalization operation on the battery; The self-healing process is complete when the stopping conditions are met. The stopping conditions are: voltage deviation less than 30mV, SOC deviation not exceeding 2%, and SOH exceeding 85% but not exceeding 15%. Set safety protection activation conditions, and reduce the discharge rate when the safety protection activation conditions are met; The safety protection activation condition is that the temperature rise rate is greater than 2℃ / s; The self-healing strategy corresponding to Level 2 risk is: The battery is subjected to step-by-step standard current balancing and low-intensity pulse activation operations in sequence, with a large time interval between the current balancing and pulse activation operations to avoid heat accumulation. The self-healing process is complete when the stopping conditions are met. When the safety protection activation conditions are met, pulse activation is immediately stopped, and only equalization operation is maintained until self-healing is completed; The safety protection activation condition is: the temperature rise rate is greater than 2.5℃ / s; The self-healing strategy corresponding to Level 3 risk is: The battery is subjected to high-intensity pulse activation and stepped low-current equalization operations in sequence; a large time interval is left between the pulse activation and current activation operations to avoid heat accumulation. The self-healing process ends when the stopping condition is met. Similarly, set the safety protection activation conditions. When the safety protection activation conditions are met, immediately stop the self-healing and start the cooling operation. The safety protection activation conditions are: either the temperature is greater than 45℃ or the temperature rise rate is greater than 3℃ / s. When the temperature does not exceed 35℃ and the temperature rise rate is less than 1.5℃ / s, the self-healing process will restart. Repeat the self-healing strategy until self-healing is complete; S404. Conduct short-term and long-term repair assessments; Within 10 minutes of the battery healing process being completed, the battery's basic indicators and SOH data were extracted again, and the SOH improvement rate, internal resistance improvement rate, and consistency recovery rate of the battery cell were calculated. The expression for the SOH improvement rate is as follows: (10); in, For SOH improvement rate, , The SOH values ​​are shown for the battery before and after self-healing, respectively. The expression for the internal resistance improvement rate is as follows: (11); in, For the internal resistance improvement rate, , These represent the rate of change of internal resistance of the battery before and after self-healing, respectively. The expression for the consistency recovery rate is as follows: (12); in, For consistency recovery rate, , These are the voltage deviations before and after battery self-healing, respectively. The improvement rate of SOH, the improvement rate of internal resistance, and the recovery rate of consistency are judged. When at least two of them meet the short-term repair conditions, the short-term repair is judged to be successful. When the battery does not meet the short-term repair conditions, remove the battery from the module. When the battery short-term repair meets the standard, the battery cell operation data is extracted 7 days and 30 days after self-healing, and the 7-day SOH decay rate and 30-day consistency deviation rate are calculated. The expression for the 7-day SOH decay rate is: (13); in, The 7-day SOH decay rate The SOH (Solubility and Health) on the 7th day after battery self-healing; The expression for the 30-day consistency deviation rate is: (14); in, The 30-day consistency deviation rate. The voltage deviation is on the 7th day after the battery self-heals. The 7-day SOH decay rate and 30-day consistency deviation rate were evaluated. When the long-term repair conditions were met, the long-term repair was deemed to have met the standards. If the long-term repair conditions are not met, it is determined that the long-term repair is not up to standard. After fine-tuning the pulse and current balancing parameters in the battery self-healing strategy, step S4 is re-executed to perform self-healing.

[0013] Furthermore, in step S402, the risk level conditions are as follows: Level 1 risk conditions include: Condition 1, voltage deviation range is [80mV, 100mV) or SOC deviation range is [3%, 5%); Condition 2, the range of SOH is [75%, 80%) and ; Level 2 risk conditions include: Condition 3, voltage deviation greater than 100mV or SOC deviation greater than 5%; Condition 4, the range of SOH is [70%, 75%) and ; Level 3 risk conditions include: Condition 5. ; Condition 6: SOH is less than 70%; Condition 7: The rate of temperature rise is greater than 2℃ / s.

