Battery aging library control method, device, equipment and medium

Abstract

The application discloses a battery aging library control method, device, equipment and medium, the battery aging library control method is through even deployment temperature detection device in the preset workspace area of aging library, collects the temperature data of key node, adopts space interpolation algorithm to convert discrete temperature data into continuous temperature field covering all aging library sites, realizes accurate reduction of temperature of each library site, based on real-time temperature value of each library site in continuous temperature field, combines preset temperature and aging rate conversion relation to dynamically calculate aging cumulative progress, when aging cumulative progress of any library site reaches preset completion threshold, immediately triggers the library instruction. The scheme breaks through the limitation of traditional fixed time length of the library mode, through dynamic construction of space temperature field and real-time calculation of aging progress, ensures that the batteries in different temperature library sites all reach consistent aging completion state, eliminates the influence of uneven temperature distribution, and significantly improves the consistency of battery performance.

Description

Technical Field

[0001] This invention relates to the field of battery production and testing technology, and in particular to a method, apparatus, equipment, and medium for controlling battery aging chambers. Background Technology

[0002] Currently, in the production process of new energy lithium batteries, after completing preliminary processes such as formation and capacity testing, the batteries need to undergo high-temperature aging treatment. This process aims to promote the more uniform and dense formation of the SEI film (solid electrolyte interface film) through a high-temperature environment, avoiding a "capacity drop" and ensuring that the battery's initial capacity, internal resistance, and other core parameters are stable before leaving the factory, thus reducing performance fluctuations during user use.

[0003] Under current technology, traditional high-temperature aging management typically relies solely on the ambient temperature of the storage area. A fixed aging time (e.g., 48 hours) is set to determine whether batteries meet process requirements before they are released for the next process. However, in actual battery aging storage areas, temperature distribution across different locations is not entirely consistent. Especially in automated storage and retrieval systems, differences in temperature across locations due to airflow, heat source distribution, and equipment layout affect the degree of aging. Furthermore, a fixed high-temperature aging time results in warehouse resource consumption and impacts production capacity turnover efficiency. Therefore, a battery aging storage control method is urgently needed to address the problem of inconsistent battery aging degrees caused by uneven temperature distribution across storage locations in the current high-temperature aging process. Summary of the Invention

[0004] The embodiments of the present invention provide a method, apparatus, equipment and medium for controlling battery aging chambers, which aims to solve the problem of inconsistent battery aging degree caused by uneven temperature distribution in the storage area during the high-temperature aging process of batteries in the prior art.

[0005] In a first aspect, embodiments of the present invention provide a battery aging chamber control method, applied to a battery aging chamber, the battery aging chamber including aging chamber locations and temperature detection devices, wherein multiple aging chamber locations and temperature detection devices are uniformly distributed within a preset working space area, the method comprising: collecting temperature data of nodes within the preset working space area through the temperature detection devices; generating a continuous temperature field covering all aging chamber locations within the entire preset working space area based on the temperature data using a spatial interpolation algorithm; calculating the aging accumulation progress of each aging chamber location based on the real-time temperature values ​​of each aging chamber location in the continuous temperature field, combined with a preset temperature-aging rate conversion relationship; and sending an outbound command for the chamber location when the aging accumulation progress of any aging chamber location reaches a preset completion threshold.

[0006] Secondly, embodiments of the present invention also provide a battery aging library control device for executing the battery aging library control method described above.

[0007] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the above-described battery aging library control method.

[0008] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the steps of the above-described battery aging library control method.

