Battery charge state calibration method and device and computer equipment

Abstract

The invention relates to a battery charge state calibration method and device and computer equipment. The method comprises the following steps: acquiring a battery cluster charge state, a maintenance duration and a current calibration time of the multi-cluster direct-current battery cabinet; under the condition that the current calibration time of the multi-cluster direct-current battery cabinet is lower than a preset time threshold value, the battery cluster charge state is a preset charge state, and the maintenance duration of the multi-cluster direct-current battery cabinet in the battery cluster charge state is longer than a preset duration, the cloud passive charge state calibration strategy is used to calibrate the current calibration time of the multi-cluster direct-current battery cabinet. Performing state-of-charge calibration processing on the multi-cluster direct-current battery cabinets; on the contrary, through an active state-of-charge calibration strategy, carrying out state-of-charge calibration processing on the multi-cluster direct-current battery cabinet; and after the calibration processing is completed, updating the battery cluster charge state of the multi-cluster direct-current battery cabinet and the maintenance duration of the multi-cluster direct-current battery cabinet in the battery cluster charge state. By adopting the method, the SOC calibration accuracy under the condition that multiple clusters of batteries are connected in parallel can be improved.

Description

Technical Field

[0001] This application relates to the technical field of energy storage battery control in electrochemical energy storage, and particularly to a method, device, and computer equipment for calibrating the state of charge of a battery. Background Art

[0002] In the frequency modulation application scenario where multiple clusters of DC battery cabinets in an energy storage system are connected in parallel, there is often a working condition where lithium iron phosphate batteries cannot be fully charged and discharged and can only be charged and discharged in the voltage plateau region. Due to factors such as differences in current sampling errors between clusters, current bias differences, battery consistency, and the inability to meet the conditions for entering the OCV-SOC (open circuit voltage-state of charge) curve calibration, after the system operates for a certain period, there is an easy problem of large calculation errors in the SOC (state of charge) value. Therefore, it is necessary to calibrate the state of charge to reduce the calculation error of the battery state of charge.

[0003] The traditional method for calibrating the state of charge of a battery is to calculate the integral of the dynamic change in the ampere-hour during the charging and discharging process of the battery; then synchronously read the dynamic change in the ampere-hour of the battery during the charging and discharging process, and manage and count the remaining ampere-hour data of the battery according to the dynamic change in the ampere-hour of the battery, so as to calculate the SOC value of the battery and calibrate the SOC value. However, this technology can only calibrate the SOC of a single battery. When it comes to the case of multiple clusters of batteries connected in parallel and operating in a frequency modulation scenario, the working SOC of the battery is in the range of 40%-60% (voltage plateau region) for a long time, and the cumulative error formed during long-term operation cannot be calibrated by the calibration strategy, resulting in poor accuracy in calibrating the SOC in the case of multiple clusters of batteries connected in parallel. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer equipment, computer-readable storage medium, and computer program product for calibrating the state of charge of a battery.

[0005] In a first aspect, this application provides a method for calibrating the state of charge of a battery, including:

[0006] Obtain the state of charge of battery clusters of multiple clusters of DC battery cabinets, the duration of maintaining the state of charge of the multiple clusters of DC battery cabinets in the state of charge of the battery clusters, and the current calibration time of the multiple clusters of DC battery cabinets;

[0007] When the current calibration time of the multiple clusters of DC battery cabinets is lower than a preset time threshold, the state of charge of the battery clusters is a preset state of charge, and the duration of maintaining the state of charge of the multiple clusters of DC battery cabinets in the state of charge of the battery clusters is greater than a preset duration, perform a state of charge calibration process on the multiple clusters of DC battery cabinets through a cloud passive state of charge calibration strategy;

[0008] When the current calibration time of the multi-cluster DC battery cabinet is higher than the preset time threshold, the state of charge of the battery cluster is the preset state of charge, and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery cluster is greater than the preset duration, the state of charge calibration process is performed on the multi-cluster DC battery cabinet through an active state of charge calibration strategy;

[0009] After completing the calibration process, update the state of charge of the battery cluster of the multi-cluster DC battery cabinet and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery cluster.

