Power battery full life cycle management application method, system and device

Abstract

The embodiment of the invention discloses a power battery full-life-cycle management application method, system and device, and belongs to the technical field of power battery management.The method comprises the steps that an intelligent management unit is connected with an unformed battery cell in a storage battery in a binding mode, and the intelligent management unit conducts full-life-cycle monitoring on the production process of the storage battery; storage battery formation and capacity grading information in the production process of a target storage battery is recorded, a storage battery pack is built, the intelligent management unit carries out full-life-cycle monitoring on the application process of the storage battery and records parameter information in the application process of the target storage battery, and the battery cell management system carries out safety fault early warning according to the parameter information in the application process. According to the embodiment of the invention, the target storage battery can be accurately replaced or maintained, a new storage battery pack can be reformed, only the target storage battery in the storage battery pack is pertinently replaced or maintained, and the maintenance cost of a user is reduced.

Description

Technical Field

[0001] The present application relates to the technical field of power battery management, and specifically to an application method, system, and device for full life cycle management of power batteries. Background Art

[0002] Power battery packs connected in series or parallel are difficult to manage during actual operation. Problems such as power battery aging, extreme working conditions and safety boundary issues under various complex working conditions restrict the promotion and application of pure electric vehicles. Therefore, it is very necessary to achieve efficient management of power batteries throughout their life cycle. If a battery in some battery packs fails or is close to failure, it may cause the entire battery pack to fail. If the entire battery pack is replaced, the maintenance cost will increase, which will restrict the promotion and application of electric vehicle use and management. Summary of the Invention

[0003] To solve the above problems and technical defects, the present application adopts the following technical solution, a method for managing the entire life cycle of a power battery, characterized by comprising the following steps: Step 1: Bind the intelligent management unit to the unformed cells in the battery and establish a communication connection between the cell management system and the intelligent management unit; Step 2: The intelligent management unit monitors the entire life cycle of the battery production process, records the battery composition and capacity information during the target battery production process, and builds a battery pack; Step 3: The intelligent management unit monitors the battery application process throughout its entire life cycle and records parameter information during the target battery application process. Step 4: The battery cell management system performs a safety fault warning based on the parameter information during the application process, performs a consistency evaluation based on the safety fault warning result, and maintains or replaces the target battery in the battery pack based on the consistency evaluation result.

[0004] Preferably, the intelligent management unit performs full life cycle monitoring of the battery production process, including: monitoring and recording parameter information during cell formation and cell capacity division, sending the parameter information to the cell management system, the cell management system performs consistency evaluation on the parameter information during cell formation and cell capacity division based on various parameter information, and matches the batteries into groups based on the consistency evaluation results.

[0005] Preferably, the parameter information during the application process includes: current curve, voltage curve, temperature curve, and data timestamp during the charging and discharging process.

[0006] Furthermore, the safety fault warning process is as follows: Determining the model of the target battery according to the battery composition and capacity information of the target battery; Obtain historical application data of multiple battery models, and obtain the safety threshold of the target battery from the historical application data according to the model of the target battery; Obtain extreme value points according to the current curve, voltage curve, and temperature curve during the charging and discharging process of the target battery; Determine whether there is an extreme point in the target parameter curve with a parameter value exceeding a safety threshold. If so, determine that the target battery is a faulty battery. If not, proceed to the next step. Two safety threshold lines are generated in each parameter curve according to the safety threshold, and the two safety threshold lines are the maximum threshold upper line and the minimum threshold lower line respectively; The stable value of the extreme point is calculated based on the parameter value of the extreme point and the safety threshold corresponding to the two safety threshold lines; Two judgment thresholds are preset, and the stable value of each extreme point is compared with the two judgment thresholds, and the extreme points are classified and assigned values ​​according to the comparison results; Performing a fault suspicion evaluation on the target parameter curve according to the proportion of each category assignment in all category assignments, and obtaining a fault suspicion evaluation result of the target parameter curve; Performing a fault early warning evaluation on the target battery based on the suspected fault evaluation results of all parameter curves of the target battery to obtain a fault early warning evaluation result of the target battery; According to the fault warning evaluation results, the target battery is maintained or replaced to form a new battery pack.