[0014] Furthermore, the short-term repair conditions are as follows: (15); in, The threshold for achieving the SOH improvement rate is... The threshold for achieving the improvement rate of internal resistance is... The threshold for achieving the consistency recovery rate; The conditions for long-term repair are as follows: (16); in, The threshold for long-term SOH repair indicators. This is the threshold for long-term voltage deviation repair indicators.

[0015] Furthermore, the adjustment process in step S5 is as follows: For batteries that have achieved long-term repair standards, the pulse and current balancing parameters in their battery self-healing strategy are used as general parameters for the corresponding risk level battery self-healing strategy.

[0016] Furthermore, the tracking and monitoring process is as follows: After the battery corresponding to the level 3 risk is cured, it will be monitored for 30 consecutive days in a high-frequency monitoring manner. If there are no abnormalities after 30 days, it will be switched to routine monitoring. After the battery corresponding to the level 2 risk is cured, it will be monitored for 14 consecutive days using high-frequency monitoring. If there are no abnormalities after 14 days, it will be switched to routine monitoring. After the battery corresponding to Level 1 risk is cured, it should be monitored for 7 consecutive days using high-frequency monitoring. If there are no abnormalities after 7 days, it should be switched to routine monitoring.

[0017] Beneficial effects: (1) Adjust the voltage and internal resistance according to the ambient temperature to avoid interference from the ambient temperature; (2) Introducing an objective optimization function for grouping can overcome the drawbacks of traditional grouping methods that rely on manual grouping, improve grouping efficiency, and reduce costs; (3) A graded self-healing strategy can be selected in a targeted manner to improve the battery repair speed; (4) The self-healing strategy parameter update can ensure that the selected parameters are compatible with the corresponding battery; (5) A tiered tracking strategy can reduce monitoring costs; (6) Introducing long-term and short-term assessments can not only promptly screen out batteries that have failed to be repaired, but also avoid the problem of false repair success. Attached Figure Description

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 This is a flowchart of the steps of the method of the present invention. Detailed Implementation

[0019] Example 1 like Figure 1 As shown, a method for the cascade utilization of decommissioned batteries from an energy storage power station includes the following steps: S1. Conduct a rapid assessment and classification of the consistency of retired batteries, and screen out unusable batteries. The detailed process is as follows: S101. Connect the individual battery cell to the edge acquisition terminal of the acquisition unit and apply a small pulse current or voltage signal, such as a 0.5C constant short pulse current with a pulse duration of 5 seconds. S102. The acquisition unit synchronously records the electrical parameters of each battery during the pulse period at a sampling rate of 1kHz. The electrical parameters include: voltage change, real-time internal resistance, temperature change, and pulse duration. S103. The consistency evaluation unit extracts transient features from the collected data, including voltage change rate and temperature gradient; transient features can better characterize the state of the battery. Voltage change rate The expression is as follows: (1); in, This represents the voltage difference between the later and earlier samples in two adjacent samplings. The sampling interval; Temperature gradient The expression is as follows: (2); in, This represents the temperature difference between the second and first consecutive samples in two adjacent samplings. S104. To eliminate interference from ambient temperature, electrical parameters and transient characteristics are corrected based on ambient temperature. The internal resistance is corrected using the following expression: (3); in, , These are the corrected internal resistance value and the original value, respectively. This is the internal resistance correction factor, typically taken as 0.008 / ℃. , These are the real-time ambient temperature and the ambient temperature reference value, respectively. It is generally set to 25℃; The voltage change rate is corrected using the following expression: (4); in, , These are the corrected value and the original value for the rate of change of voltage, respectively. This is the voltage change rate correction factor, typically taken as 0.005 / ℃; The rate of change of internal resistance, calculated based on the internal resistance correction value, reflects the degree of aging of the battery cell. The expression is as follows: (5); in, The rate of change of internal resistance, This is the first internal resistance value collected; S105. Conduct consistency scoring and classify according to consistency scores; First , , Normalization is performed, and the score range is determined to be [0, 100]. The specific process is as follows: for When the value equals 0.01, the score is 0; when the value equals 0.1, the score is 100, determined by the points (0.01, 0) and (0.1, 100). The linear function relationship between the score and the interval [0.01, 0.1] is as follows: When the score is less than 0.1, the score is directly taken as 0. When the score is greater than 0.1, the score is directly set to 100. for When the value equals 50, the score is 0; when the value equals 5, the score is 100, determined by the points (50,0) and (5,100). The linear function relationship between the score and the interval [5, 50] is as follows: When the score is less than 5, the score is directly taken as 100. If the score is greater than 50, the score is set to 0. for When the value equals 0.8, the score is 0; when the value equals 0.1, the score is 100. This is determined based on the points (0.8, 0) and (0.1, 100). The linear function relationship between the score and the interval [0.1, 0.8] is as follows: When the score is less than 0.1, the score is directly taken as 100. If the score is greater than 0.8, the score is set to 0. The evaluation formula is as follows: (6); in, For consistency score, , , They are respectively , , The corresponding score , , They are respectively , , The corresponding scoring weights; , , The values ​​are generally 0.4, 0.3, and 0.3. when At that time, the battery was rated A, indicating high performance; when At that time, the battery was rated B, indicating medium performance; when At that time, the battery was rated C, indicating low performance; C-grade batteries were eliminated, and data information for A-grade and B-grade batteries was recorded. Battery data information included: consistency score, state of equilibrium (SOH), internal resistance correction value, voltage, capacity, cycle count, and service life.