[0010] Optionally, the state of charge calibration process for the multi-cluster DC battery cabinet through the cloud passive state of charge calibration strategy includes:

[0011] Obtain the full battery data of the multi-cluster DC battery cabinet over the entire time period, and based on the current full battery data, determine whether the multi-cluster DC battery cabinet meets the state of charge calibration conditions;

[0012] When the multi-cluster DC battery cabinet meets the state of charge calibration conditions, calculate the current state of charge of the multi-cluster DC battery cabinet through a state of charge recognition model based on the current full battery data;

[0013] Send the current state of charge to the local state calibration unit in a manner issued by the cloud, and based on the current state of charge, perform the state of charge calibration process on the multi-cluster DC battery cabinet through the local state calibration unit.

[0014] Optionally, the determination of whether the multi-cluster DC battery cabinet meets the state of charge calibration conditions based on the current full battery data includes:

[0015] Based on the full battery data, identify the battery voltage value of the multi-cluster DC battery cabinet, the battery current value of the multi-cluster DC battery cabinet, and the battery temperature value of the multi-cluster DC battery cabinet;

[0016] Based on the battery voltage value, the battery current value, and the battery temperature value, train the initial state of charge recognition model, and when the number of training times of the initial state of charge recognition model is lower than the preset number of training times, return to execute the step of obtaining the current full battery data of the multi-cluster DC battery cabinet;

[0017] When the number of training times of the initial state of charge recognition model is not less than the preset number of training times, use the initial state of charge recognition model obtained in the last iteration as the target state of charge recognition model, and determine that the multi-cluster DC battery cabinet meets the state of charge calibration conditions.

[0018] Optionally, the process of calibrating the state of charge of the multi-cluster DC battery cabinet through the active state of charge calibration strategy includes:

[0019] In the multi-cluster DC battery cabinet, randomly select a target single-cluster battery and cut off the battery scheduling response mode of the target single-cluster battery;

[0020] Through the power-on control unit, control the target single-cluster battery to perform power-on processing, and when the highest single-cell voltage of the target single-cluster battery reaches the full charge calibration voltage threshold, based on the preset state of charge calibration value, replace the current state of charge of the target single-cluster battery to obtain the new state of charge of the target single-cluster battery;

[0021] Based on the new state of charge, perform state of charge calibration processing on the target single-cluster battery and restore the battery scheduling response mode of the target single-cluster battery;

[0022] In the multi-cluster DC battery cabinet, re-select the target single-cluster battery that has not been selected as the target single-cluster battery and return to execute the step of cutting off the battery scheduling response mode of the target single-cluster battery until it is determined that all single-cluster batteries have completed the state of charge calibration processing, and then determine that the multi-cluster DC battery cabinet has completed the state of charge calibration processing.

[0023] Optionally, before replacing the current state of charge of the target single-cluster battery with the preset state of charge calibration value to obtain the new state of charge of the target single-cluster battery, it further includes:

[0024] Based on the battery specification information of the target single-cluster battery, identify the minimum continuous charging value of the target single-cluster battery, and based on the minimum continuous charging value, through the power-on control unit, perform continuous charging processing on the target single-cluster battery;

[0025] Detect the current battery voltage value of the target single-cluster battery, and when the current battery voltage value is lower than the full charge calibration voltage threshold, return to execute the step of detecting the current battery voltage value of the target single-cluster battery until the current battery voltage value is equal to the full charge calibration voltage threshold, and then determine that the highest single-cell voltage of the target single-cluster battery reaches the full charge calibration voltage threshold.

[0026] Optionally, the process of updating the state of charge of the battery clusters in the multi-cluster DC battery cabinet and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters includes:

[0027] Identify the current state of charge of the multi-cluster DC battery cabinet and replace the state of charge of the battery clusters in the multi-cluster DC battery cabinet with the current state of charge;

[0028] Zero out the maintenance duration to complete the update task of the maintenance duration of the multi-cluster DC battery cabinet in the battery cluster state of charge.