[0009] Compared with the prior art, the beneficial effects of the present invention are:

[0010] In the technical solution of this invention, the battery aging chamber control method uniformly deploys temperature detection devices within a preset working space area of ​​the aging chamber to collect temperature data at key nodes; employs a spatial interpolation algorithm to transform discrete temperature data into a continuous temperature field covering all aging chamber locations, achieving accurate temperature restoration for each location; based on the real-time temperature values ​​of each location in the continuous temperature field, and combined with a preset temperature-aging rate conversion relationship, dynamically calculates the aging accumulation progress; when the aging accumulation progress of any location reaches a preset completion threshold, an outbound command is triggered immediately. This solution overcomes the limitations of the traditional fixed-duration outbound mode, ensuring that batteries in different temperature chamber locations reach a consistent aging completion state through the dynamic construction of the spatial temperature field and real-time calculation of the aging progress, significantly improving battery performance consistency while eliminating the impact of uneven temperature distribution. Attached Figure Description

[0011] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A flowchart of the battery aging library control method provided by the present invention;

[0013] Figure 2 The first sub-flowchart of the battery aging library control method provided by the present invention;

[0014] Figure 3 This is a second sub-flowchart of the battery aging library control method provided by the present invention;

[0015] Figure 4 The third sub-flowchart of the battery aging library control method provided by the present invention;

[0016] Figure 5 The fourth sub-flowchart of the battery aging library control method provided by the present invention;

[0017] Figure 6 The fifth sub-flowchart of the battery aging library control method provided by the present invention;

[0018] Figure 7 The sixth sub-flowchart of the battery aging library control method provided by the present invention;

[0019] Figure 8 A schematic block diagram of a unit of the battery aging chamber control device provided by the present invention;

[0020] Figure 9 A schematic block diagram of a computer device provided in an embodiment of the present invention;

[0021] Figure 10 This is a schematic diagram of the aging chamber layout for the battery aging chamber control method provided in an embodiment of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0024] It should also be understood that the terminology used in this specification is for the purpose of describing embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0025] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0026] This invention addresses the problem of inconsistent battery aging degrees caused by uneven temperature distribution in the battery aging process under existing technologies. It discloses a battery aging chamber control method applied to a battery aging chamber. The aging chamber consists of multiple storage locations evenly distributed within a pre-defined working space. Each aging location is equipped with a temperature detection device, i.e., a temperature acquisition probe, which has a unique number within the system. The temperature detection device collects real-time temperature data from each node according to a set cycle. The temperature detection device transmits the collected temperature data to the control system via wired or wireless means, using the WebAPI protocol in JSON format for data exchange to ensure the stability and real-time performance of data transmission.

[0027] Reference Figures 1 to 7 The method includes the following steps:

[0028] S110. Collect temperature data of the nodes within the preset workspace area where it is located through the temperature detection device;

[0029] S120. Based on the temperature data, a continuous temperature field covering all the aging storage locations within the entire preset working space area is generated using a spatial interpolation algorithm.

[0030] S130. Based on the real-time temperature values ​​of each aging storage location in the continuous temperature field, and combined with the preset temperature-aging rate conversion relationship, calculate the cumulative aging progress of each aging storage location.

[0031] S140. When the aging accumulation progress of any of the aging storage locations reaches a preset completion threshold, send an outbound instruction for that storage location.

[0032] First, temperature data is collected from each temperature detection device. Based on this temperature data, a continuous temperature field covering all aging storage locations within the entire preset working space is generated using a spatial interpolation algorithm. Specifically, the spatial interpolation algorithm employs bilinear interpolation. Bilinear interpolation utilizes data from four adjacent temperature sensors in the storage area to calculate the temperature value of the target storage location through linear interpolation.

[0033] Based on the real-time temperature values ​​of each aging storage location within the continuous temperature field, and combined with a preset temperature-to-aging-rate conversion relationship, the system calculates the cumulative aging progress for each storage location. Specifically, the temperature-to-aging-rate conversion relationship is obtained through experimental calibration; the high-temperature aging rate of batteries varies at different temperatures, with higher temperatures requiring shorter aging times. The system converts the current temperature value of each storage location into an aging progress value using a temperature-to-time correspondence table and accumulates it to a set threshold, such as 100%. When the temperature of a storage location changes, the system dynamically adjusts to ensure that the calculation results reflect the current true aging state.