[0007] Furthermore, the calculation formula of the stable value of the extreme point is as follows: Y n =│(X n -I) 2 -(X n -J) 2 │ / (t n -t n－1 ) Among them, Y n is the stable value of the nth extreme point, X n is the parameter value of the nth extreme point, I is the safety threshold corresponding to the upper limit of the maximum threshold, J is the safety threshold corresponding to the lower limit of the minimum threshold, t n The timestamp of the nth extreme point.

[0008] Furthermore, the two judgment thresholds are respectively a first judgment threshold and a second judgment threshold, the first judgment threshold is greater than the second judgment threshold, and the classification assignment formula is as follows: When K1<Y n When Q n =ω; When K2<Y n When K1 is less than Q n =φ; When Y n When K1 is less than Q n =σ; Among them, Q n is the classification assignment for the nth extreme point, K1 is the first proportion threshold, K2 is the second proportion threshold, ω is the first category assignment, φ is the second category assignment, and σ is the third category assignment.

[0009] Furthermore, the fault suspicion evaluation process is as follows: If the first category assignment ω accounts for the highest proportion among all classification assignments, the target curve is judged to be a high fault suspicion curve; If the second category assignment φ accounts for the highest proportion of all classification assignments, the target curve is judged to be a low fault suspicion curve; If the third category assignment σ accounts for the highest proportion among all classification assignments, the target curve is judged to be a non-fault suspect curve.

[0010] Furthermore, the fault warning evaluation process is as follows: If there is a high-fault-suspicion curve among the fault-suspicion evaluation results of all parameter curves, the target battery is judged to be a high-fault-suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are low fault suspicion curves, the target battery is judged to be a high fault suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are no-fault suspicion curves, the target battery is determined to be a no-fault suspicion battery and does not need to be maintained or replaced; Otherwise, the target battery is determined to be a low-fault suspect battery, and the user can choose whether to perform maintenance or replacement.

[0011] A power battery full life cycle management application system, including: The intelligent management module is used to bind and connect with the unformed cells in the battery, monitor the battery production process and application process throughout its life cycle, and record the battery formation capacity information during the target battery production process and parameter information during the application process; The battery cell management module is used to issue safety fault warnings based on parameter information during the application process, perform consistency evaluation based on the safety fault warning results, and maintain or replace target batteries in the battery pack based on the consistency evaluation results; The data transmission module is used to establish a communication connection between the battery cell management module and the intelligent management module.

[0012] A power battery full life cycle management application device, the device includes a service processor and a distributed memory, the service processor is connected to the memory, the distributed memory stores a service self-management program, and is configured to store machine-readable instructions. The service processor executes the service self-management program, and when the instructions are executed by the processor, the power battery full life cycle management application method as described above is implemented.

[0013] Compared with the prior art, the beneficial effects of the embodiments of the present application are: This application monitors the entire life cycle of the battery production and application processes, manages battery faults based on the monitored parameter information, performs calculations, judgments, and evaluations, and determines whether the target battery is faulty, highly suspected of a fault, has a low suspicion of a fault, or has no suspicion of a fault. Based on the judgment results, a consistency evaluation is performed, and the target battery is accurately replaced or maintained, and a new battery pack is reassembled. Only the target batteries in the battery pack are replaced or maintained in a targeted manner, thereby reducing the user's maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In the attached figure: Figure 1 A schematic diagram of the method steps of an embodiment of the present application; Figure 2 A schematic diagram of the system structure of an embodiment of the present application; Figure 3 This is a schematic diagram of the device structure of an embodiment of the present application. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0016] Example 1: Figure 1 As shown, a power battery full life cycle management application method includes the following steps: Lithium batteries are empty upon assembly and must be charged and activated. This initial charging process is called formation, and it activates the active materials within the battery. Formation, also known as activation, is a crucial step that impacts battery performance.