[0020] S2. Perform a matching operation on the remaining retired batteries to obtain the optimal solution. The detailed process is as follows: S201. Estimate the annual decay rate of battery cell capacity. The estimation formula is as follows: (7); in, , These are the number of cycles and the service life, respectively. , , These are the cyclic attenuation coefficient, the service attenuation coefficient, and the internal resistance attenuation coefficient, respectively. Generally, 0.0008% per dose is taken. Generally, it is taken as 0.003% / year. The general value is 0.002% / Ω; S202, Perform scene determination; Extract the cells with the highest and lowest consistency scores from the same batch of batteries, and record the highest consistency score as . The maximum consistency value is denoted as . ; Set scene judgment threshold When there is This refers to a typical scenario; When there is This is a scenario of significant inconsistency; 20 is a better number; S203. Group and match according to different scenarios to determine the optimal solution; To prevent excessive differences in batteries within the same group, grouping must meet the following constraints: (8); in, This represents the difference between the maximum and minimum voltage values ​​among all batteries in the same group. , These are the minimum and maximum internal resistance values ​​for each battery in the same group, respectively. , These are the minimum and maximum values ​​of the current actual usable maximum capacity for each battery in the same group, respectively. , These are the minimum and maximum annual degradation rates for each battery in the same group, respectively. For typical scenarios, first determine the objective optimization function; the number of batteries in each group remains consistent with the number of batteries in the original battery group, therefore, the number of battery groups is determined based on the number of candidate batteries, and denoted as [missing information]. The number of batteries in each group is recorded as Then the expression for the objective optimization function is as follows: (9); in, The objective function value, , , , The first Group 1 The voltage, internal resistance, current usable maximum capacity, and annual degradation rate of each battery. , , , The first Average voltage, average internal resistance, average current usable maximum capacity, and average annual degradation rate of the battery pack; The objective of the optimization function is to make the objective function value The goal is to minimize the objective function. The optimal solution is the one that minimizes the objective function. The solution that minimizes the objective function within the constraints is the optimal solution, and the grouping and pairing scheme corresponding to this solution is called the optimal scheme. For cases of significant inconsistency, the batch of batteries will be reclassified. The secondary classification is carried out within Grade A and Grade B, that is, Grade A is divided into Grade A1 and Grade A2, and Grade B is divided into Grade B1 and Grade B2; The standard for Grade A1 is: ; The standard for A2 level is: ; The standard for B1 level is: ; The standard for B2 level is: ; At this point, groups are formed within levels A1, A2, B1, and B2, in the same way as in the conventional scenario. That is, the number of groups in levels A1, A2, B1, and B2 is determined based on the total number of batteries in levels A1, A2, B1, and B2, and then the optimal solution of the objective optimization function is obtained to get the optimal solution.