[0034] When the aging progress of any of the aforementioned aging storage locations reaches a preset completion threshold, an outbound command is sent to that storage location. Specifically, the system polls each storage location at a set period to check if it meets the outbound conditions, such as every 30 seconds. When the aging progress of a storage location reaches 100%, the system immediately generates an outbound task and pushes it to the warehouse control system (WCS). The system optimizes the outbound sequence based on factors such as storage location, outbound channel occupancy, and production needs, releasing storage locations that have met the conditions first, thereby improving warehouse utilization and reducing production bottlenecks.

[0035] Furthermore, to further improve outbound efficiency, intelligent optimization algorithms are incorporated into outbound task scheduling. For example, genetic algorithms or simulated annealing algorithms can be used to optimize the outbound sequence, reducing the time spent in outbound channels and production bottlenecks. In addition, the priority of outbound tasks can be dynamically adjusted based on production plans and inventory status to ensure the efficient operation of the production process.

[0036] Furthermore, to improve system stability and reliability, more anomaly detection and handling mechanisms can be incorporated into the data preprocessing stage. For example, if the data from a temperature probe acquired by a temperature acquisition system is empty, the system can use the most recently acquired normal data for calculation. When a temperature probe's temperature value is abnormal—that is, if it is zero or exceeds the normal value—the system can notify the operator via a pop-up alert for inspection and handling. Simultaneously, the system automatically records each acquisition of raw data, including the number of each abnormal probe, its temperature value, and the acquisition time, for subsequent maintenance reference.

[0037] In one embodiment, reference is made to Figure 2 The steps in S120 include:

[0038] S121. Periodically acquire the current temperature data of the temperature detection device at each geometric vertex in the spatial area where the target aging storage location is located;

[0039] S122. Based on the current temperature data, perform linear interpolation calculation in the first preset direction to generate an intermediate temperature value;

[0040] S123. Based on the current temperature data and the intermediate temperature value, perform linear interpolation calculation in the second preset direction to generate the target storage location temperature.

[0041] The current temperature data of the temperature detection devices at each geometric vertex within the spatial area where the target aging storage location is located is periodically acquired. Specifically, the temperature detection devices are installed in key locations within the storage area, such as each layer and column, to ensure coverage of the entire aging area. Each temperature detection device has a unique number used to establish coordinate mapping relationships in temperature calculations.

[0042] Based on the current temperature data, multiple linear interpolation calculations need to be performed according to the storage area settings to generate intermediate temperature values ​​first, and then the target storage location temperature needs to be obtained to confirm the storage area temperature of each aging storage location. Figure 10 For example, suppose we need to calculate the temperature value of point P, where the coordinates are (x, y), in the aging storage area. The layout of the battery aging storage area where this aging storage point is located is a planar rectangle. In this case, the so-called first preset direction is the horizontal direction, and the second preset direction is the vertical direction. The coordinates and temperature values ​​of the four vertices closest to point P are known to be Q1(x1, y1, ..., y1). Q2(x2,y1, Q3(x1,y2, ) and Q4(x2,y2, First, perform a linear interpolation in the horizontal direction to calculate the temperature at the midpoint Q12 (x-axis, y-axis) on the bottom edge. The formula is:

[0043] ;

[0044] Then, a second interpolation is performed in the horizontal direction to calculate the temperature of the midpoint Q34 (x-axis, y-axis) located on the top edge, using the following formula:

[0045] ;

[0046] Finally, a third interpolation is performed in the vertical direction to calculate the temperature T at point P, using the following formula:

[0047] ;

[0048] Through the above steps, the real-time temperature value of each storage location within the entire preset working space can be calculated, generating a continuous temperature field. After generating the continuous temperature field, to facilitate operators' monitoring of the temperature distribution in the storage area, the generated temperature field data can be visualized. Using a heat map or a 3D temperature distribution map, the temperature changes within the storage area can be intuitively displayed on a screen connected to the control system of the battery aging storage area, helping operators to promptly identify and address temperature anomalies. Furthermore, to further improve the accuracy of the interpolation algorithm, higher-order interpolation algorithms, such as cubic spline interpolation or radial basis function interpolation, can be introduced. These algorithms can better fit the temperature distribution, especially in areas with large temperature variations, improving the accuracy of the interpolation results.