[0017] Capacity grading involves charging and discharging the battery, testing the discharge capacity when the grading capacity is fully charged, and determining the battery capacity. Only batteries whose tested capacity meets or exceeds the designed capacity are qualified. This process of screening qualified batteries through capacity testing is called capacity grading.

[0018] Bind the intelligent management unit to the unformed cells in the battery and establish a communication connection between the cell management system and the intelligent management unit; The intelligent management unit records the manufacturer information and cell number of the battery.

[0019] The intelligent management unit monitors the entire life cycle of the battery production process, records battery composition and capacity information during the production process, and builds battery packs; The intelligent management unit records the battery cell capacity division date.

[0020] The intelligent management unit monitors the battery production process throughout its entire life cycle, including: Monitor and record parameter information during the cell formation and cell capacity division process, and send the parameter information to the cell management system. The cell management system will perform consistency evaluation on the parameter information during the cell formation and cell capacity division process based on various parameter information, and match the batteries into groups based on the consistency evaluation results.

[0021] The intelligent management unit monitors the entire life cycle of the battery application process and records parameter information during the battery application process; The intelligent management unit records the date when the battery pack is first charged and discharged after leaving the factory.

[0022] The parameter information during the application process includes: current curve, voltage curve, temperature curve, and data timestamp during charging and discharging.

[0023] The battery cell management system performs safety fault warning based on parameter information during the application process, performs consistency evaluation based on the safety fault warning results, and maintains or replaces target batteries in the battery pack based on the consistency evaluation results.

[0024] The safety fault warning process is as follows: Determining the model of the target battery according to the battery composition and capacity information of the target battery; Obtain historical application data of multiple battery models, and obtain the safety threshold of the target battery from the historical application data according to the model of the target battery; Obtain extreme value points according to the current curve, voltage curve, and temperature curve during the charging and discharging process of the target battery; Determine whether there is an extreme point in the target parameter curve with a parameter value exceeding a safety threshold. If so, determine that the target battery is a faulty battery. If not, proceed to the next step. Safety thresholds include: maximum charge current, minimum charge current, maximum charge voltage, minimum charge voltage, maximum charge temperature, minimum charge temperature, maximum discharge current, minimum discharge current, maximum discharge voltage, minimum discharge voltage, maximum discharge temperature, and minimum discharge temperature.

[0025] Two safety threshold lines are generated in each parameter curve according to the safety threshold, and the two safety threshold lines are the maximum threshold upper line and the minimum threshold lower line respectively; The stable value of the extreme point is calculated based on the parameter value of the extreme point and the safety threshold corresponding to the two safety threshold lines; The calculation formula is as follows: Y n =│(X n -I) 2 -(X n -J) 2 │ / (t n -t n－1 ) Among them, Y n is the stable value of the nth extreme point, X n is the parameter value of the nth extreme point, I is the safety threshold corresponding to the upper limit of the maximum threshold, J is the safety threshold corresponding to the lower limit of the minimum threshold, t n The timestamp of the nth extreme point.

[0026] Two judgment thresholds are preset, and the stable value of each extreme point is compared with the two judgment thresholds, and the extreme points are classified and assigned values ​​according to the comparison results; The two judgment thresholds are the first judgment threshold and the second judgment threshold. The first judgment threshold is greater than the second judgment threshold. The classification assignment formula is as follows: When K1<Y n When Q n =ω; When K2<Y n When K1 is less than Q n =φ; When Y n When K1 is less than Q n =σ; Among them, Q n is the classification assignment of the nth extreme point, K1 is the first ratio threshold, K2 is the second ratio threshold, ω is the first category assignment, φ is the second category assignment, and σ is the third category assignment; Performing a fault suspicion evaluation on the target parameter curve according to the proportion of each category assignment in all category assignments, and obtaining a fault suspicion evaluation result of the target parameter curve; The fault suspicion evaluation process is as follows: If the first category assignment ω accounts for the highest proportion among all classification assignments, the target curve is judged to be a high fault suspicion curve; If the second category assignment φ accounts for the highest proportion of all classification assignments, the target curve is judged to be a low fault suspicion curve; If the third category assignment σ accounts for the highest proportion among all classification assignments, the target curve is judged to be a non-fault suspect curve.