[0021] S3. Assemble the retired batteries into new battery packs according to the optimal solution.

[0022] S4. Perform online self-healing balancing control on the battery pack. The detailed process is as follows: S401: Real-time acquisition of battery pack operating data, combined with electrical data acquired during pulse periods, to calculate basic indicators; Operational data includes: battery, individual cell voltage, internal resistance correction value, real-time temperature, SOC, and cycle count increment; The definition of SOH is: (10); in, This refers to the battery's rated capacity. The definition of SOC is: (11); in, This represents the current remaining capacity of the battery. The basic indicators include: voltage deviation, SOC deviation, temperature rise rate, and internal resistance change rate. ; Here, voltage deviation and SOC deviation refer to the differences between the voltage and SOC of a certain cell in the battery pack and the average voltage and SOC of the battery pack, respectively. The rate of change of internal resistance here is also used The definition is to calculate the rate of change of internal resistance using the internal resistance after temperature correction. S402. Assess the risk level of the battery cell; the risk levels are divided into three levels from high to low: Level 3, Level 2, and Level 1. The risk level criteria are as follows: Level 1 risk conditions include: Condition 1, voltage deviation range is [80mV, 100mV) or SOC deviation range is [3%, 5%); Condition 2, the range of SOH is [75%, 80%) and ; Level 2 risk conditions include: Condition 3, voltage deviation greater than 100mV or SOC deviation greater than 5%; Condition 4, the range of SOH is [70%, 75%) and ; Level 3 risk conditions include: Condition 5. ; Condition 6: SOH is less than 70%; Condition 7: The rate of temperature rise is greater than 2℃ / s; The rules for determining risk levels are as follows: By comparing the risk conditions, determine the basic indicators and SOH levels of the battery, and find the item with the highest risk level. The risk level corresponding to this parameter is the risk level of the battery. If the battery's basic indicators and SOH do not meet the risk conditions of Level 1, 2, or 3, the battery is considered to be in a state of no degradation. S403. Based on the risk level, provide a corresponding self-healing strategy to self-heal the control battery. The self-healing strategy corresponding to Level 1 risk is: Perform a mild discharge equalization operation on the battery; the discharge rate is 0.1. The self-healing process is complete when the stopping conditions are met. The stopping conditions are: voltage deviation less than 30mV, SOC deviation not exceeding 2%, and SOH exceeding 85%. No more than 15%; To ensure safety and prevent overheating, safety protection activation conditions are set. When these conditions are met, the discharge rate is reduced to 0.05. The safety protection activation condition is that the temperature rise rate is greater than 2℃ / s; The self-healing strategy corresponding to Level 2 risk is: The battery is subjected to stepped standard current balancing and low-intensity pulse activation operations in sequence, with a large time interval between the current balancing and pulse activation operations to avoid heat accumulation; the charging rate and discharging rate of the stepped balancing are 0.2 and 0.3, respectively; the pulse uses a current with a rate between 0.2 and 0.3, a duration of 3 to 5 seconds, and a pulse application frequency of 1Hz; The self-healing process is complete when the stopping conditions are met. Similarly, set the safety protection activation conditions. When the safety protection activation conditions are met, immediately stop pulse activation and only retain the equalization operation until self-healing is completed. The safety protection activation condition is: the temperature rise rate is greater