[0049] Furthermore, to improve the accuracy and reliability of interpolation calculations, preprocessing can be performed after temperature data acquisition. For example, filtering algorithms, such as low-pass filtering, can be used to remove noise and improve data smoothness. Additionally, data anomaly detection algorithms can be employed to automatically identify and remove abnormal data, ensuring the accuracy of interpolation calculations.

[0050] In one embodiment, reference is made to Figure 3 Step S121 is followed by:

[0051] S121a. When a data loss is detected in any of the temperature detection devices, the most recent valid temperature value of the temperature detection device is retrieved from the historical database.

[0052] S121b. When the current temperature data of the temperature detection device is detected to exceed the preset reasonable range, the temperature detection device is marked as abnormal and an abnormal warning signal is triggered.

[0053] After each data acquisition, the system checks the data returned by each temperature detection device. If it detects that the data from a certain temperature detection device is empty or missing, the system automatically retrieves the most recent valid temperature value for that device from the historical database. This mechanism ensures that the system can continue temperature interpolation calculations even in the event of missing data, avoiding misjudgments in outbound data due to single-point data loss. For example, assuming that temperature detection device Q1 loses data during a data acquisition, the system will automatically retrieve the most recent valid temperature value for Q1 from the historical database and use it for subsequent interpolation calculations.

[0054] When the current temperature data of the temperature detection device exceeds a preset reasonable range, the system marks the temperature detection device as abnormal and triggers an abnormality warning signal. Specifically, after each data acquisition, the system automatically checks whether the current temperature data of each temperature detection device is within the preset reasonable range. The preset reasonable range can be set according to the actual temperature distribution of the warehouse area and historical data; for example, the reasonable range can be set to 25℃ to 45℃. If the current temperature data of a certain temperature detection device exceeds this range, the system will immediately mark the temperature detection device as abnormal and trigger an abnormality warning signal. The warning signal can notify the operator in various ways, such as pop-up prompts, SMS notifications, and email notifications. In addition, the system will record detailed information for each abnormal detection, including the abnormal probe number, temperature value, and acquisition time, for subsequent maintenance and fault analysis reference. For example, assuming the current temperature value of temperature detection device Q2 is 50℃, exceeding the preset reasonable range of 45℃, the system will mark Q2 as abnormal and send an abnormality warning signal to the operator.

[0055] Based on the above embodiments, to further improve the system's fault tolerance, redundant temperature detection devices are added to the battery aging chamber. For example, multiple temperature detection devices are installed at each geometric vertex. When a temperature detection device malfunctions or loses data, the system can automatically switch to a backup device to ensure data continuity and reliability.

[0056] In one embodiment, reference is made to Figure 4 The steps in S130 include:

[0057] S131. Based on the preset temperature-aging rate mapping curve, the target storage temperature is converted into an instantaneous aging rate.

[0058] S132. Integrate the instantaneous aging rate over a continuous time period to generate an aging cumulative progress value.

[0059] Based on a preset temperature-to-aging-rate mapping curve, the target storage temperature is converted into an instantaneous aging rate. Specifically, the conversion relationship between temperature and aging rate is obtained through experimental calibration; the high-temperature aging rate of the battery varies at different temperatures, with higher temperatures resulting in faster aging rates. The preset temperature-to-aging-rate mapping curve is typically stored in the system in the form of a table or function. For example, assuming the mapping curve is... Where r represents the aging rate and T represents the temperature. The system calculates the corresponding instantaneous aging rate based on the real-time temperature value of each aging storage location by looking up a mapping curve or function. For example, if the temperature of the target storage location is 35°C, the system finds the corresponding instantaneous aging rate to be 0.001% / hour through the mapping curve.

[0060] The instantaneous aging rate over a continuous time period is integrated to generate the cumulative aging progress value. Specifically, the system calculates the instantaneous aging rate corresponding to the target storage temperature in each data acquisition cycle, multiplies it by the time interval, and obtains the cumulative aging amount P within that time period, as shown in the formula:

[0061] ;

[0062] The system sums up the accumulated aging amount in each cycle to generate an accumulated aging progress value P, using the following formula:

[0063] ;

[0064] Where n represents the total number of data collection cycles. Through the above steps, the system can dynamically calculate the cumulative aging progress of each aging storage location, ensuring that the calculation results reflect the current true aging status.