[0027] Performing a fault early warning evaluation on the target battery based on the suspected fault evaluation results of all parameter curves of the target battery to obtain a fault early warning evaluation result of the target battery; The fault warning evaluation process is as follows: If there is a high-fault-suspicion curve among the fault-suspicion evaluation results of all parameter curves, the target battery is judged to be a high-fault-suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are low fault suspicion curves, the target battery is judged to be a high fault suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are no-fault suspicion curves, the target battery is determined to be a no-fault suspicion battery and does not need to be maintained or replaced; Otherwise, the target battery is determined to be a low-fault suspect battery, and the user can choose whether to perform maintenance or replacement.

[0028] According to the fault warning evaluation results, the target battery is maintained or replaced to form a new battery pack.

[0029] Example 2: Figure 2 As shown, a power battery full life cycle management application system includes: The intelligent management module is used to bind and connect with the unformed cells in the battery, monitor the battery production process and application process throughout its life cycle, and record the battery formation capacity information during the target battery production process and parameter information during the application process; The battery cell management module is used to issue safety fault warnings based on parameter information during the application process, perform consistency evaluation based on the safety fault warning results, and maintain or replace target batteries in the battery pack based on the consistency evaluation results; The data transmission module is used to establish a communication connection between the battery cell management module and the intelligent management module.

[0030] Example 3: A power battery full life cycle management application device, the device includes a service processor and a distributed memory, the service processor is connected to the memory, the distributed memory stores a service self-management program, and is configured to store machine-readable instructions. The service processor executes the service self-management program, and when the instructions are executed by the processor, the power battery full life cycle management application method as described in Example 1 is implemented.

[0031] The above-described embodiments merely represent preferred implementations of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person skilled in the art would be able to make numerous variations, improvements, and substitutions without departing from the spirit of the present application, all of which fall within the scope of protection of the present application.

Claims

1. A power battery full life cycle management application method, characterized in that: The following steps are involved: Step 1: Bind and connect the intelligent management unit to the unformed battery cells in the battery, and establish a communication connection between the battery cell management system and the intelligent management unit; Step 2: The intelligent management unit monitors the battery production process throughout its life cycle, records the battery capacity information during the target battery production process, and builds a battery pack; Step 3: The intelligent management unit monitors the battery application process throughout its life cycle and records parameter information during the application of the target battery; Step 4: The battery cell management system performs safety fault warning according to the parameter information in the application process, performs consistency evaluation according to the safety fault warning result, and maintains or replaces the target battery in the battery pack according to the consistency evaluation result.

2. A power battery full life cycle management application method according to claim 1, characterized in that: The intelligent management unit performs full life cycle monitoring of the battery production process, including: monitoring and recording parameter information during cell formation and cell capacity division, sending the parameter information to the cell management system, the cell management system performs consistency evaluation on the parameter information during cell formation and cell capacity division based on various parameter information, and matches the batteries into groups based on the consistency evaluation results.

3. A power battery full life cycle management application method according to claim 1, characterized in that: The parameter information in the application process includes: current curve, voltage curve, temperature curve, and data timestamp in the charging and discharging process.