than 2.5℃ / s; The self-healing strategy corresponding to Level 3 risk is: The battery is subjected to high-intensity pulse activation and stepped low-current equalization operations in sequence; a large time interval is left between the pulse activation and current activation operations to avoid heat accumulation; the pulse uses a current with a rate between 0.3 and 0.5, a duration of 5 to 8 seconds, and a pulse application frequency of 0.5 Hz; the charging rate and discharging rate of the stepped equalization are 0.1 and 0.15, respectively. The self-healing process ends when the stopping condition is met. Similarly, set the safety protection activation conditions. When the safety protection activation conditions are met, immediately stop the self-healing and start the cooling operation. The safety protection activation conditions are: either the temperature is greater than 45℃ or the temperature rise rate is greater than 3℃ / s. When the temperature does not exceed 35℃ and the temperature rise rate is less than 1.5℃ / s, the self-healing process will restart. Repeat the self-healing strategy until self-healing is complete; S404. Conduct short-term and long-term repair assessments; Within 10 minutes of the battery healing process being completed, the battery's basic indicators and SOH data were extracted again, and the SOH improvement rate, internal resistance improvement rate, and consistency recovery rate of the battery cell were calculated. The expression for the SOH improvement rate is as follows: (12); in, For SOH improvement rate, , The SOH values ​​are shown for the battery before and after self-healing, respectively. The expression for the internal resistance improvement rate is as follows: (13); in, For the internal resistance improvement rate, , These represent the rate of change of internal resistance of the battery before and after self-healing, respectively. The expression for the consistency recovery rate is as follows: (14); in, For consistency recovery rate, , These are the voltage deviations before and after battery self-healing, respectively. The improvement rate of SOH, the improvement rate of internal resistance, and the recovery rate of consistency are evaluated. Short-term repair is considered successful when at least two of these criteria are met. The short-term repair criteria are as follows: (15); in, A threshold of 3% is preferred for achieving the SOH improvement rate target. To determine the threshold for achieving the target improvement rate in internal resistance, 8% is a good starting point. A 70% threshold is preferable for achieving the consistency recovery rate target. When the battery does not meet the short-term repair conditions, remove the battery from the module. When the battery short-term repair meets the standard, the battery cell operation data is extracted 7 days and 30 days after self-healing, and the 7-day SOH decay rate and 30-day consistency deviation rate are calculated. The expression for the 7-day SOH decay rate is: (16); in, The 7-day SOH decay rate The SOH (Solubility and Health) on the 7th day after battery self-healing; The expression for the 30-day consistency deviation rate is: (17); in, The 30-day consistency deviation rate. The voltage deviation is on the 7th day after the battery self-heals. The 7-day SOH decay rate and 30-day consistency deviation rate were evaluated. When the long-term repair conditions were met, the long-term repair was deemed to have met the standards. When the conditions for long-term repair are not met, it is determined that the long-term repair is not up to standard. After fine-tuning the pulse and current balancing parameters in the battery self-healing strategy, step S4 is re-executed to perform self-healing. The conditions for long-term repair are as follows: (18); in, The threshold for long-term SOH repair is typically set at 0.5%. The threshold for long-term voltage deviation repair is generally set at 50%.