[0065] Furthermore, referring to Figure 5The step of constructing the preset temperature-aging rate conversion relationship in step S131 includes:

[0066] S1311. By conducting multiple sets of constant temperature battery aging experiments in the battery aging chamber, the critical time for stable battery performance under different temperatures is measured.

[0067] S1312. Based on the reciprocal of the critical time, construct a nonlinear positive correlation function between temperature and aging rate.

[0068] Multiple sets of constant-temperature battery aging experiments were conducted in the battery aging chamber to measure the critical time for battery performance to stabilize at different temperatures. Specifically, the experiment was designed as follows: representative battery models were selected to ensure the universality and reliability of the experimental results; multiple constant temperature points were set, such as 46℃, 49℃, 52℃, and 55℃, and the experiment was repeated multiple times at each temperature point to reduce experimental errors; at each temperature point, the batteries were placed in the aging chamber for long-term aging experiments, and changes in battery performance, such as capacity and internal resistance, were recorded; battery performance data were collected periodically until the battery performance stabilized, i.e., the critical time was reached. The critical time is defined as the point at which battery performance changes tend to plateau.

[0069] The critical time for battery performance stability at each temperature point was determined using experimental data. The specific steps are as follows: Analyze the experimental data at each temperature point and plot the curve of battery performance changing over time; identify the inflection point of the curve, i.e., the point at which the rate of change in battery performance significantly decreases, which is the critical time; record the critical time at each temperature point and create a data table, for example: 46℃: 36 hours, 49℃: 32 hours, 52℃: 29 hours, 55℃: 24 hours.

[0070] Using the reciprocal of the critical time as a benchmark, a nonlinear positive correlation function between temperature and aging rate is constructed. The specific steps are as follows: Calculate the aging rate at each temperature point, i.e., the reciprocal of the critical time; using these data points, fit the nonlinear positive correlation function between temperature and aging rate through regression analysis methods, such as multinomial regression or exponential regression; then determine the optimal fitting parameters using the least squares method or other optimization methods to ensure that the function accurately describes the relationship between temperature and aging rate.

[0071] In practical applications, the aging rate of batteries is affected not only by temperature but also by factors such as humidity, voltage, and current. Multi-factor experiments can be conducted to comprehensively consider the impact of these factors on the aging rate, thereby constructing a more comprehensive multivariate aging rate model and improving the system's adaptability and reliability.

[0072] Furthermore, to address the dynamic changes in the storage environment, a real-time update mechanism will be introduced into the battery aging storage control method. For example, the system can periodically conduct small-scale experiments to monitor changes in the actual aging rate and dynamically adjust the parameters of the temperature-aging rate function to ensure it always conforms to the current actual operating conditions. Machine learning algorithms can also be used to predict temperature change trends in the storage area based on historical and current data, allowing for advance adjustments to the aging rate calculation method and improving the system's adaptability and robustness.

[0073] In one embodiment, reference is made to Figure 6 The steps in S140 include:

[0074] S141. Through a preset aging storage location status polling mechanism, monitor the aging accumulation progress of each storage location in real time.

[0075] S142. When the progress value is detected to have reached the preset completion threshold, the outbound instruction containing the coordinates of the aging storage location is generated.

[0076] S143. Based on the topology of the battery aging library and the load status of the battery aging library's outbound channel, dynamically optimize the outbound command.

[0077] In this embodiment, the system is designed with a periodic polling task to check the aging progress of all aging storage locations at set time intervals. The polling task accesses a database storing the aging progress to obtain the latest aging progress value for each storage location. For example, assuming there are 100 aging storage locations in the system, each with a unique number (such as storage location 1, storage location 2, ..., storage location 100), the polling task will check the progress value of each storage location sequentially. When the progress value reaches a preset completion threshold, an outbound instruction containing the coordinates of the aging storage location is generated. The preset completion threshold is set according to the battery aging process requirements; for example, assuming the completion threshold is 100%, it indicates that battery aging is complete. When the polling task detects that the aging progress of a certain storage location has reached 100%, the system generates an outbound instruction. This outbound instruction contains the coordinate information of the aging storage location; for example, the outbound instruction format is "Outbound Instruction: Storage Location 12 (3,4)", where (3,4) represents the coordinate position of storage location 12 in the aging storage. The generated outbound instruction will be sent to the outbound control system to execute subsequent outbound operations.