[0029] In a second aspect, the present application also provides a device for calibrating the state of charge of a battery, including:

[0030] An acquisition module, configured to acquire the state of charge of the battery clusters of the multi-cluster DC battery cabinet, the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters, and the current calibration time of the multi-cluster DC battery cabinet;

[0031] A first calibration module, configured to perform a state of charge calibration process on the multi-cluster DC battery cabinet through a cloud passive state of charge calibration strategy when the current calibration time of the multi-cluster DC battery cabinet is lower than a preset time threshold, the state of charge of the battery clusters is a preset state of charge, and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters is greater than a preset duration;

[0032] A first calibration module, configured to perform a state of charge calibration process on the multi-cluster DC battery cabinet through an active state of charge calibration strategy when the current calibration time of the multi-cluster DC battery cabinet is higher than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters is greater than the preset duration;

[0033] An update module, configured to update the state of charge of the battery clusters of the multi-cluster DC battery cabinet and the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters after completing the calibration process.

[0034] Optionally, the first calibration module is specifically configured to:

[0035] Acquire the full battery data of the multi-cluster DC battery cabinet over the entire period, and based on the current full battery data, determine whether the multi-cluster DC battery cabinet meets the state of charge calibration conditions;

[0036] When the multi-cluster DC battery cabinet meets the state of charge calibration conditions, calculate the current state of charge of the multi-cluster DC battery cabinet through a state of charge recognition model based on the current full battery data;

[0037] Send the current state of charge to the local state calibration unit in a manner of cloud distribution, and perform a state of charge calibration process on the multi-cluster DC battery cabinet through the local state calibration unit based on the current state of charge.

[0038] Optionally, the first calibration module is specifically configured to:

[0039] Based on the full battery data, identify the battery voltage value of the multi-cluster DC battery cabinets, the battery current value of the multi-cluster DC battery cabinets, and the battery temperature value of the multi-cluster DC battery cabinets;

[0040] Based on the battery voltage value, the battery current value, and the battery temperature value, train the initial state of charge recognition model, and when the number of training times of the initial state of charge recognition model is lower than the preset number of training times, return to execute the step of obtaining the current full battery data of the multi-cluster DC battery cabinets;

[0041] When the number of training times of the initial state of charge recognition model is not lower than the preset number of training times, take the initial state of charge recognition model obtained in the last iteration as the target state of charge recognition model, and determine that the multi-cluster DC battery cabinets meet the state of charge calibration conditions.

[0042] Optionally, the second calibration module is specifically configured to:

[0043] Randomly select a target single-cluster battery from the multi-cluster DC battery cabinets, and cut off the battery scheduling response mode of the target single-cluster battery;

[0044] Through the power-on control unit, control the target single-cluster battery to perform power-on processing, and when the highest single-cell voltage of the target single-cluster battery reaches the full charge calibration voltage threshold, based on the preset state of charge calibration value, replace the current state of charge of the target single-cluster battery to obtain the new state of charge of the target single-cluster battery;

[0045] Based on the new state of charge, perform state of charge calibration processing on the target single-cluster battery, and restore the battery scheduling response mode of the target single-cluster battery;

[0046] In the multi-cluster DC battery cabinets, re-select the target single-cluster batteries that have not been selected as the target single-cluster batteries, and return to execute the step of cutting off the battery scheduling response mode of the target single-cluster battery until it is determined that all single-cluster batteries have completed the state of charge calibration processing, and determine that the multi-cluster DC battery cabinets have completed the state of charge calibration processing.