[0023] S5. Adjust the parameters of the self-healing strategy. The adjustment process is as follows: For batteries that have achieved long-term repair standards, the pulse and current balancing parameters in their battery self-healing strategy are used as general parameters for the corresponding risk level battery self-healing strategy.

[0024] S6. Follow up and monitor the self-healed battery. The follow-up and monitoring process is as follows: After the battery corresponding to the level 3 risk is cured, it will be monitored for 30 consecutive days in a high-frequency monitoring manner. If there are no abnormalities after 30 days, it will be switched to routine monitoring. After the battery corresponding to the level 2 risk is cured, it will be monitored for 14 consecutive days using high-frequency monitoring. If there are no abnormalities after 14 days, it will be switched to routine monitoring. After the battery corresponding to Level 1 risk is cured, it will be monitored for 7 consecutive days with high frequency monitoring. If there are no abnormalities after 7 days, it will be switched to routine monitoring. The monitoring frequency of high-frequency monitoring is twice that of conventional monitoring.

[0025] The above embodiments are merely preferred technical solutions of the present invention and should not be considered as limitations on the present invention. The scope of protection of the present invention should be limited to the technical solutions described in the claims, including equivalent substitutions of the technical features described in the claims. That is, equivalent substitutions and improvements within this scope are also within the scope of protection of the present invention.

Claims

1. A method for the cascade utilization of decommissioned batteries from an energy storage power station, characterized in that, Includes the following steps: S1. Quickly assess and classify the consistency of retired batteries, and screen out unusable batteries; S2. Perform a matching operation on the remaining retired batteries to obtain the optimal solution; S3. Assemble the retired batteries into new battery packs according to the optimal solution; S4. Perform online self-healing equalization control on the battery pack; S5. Adjust the parameters of the self-healing strategy; S6. Monitor the self-healing battery.

2. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 1, characterized in that, The detailed process of step S1 is as follows: S101. Connect the individual battery cell to the edge acquisition terminal of the acquisition unit and apply a small pulse signal; S102. The acquisition unit synchronously records the electrical parameters of each battery during the pulse period. The electrical parameters include: voltage change, real-time internal resistance, temperature change, and pulse duration. S103. Extract transient features from the collected data, including: voltage change rate and temperature gradient; Voltage change rate The expression is as follows: （1）； in, This represents the voltage difference between the later and earlier samples in two adjacent samplings. The sampling interval; Temperature gradient The expression is as follows: （2）； in, This represents the temperature difference between the second and first consecutive samples in two adjacent samplings. S104. Correct electrical parameters and transient characteristics based on ambient temperature; The internal resistance is corrected using the following expression: （3）； in, , These are the corrected internal resistance value and the original value, respectively. This is the internal resistance correction factor. , These are the real-time ambient temperature and the ambient temperature reference value, respectively. The voltage change rate is corrected using the following expression: （4）； in, , These are the corrected value and the original value for the rate of change of voltage, respectively. This is the voltage change rate correction factor; The rate of change of internal resistance is calculated based on the internal resistance correction value, as expressed below: （5）； in, The rate of change of internal resistance, This is the first internal resistance value collected; S105. Perform consistency scoring and classify batteries according to consistency scores, then remove unusable batteries. The detailed process is as follows: First , , Normalization is performed, and the score range is defined as [0, 100]. The evaluation formula is as follows: （6）； in, For consistency score, , , They are respectively , , The corresponding score , , They are respectively , , The corresponding scoring weights; when At that time, the battery was rated A, indicating high performance; when At that time, the battery was rated B, indicating medium performance; when At that time, the battery was rated C, indicating low performance; Discard the C-grade batteries and record the data information of the A-grade and B-grade batteries.

3. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 2, characterized in that, Battery data includes: consistency score, state of equilibrium (SOH), internal resistance correction value, voltage, capacity, cycle life, and service life.

4. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 3, characterized in that, The detailed process of step S2 is as follows: S201. Estimate the annual decay rate of battery cell capacity. The estimation formula is as follows: （7）； in, , These are the number of cycles and the service life, respectively. , , These are the cyclic attenuation coefficient, the service attenuation coefficient, and the internal resistance attenuation coefficient, respectively. S202. Perform scenario determination; extract the cells with the highest and lowest consistency scores from the same batch of batteries, and record the highest consistency score as... The maximum consistency value is denoted as . ; Set scene judgment threshold When there is This refers to a typical scenario; When there is This is a scenario of significant inconsistency; S203. Group and match according to different scenarios to determine the optimal solution; The grouping must meet the following constraints: （8）； in, This represents the difference between the maximum and minimum voltage values ​​among all batteries in the same group. , These are the minimum and maximum internal resistance values ​​for each battery in the same group, respectively. , These are the minimum and maximum values ​​of the current actual usable maximum capacity for each battery in the same group, respectively. , These are the minimum and maximum annual degradation rates for each battery in the same group, respectively.

5. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 4, characterized in that, The detailed process of step S203 is as follows: For typical scenarios, first determine the objective optimization function; the number of batteries in each group remains consistent with the number of batteries in the original battery group, therefore, the number of battery groups is determined based on the number of candidate batteries, and denoted as [missing information]. The number of batteries in each group is recorded as Then the expression for the objective optimization function is as follows: （9）； in, The objective function value, , , , The first Group 1 The voltage, internal resistance, current usable maximum capacity, and annual degradation rate of each battery. , , , The first Average voltage, average internal resistance, average current usable maximum capacity, and average annual degradation rate of the battery pack; The objective of the optimization function is to make the objective function value The goal is to minimize the objective function. The optimal solution is the one that minimizes the objective function. The solution that minimizes the objective function within the constraints is the optimal solution, and the grouping and pairing scheme corresponding to this solution is called the optimal scheme. For cases of significant inconsistency, the batch of batteries will be reclassified. Grade A is divided into Grade A1 and Grade A2, and Grade B is divided into Grade B1 and Grade B2; The standard for Grade A1 is: ; The standard for A2 level is: ; The standard for B1 level is: ; The standard for B2 level is: ; The grouping method at each level is the same as in the conventional scenario, resulting in the optimal solution.

6. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 4, characterized in that, The detailed process of step S4 is as follows: S401: Real-time acquisition of battery pack operating data, combined with electrical data acquired during pulse periods, to calculate basic indicators; Operational data includes: battery, individual cell voltage, internal resistance correction value, real-time temperature, SOC, and cycle count increment; The basic indicators include: voltage deviation, SOC deviation, temperature rise rate, and internal resistance change rate. S402. Assess the risk level of the battery cell; the risk levels are divided into three levels from high to low: Level 3, Level 2, and Level 1. The rules for determining risk levels are as follows: By comparing the risk conditions, determine the basic indicators and SOH levels of the battery, and find the item with the highest risk level. The risk level corresponding to this parameter is the risk level of the battery. If the battery's basic indicators and SOH do not meet the risk conditions of Level 1, 2, or 3, the battery is considered to be in a state of no degradation. S403. Based on the risk level, provide a corresponding self-healing strategy to self-heal the control battery. The self-healing strategy corresponding to Level 1 risk is: Perform a mild discharge equalization operation on the battery; The self-healing process is complete when the stopping conditions are met. The stopping conditions are: voltage deviation less than 30mV, SOC deviation not exceeding 2%, and SOH exceeding 85% but not exceeding 15%. Set safety protection activation conditions, and reduce the discharge rate when the safety protection activation conditions are met; The safety protection activation condition is that the temperature rise rate is greater than 2℃ / s; The self-healing strategy corresponding to Level 2 risk is: The battery is subjected to step-by-step standard current balancing and low-intensity pulse activation operations in sequence, with a large time interval between the current balancing and pulse activation operations to avoid heat accumulation. The self-healing process is complete when the stopping conditions are met. When the safety protection activation conditions are met, pulse activation is immediately stopped, and only equalization operation is maintained until self-healing is completed; The safety protection activation condition is: the temperature rise rate is greater than 2.5℃ / s; The self-healing strategy corresponding to Level 3 risk is: The battery is subjected to high-intensity pulse activation and stepped low-current equalization operations in sequence; a large time interval is left between the pulse activation and current activation operations to avoid heat accumulation. The self-healing process ends when the stopping condition is met. Similarly, set the safety protection activation conditions. When the safety protection activation conditions are met, immediately stop the self-healing and start the cooling operation. The safety protection activation conditions are: either the temperature is greater than 45℃ or the temperature rise rate is greater than 3℃ / s. When the temperature does not exceed 35℃ and the temperature rise rate is less than 1.5℃ / s, the self-healing process will restart. Repeat the self-healing strategy until self-healing is complete; S404. Conduct short-term and long-term repair assessments; Within 10 minutes of the battery healing process being completed, the battery's basic indicators and SOH data were extracted again, and the SOH improvement rate, internal resistance improvement rate, and consistency recovery rate of the battery cell were calculated. The expression for the SOH improvement rate is as follows: （10）； in, For SOH improvement rate, , The SOH values ​​are shown for the battery before and after self-healing, respectively. The expression for the internal resistance improvement rate is as follows: （11）； in, For the internal resistance improvement rate, , These represent the rate of change of internal resistance of the battery before and after self-healing, respectively. The expression for the consistency recovery rate is as follows: （12）； in, For consistency recovery rate, , These are the voltage deviations before and after battery self-healing, respectively. The improvement rate of SOH, the improvement rate of internal resistance, and the recovery rate of consistency are judged. When at least two of them meet the short-term repair conditions, the short-term repair is judged to be successful. When the battery does not meet the short-term repair conditions, remove the battery from the module. When the battery short-term repair meets the standard, the battery cell operation data is extracted 7 days and 30 days after self-healing, and the 7-day SOH decay rate and 30-day consistency deviation rate are calculated. The expression for the 7-day SOH decay rate is: （13）； in, The 7-day SOH decay rate The SOH (Solubility and Health) on the 7th day after battery self-healing; The expression for the 30-day consistency deviation rate is: （14）； in, The 30-day consistency deviation rate. The voltage deviation is on the 7th day after the battery self-heals. The 7-day SOH decay rate and 30-day consistency deviation rate were evaluated. When the long-term repair conditions were met, the long-term repair was deemed to have met the standards. If the long-term repair conditions are not met, it is determined that the long-term repair is not up to standard. After fine-tuning the pulse and current balancing parameters in the battery self-healing strategy, step S4 is re-executed to perform self-healing.