[0078] Based on the topology of the battery aging chamber and the load status of its outbound channels, the system dynamically optimizes the outbound commands. Specifically, the system considers the topology of the aging chamber and the real-time load status of the outbound channels to optimize the execution order of the outbound commands. The topology of the aging chamber includes information such as the layout of the storage locations and the location and number of outbound channels. The load status of the outbound channels can be obtained through a real-time monitoring system.

[0079] In one embodiment, reference is made to Figure 7 The battery aging library control method of the present invention further includes:

[0080] S150. Monitor the performance parameters of batteries that have been aged and shipped out in subsequent processes.

[0081] S160. When the performance parameters of the battery are detected to fluctuate beyond a preset performance threshold, the parameters of the temperature-aging rate conversion relationship are reverse-calibrated.

[0082] After the battery cells have aged and left the warehouse, the system continues to monitor their performance parameters in real time during subsequent processes. Performance parameters include, but are not limited to, the cell's capacity, internal resistance, and self-discharge rate. Monitoring equipment can be automated testing equipment or manual inspection equipment, depending on the actual production environment. For example, assuming the battery cells enter the charge-discharge testing process after leaving the warehouse, the system will periodically collect the cell's performance data using automated testing equipment and store it in a database. When the system detects that the performance parameters of the battery cells fluctuate beyond a preset performance threshold, it will trigger a reverse calibration mechanism. The preset performance threshold is set based on the normal performance range of the battery cells; for example, assuming the capacity fluctuation threshold is ±5% and the internal resistance fluctuation threshold is ±10%. When the system detects that the performance parameters of a battery cell fluctuate beyond the preset threshold, it will generate an alarm message and automatically initiate the reverse calibration process. For example, assuming the system detects that the capacity of a battery cell drops from 1000mAh to 940mAh, with a fluctuation exceeding 5%, the system will trigger the reverse calibration mechanism.

[0083] The core of the reverse calibration mechanism is adjusting the parameters of the temperature-aging rate conversion relationship to ensure a more accurate aging process for subsequent battery cells. The system collects data on battery cells whose performance parameters fluctuate beyond a threshold, including temperature records of the aging storage locations and cumulative aging progress records. The system analyzes the collected data to diagnose the causes of performance parameter fluctuations. For example, if an anomaly is found in the temperature record of a storage location, it may be due to a faulty temperature sensor or temperature control equipment. Based on the diagnostic results, the system adjusts the parameters of the temperature-aging rate conversion relationship. For instance, if a systematic deviation is found in the temperature record of a storage location, the system can adjust the parameters of the temperature-aging rate mapping curve for that location to better reflect actual operating conditions. After parameter adjustment, the system verifies the adjustment effect in subsequent aging experiments to ensure that the new parameters effectively reduce performance parameter fluctuations. If the verification results are unsatisfactory, the system continues to adjust the parameters until the expected effect is achieved.

[0084] As can be seen from the above embodiments, the battery aging chamber control method of the present invention has broad application prospects and huge market potential. Through intelligent, data-driven control methods, the accuracy and efficiency of battery aging control can be significantly improved, enhancing battery performance and lifespan, and meeting market demands in fields such as electric vehicles, energy storage systems, and portable electronic devices. Simultaneously, policy support and environmental requirements provide a favorable external environment for the development of this technology. Therefore, this technology is expected to play a significant role in the future battery industry, promoting the further development and application of battery technology.