4. A power battery full life cycle management application method according to claim 3, characterized in that: The safety fault warning process is as follows: Determine the model of the target battery according to the battery composition capacity information of the target battery; Obtain historical application data of multiple types of batteries, and obtain the safety threshold of the target battery from the historical application data according to the model of the target battery; Obtain extreme value points according to the current curve, voltage curve, and temperature curve during the charging and discharging process of the target battery; Determine whether there is an extreme point in the target parameter curve whose parameter value exceeds the safety threshold. If so, determine that the target battery is a faulty battery. If not, proceed to the next step. Two safety threshold lines are generated in each parameter curve according to the safety threshold, and the two safety threshold lines are respectively the maximum threshold upper line and the minimum threshold lower line; The stable value of the extreme point is calculated based on the parameter value of the extreme point and the safety threshold corresponding to the two safety threshold lines; Two judgment thresholds are preset, and the stable value of each extreme point is compared with the two judgment thresholds, and the extreme points are classified and assigned values ​​according to the comparison results; Performing a fault suspicion evaluation on the target parameter curve according to the proportion of each type of assignment in all the classification assignments, and obtaining a fault suspicion evaluation result of the target parameter curve; Performing a fault warning evaluation on the target battery according to the suspected fault evaluation results of all parameter curves of the target battery, and obtaining a fault warning evaluation result of the target battery; According to the fault warning evaluation results, the target battery is maintained or replaced to form a new battery pack.

5. A power battery full life cycle management application method according to claim 4, characterized in that: The calculation formula of the stable value of the extreme point is as follows: Y n =│(X n -I) 2 -(X n -J) 2 │ / (t n -t n－1 ) Among them, Y n is the stable value of the nth extreme point, X n is the parameter value of the nth extreme point, I is the safety threshold corresponding to the upper limit of the maximum threshold, J is the safety threshold corresponding to the lower limit of the minimum threshold, t n The timestamp of the nth extreme point.

6. A power battery full life cycle management application method according to claim 5, characterized in that: The two judgment thresholds are respectively a first judgment threshold and a second judgment threshold, the first judgment threshold is greater than the second judgment threshold, and the classification assignment formula is as follows: When K1<Y n When n =ω; When K2<Y n When <K1, Q n =φ; When Y n When <K1, Q n =σ; Among them, Q n Assign the classification value of the nth extreme point, K1 is the first proportion threshold, K2 is the second proportion threshold, ω is the first category assignment, φ is the second category assignment, and σ is the third category assignment.

7. A power battery full life cycle management application method according to claim 6, characterized in that: The fault suspicion evaluation process is as follows: If the first category assignment ω accounts for the highest proportion of all classification assignments, the target curve is judged to be a high fault suspicion curve; If the second category assignment φ accounts for the highest proportion of all classification assignments, the target curve is judged to be a low fault suspicion curve; If the third category assignment σ accounts for the highest proportion of all classification assignments, the target curve is judged to be a non-fault suspect curve.

8. A power battery full life cycle management application method according to claim 7, characterized in that: The fault warning evaluation process is as follows: If there is a high-fault-suspicion curve in the fault-suspicion evaluation results of all parameter curves, the target battery is judged to be a high-fault-suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are low fault suspicion curves, the target battery is judged to be a high fault suspicion battery and needs to be maintained or replaced; If all the fault suspicion evaluation results of all parameter curves are non-fault suspicion curves, the target battery is judged to be a non-fault suspicion battery and does not need to be maintained or replaced; Otherwise, the target battery is determined to be a low-fault suspect battery, and the user can choose whether to perform maintenance or replacement.

9. A power battery full life cycle management application system, characterized in that: include: The intelligent management module is used to bind and connect with the unformed cells in the battery, monitor the battery production process and application process throughout the life cycle, and record the battery formation capacity information during the target battery production process and parameter information during the application process; The battery cell management module is used to make safety fault warnings according to parameter information in the application process, perform consistency evaluation according to the safety fault warning results, and maintain or replace the target batteries in the battery pack according to the consistency evaluation results; The data transmission module is used to establish a communication connection between the battery cell management module and the intelligent management module.

10. A power battery full life cycle management application device, characterized in that: The device includes a service processor and a distributed memory, the service processor is connected to the memory, the distributed memory stores a service self-management program, and is configured to store machine-readable instructions. The service processor executes the service self-management program, and when the instructions are executed by the processor, the power battery full life cycle management application method as described in claim 8 is implemented.

Images