7. The method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 6, characterized in that, In step S402, the risk level conditions are as follows: Level 1 risk conditions include: Condition 1, voltage deviation range is [80mV, 100mV) or SOC deviation range is [3%, 5%); Condition 2, the range of SOH is [75%, 80%) and ; Level 2 risk conditions include: Condition 3, voltage deviation greater than 100mV or SOC deviation greater than 5%; Condition 4, the range of SOH is [70%, 75%) and ; Level 3 risk conditions include: Condition 5. ; Condition 6: SOH is less than 70%; Condition 7: The rate of temperature rise is greater than 2℃ / s.

8. A method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 6, characterized in that, The conditions for short-term repair are as follows: （15）； in, The threshold for achieving the SOH improvement rate is... The threshold for achieving the improvement rate of internal resistance is... The threshold for achieving the consistency recovery rate; The conditions for long-term repair are as follows: （16）； in, The threshold for long-term SOH repair indicators. This is the threshold for long-term voltage deviation repair indicators.

9. A method for the cascade utilization of decommissioned batteries in an energy storage power station according to claim 6, characterized in that, The adjustment process for step S5 is as follows: For batteries that have achieved long-term repair standards, the pulse and current balancing parameters in their battery self-healing strategy are used as general parameters for the corresponding risk level battery self-healing strategy.

10. A method for the cascade utilization of decommissioned batteries from an energy storage power station according to claim 7, characterized in that, The tracking and monitoring process is as follows: After the battery corresponding to the level 3 risk is cured, it will be monitored for 30 consecutive days in a high-frequency monitoring manner. If there are no abnormalities after 30 days, it will be switched to routine monitoring. After the battery corresponding to the level 2 risk is cured, it will be monitored for 14 consecutive days using high-frequency monitoring. If there are no abnormalities after 14 days, it will be switched to routine monitoring. After the battery corresponding to Level 1 risk is cured, it should be monitored for 7 consecutive days using high-frequency monitoring. If there are no abnormalities after 7 days, it should be switched to routine monitoring.

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