[0085] Figure 8 This is a schematic block diagram of a battery aging chamber control device 600 provided in an embodiment of the present invention. Figure 8 As shown, corresponding to the above-described battery aging chamber control method, the present invention also provides a battery aging chamber control device 600. This battery aging chamber control device 600 includes a unit for executing the above-described battery aging chamber control method, and the device can be configured in a desktop computer, tablet computer, smartphone, or other terminal.

[0086] Specifically, please refer to Figure 8 The battery aging chamber control device 600 includes:

[0087] The parameter acquisition unit 610 is used to collect temperature data of the nodes within the preset workspace area where it is located through the temperature detection device.

[0088] The continuous temperature field construction unit 620 is used to generate a continuous temperature field covering all the aging storage locations within the entire preset working space area based on the temperature data and through a spatial interpolation algorithm.

[0089] The aging cumulative progress acquisition unit 630 is used to calculate the aging cumulative progress of each aging storage location based on the real-time temperature value of each aging storage location in the continuous temperature field and in combination with the preset temperature and aging rate conversion relationship.

[0090] The outbound judgment unit 640 is used to send an outbound instruction for any of the aging storage locations when the cumulative aging progress of any of the aging storage locations reaches a preset completion threshold.

[0091] In one embodiment, the continuous temperature field construction unit 620 includes:

[0092] A periodic acquisition unit is used to periodically acquire the current temperature data of the temperature detection device at each geometric vertex within the spatial area where the target aging storage location is located;

[0093] The first linear interpolation calculation unit is used to perform linear interpolation calculation in a first preset direction based on the current temperature data to generate an intermediate temperature value;

[0094] The second linear interpolation calculation unit is used to perform linear interpolation calculation in a second preset direction to generate the target storage location temperature based on the current temperature data and the intermediate temperature value.

[0095] In one embodiment, the periodic acquisition unit is further provided with:

[0096] The data missing completion unit is used to retrieve the most recent valid temperature value of the temperature detection device from the historical database when a data missing is detected in any of the temperature detection devices.

[0097] The data anomaly alarm unit is used to mark the temperature detection device as abnormal and trigger an anomaly warning signal when the current temperature data of the temperature detection device is detected to exceed a preset reasonable range.

[0098] In one embodiment, the aging accumulation progress acquisition unit 630 includes:

[0099] The instantaneous aging rate acquisition unit is used to convert the target storage temperature into an instantaneous aging rate according to a preset temperature-aging rate mapping curve.

[0100] The aging cumulative progress value conversion unit is used to perform integral calculation on the instantaneous aging rate over a continuous time period to generate an aging cumulative progress value.

[0101] In one embodiment, the instantaneous aging rate acquisition unit includes:

[0102] The critical time acquisition unit is used to measure the critical time for battery performance to stabilize under different temperatures by conducting multiple sets of constant temperature battery aging experiments in the battery aging library.

[0103] The relational function construction unit is used to construct a nonlinear positive correlation function between temperature and aging rate based on the reciprocal of the critical time.

[0104] In one embodiment, the outbound judgment unit 640 includes:

[0105] The equipment control command generation unit is used to monitor the aging accumulation progress of each storage location in real time through a preset aging storage location status polling mechanism.

[0106] The outbound instruction generation unit is used to generate the outbound instruction containing the coordinates of the aging storage location when the progress value is detected to have reached a preset completion threshold.

[0107] The outbound instruction optimization unit is used to dynamically optimize the outbound instruction based on the topology of the battery aging warehouse and the load status of the outbound channel of the battery aging warehouse.

[0108] In one embodiment, the battery aging chamber control device 600 further includes:

[0109] The battery status monitoring unit is used to monitor the performance parameters of batteries that have been aged and shipped out of the warehouse in subsequent processes.

[0110] The parameter reverse optimization unit is used to reverse-calibrate the parameters of the temperature-aging rate conversion relationship when the performance parameter fluctuation of the battery is detected to exceed the preset performance threshold.

[0111] The aforementioned battery aging chamber control device 600 can be implemented as a computer program, which can, for example... Figure 9 It runs on the computer device shown.

[0112] Please see Figure 9 , Figure 9 This is a schematic block diagram of a computer device 500 provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a desktop computer, tablet computer, or smartphone. The server can be a standalone server or a server cluster composed of multiple servers.

[0113] See Figure 9 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0114] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a battery aging library control method.

[0115] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0116] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a battery aging library control method.

[0117] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0118] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0119] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0120] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0121] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0122] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0123] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0124] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0125] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0126] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0127] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A battery aging library control method, characterized by, The application is applied to a battery aging library, the battery aging library comprises aging library sites and temperature detection devices, a plurality of the aging library sites and temperature detection devices are uniformly distributed in a preset working space area, and the method comprises the following steps: Collecting temperature data of nodes in the preset working space area by the temperature detection device; Based on the temperature data, a continuous temperature field covering all the aging library sites in the entire preset working space area is generated by a spatial interpolation algorithm; According to the real-time temperature value of each aging library site in the continuous temperature field, the aging cumulative progress of each aging library site is calculated in combination with a preset temperature and aging rate conversion relationship; When the aging cumulative progress of any aging library site reaches a preset completion threshold, an out-of-library instruction of the library site is sent.

2. The battery degradation library control method according to claim 1, characterized by, The step of generating a continuous temperature field covering all the aging library sites in the entire preset working space area based on the temperature data by a spatial interpolation algorithm comprises the following steps: Periodically acquiring current temperature data of the temperature detection device on each geometric vertex in the space area where the target aging library site is located; Based on the current temperature data, an intermediate temperature value is generated by performing linear interpolation calculation in a first preset direction; Based on the current temperature data and the intermediate temperature value, a target library site temperature is generated by performing linear interpolation calculation in a second preset direction.

3. The battery degradation library control method according to claim 2, characterized by, The step of periodically acquiring current temperature data of the temperature detection device on each geometric vertex in the space area where the target aging library site is located further comprises the following steps: When it is detected that any temperature detection device has data loss, the latest valid temperature value of the temperature detection device is retrieved from a historical database; When it is detected that the current temperature data of the temperature detection device is out of a preset reasonable range, the temperature detection device is marked as an abnormal state and an abnormal early warning signal is triggered.

4. The battery degradation library control method according to claim 2, characterized by, The step of calculating the aging cumulative progress of each aging library site according to the real-time temperature value of each aging library site in the continuous temperature field in combination with a preset temperature and aging rate conversion relationship comprises the following steps: According to a preset temperature and aging rate mapping curve, the target library site temperature is converted into an instantaneous aging rate; The instantaneous aging rate in a continuous time period is integrated to generate an aging cumulative progress value.

5. The battery degradation library control method according to claim 1, characterized by, The step of sending an out-of-library instruction of the library site when the aging cumulative progress of any aging library site reaches a preset completion threshold comprises the following steps: The aging cumulative progress of each library site is monitored in real time through a preset aging library site state polling mechanism; When it is detected that the progress value reaches the preset completion threshold, the out-of-library instruction containing the coordinates of the aging library site is generated; Based on the topology of the battery aging library and the out-of-library channel load state of the battery aging library, the out-of-library instruction is dynamically optimized.

6. The battery degradation library control method according to claim 1, characterized by, The method further comprises the following steps: Monitoring the performance parameters of the battery out of the library in subsequent processes; When it is detected that the performance parameter fluctuation of the battery exceeds a preset performance threshold, the parameters of the temperature and aging rate conversion relationship are calibrated in reverse.

7. The battery degradation library control method according to claim 4, characterized by, The construction step of the preset temperature and aging rate conversion relationship comprises the following steps: The critical time of battery performance stability under different temperatures is measured by performing multiple sets of constant-temperature battery aging experiments in the battery aging library; A nonlinear positive correlation function of temperature and aging rate is constructed based on the reciprocal of the critical time.

8. A battery aging library control device characterized by comprising: A battery aging library control method is provided.

9. A computer device, comprising: The computer device comprises a memory and a processor connected to the memory; the memory is used to store a computer program; and the processor is used to run the computer program stored in the memory to execute the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program comprises program instructions which, when executed by a processor, can implement the steps of the method according to any one of claims 1 to 7.

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