[0047] Optionally, the device further includes:

[0048] A power-on module, configured to identify the minimum continuous charging value of the target single-cluster battery based on the battery specification information of the target single-cluster battery, and based on the minimum continuous charging value, through the power-on control unit, perform continuous charging processing on the target single-cluster battery;

[0049] A detection module, configured to detect the current battery voltage value of the target single cluster of batteries, and when the current battery voltage value is lower than the full charge calibration voltage threshold, return to execute the step of detecting the current battery voltage value of the target single cluster of batteries until the current battery voltage value is equal to the full charge calibration voltage threshold, and determine that the highest single cell voltage of the target single cluster of batteries reaches the full charge calibration voltage threshold.

[0050] Optionally, the update module is specifically configured to:

[0051] Identify the current state of charge of the multi-cluster DC battery cabinet, and replace the state of charge of the battery clusters of the multi-cluster DC battery cabinet with the current state of charge;

[0052] Reset the maintenance duration to zero to complete the update task of the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery clusters.

[0053] In a third aspect, the present application provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method described in any one of the first aspects are implemented.

[0054] In a fourth aspect, the present application provides a computer-readable storage medium. A computer program is stored thereon, and when the computer program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0055] In a fifth aspect, the present application provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0056] The above-mentioned method, device and computer equipment for calibrating the state of charge of a battery obtain the state of charge of battery clusters of multiple clusters of DC battery cabinets, the duration of maintaining the state of charge of the battery clusters in the multiple clusters of DC battery cabinets, and the current calibration time of the multiple clusters of DC battery cabinets; when the current calibration time of the multiple clusters of DC battery cabinets is lower than a preset time threshold, the state of charge of the battery clusters is a preset state of charge, and the duration of maintaining the state of charge of the battery clusters in the multiple clusters of DC battery cabinets is greater than a preset duration, the state of charge of the multiple clusters of DC battery cabinets is calibrated through a cloud passive state of charge calibration strategy; when the current calibration time of the multiple clusters of DC battery cabinets is higher than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the duration of maintaining the state of charge of the battery clusters in the multiple clusters of DC battery cabinets is greater than the preset duration, the state of charge of the multiple clusters of DC battery cabinets is calibrated through an active state of charge calibration strategy; after the calibration process is completed, the state of charge of the battery clusters of the multiple clusters of DC battery cabinets and the duration of maintaining the state of charge of the battery clusters in the multiple clusters of DC battery cabinets are updated. This solution uses an active calibration method and a cloud passive state of charge calibration strategy to perform state of charge calibration under different state of charge conditions of the battery clusters and different durations of maintaining the state of charge, so as to ensure that the state of charge can be calibrated under any state conditions of the battery clusters. Moreover, this solution designs different battery state calculation methods for different states of the battery clusters, thereby greatly reducing the SOC calculation error under the condition of parallel connection of multiple clusters of batteries and improving the SOC calibration accuracy under the condition of parallel connection of multiple clusters of batteries. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1 It is an application environment diagram of the method for calibrating the state of charge of a battery in an embodiment;

[0059] Figure 2 It is a flowchart of the method for calibrating the state of charge of a battery in an embodiment;

[0060] Figure 3 It is a flowchart of an example of calibrating the state of charge of a battery in an embodiment;

[0061] Figure 4 It is a structural block diagram of the device for calibrating the state of charge of a battery in an embodiment;

[0062] Figure 5 It is the internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0063] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0064] The method for calibrating the state of charge of a battery provided by an embodiment of the present application can be applied to an application environment such as Figure 1 shown in the parallel connection of multiple clusters of batteries. Among them, in this application environment, it includes a host battery cabinet and multiple slave battery cabinets. Each battery cabinet is connected in parallel, and all battery cabinets perform state-of-charge calibration through a control center including an EMS (Energy Management System), an SCU (local monitoring system, three-level BMS (Battery Monitoring and Management System)), a switch, a PCS (Power Conversion System), and the cloud. Among them, the SCU is responsible for summarizing and statistically analyzing the information of multiple clusters of batteries, power-on and power-off management, and external northbound communication; the EMS is responsible for charge and discharge scheduling management, coordinating the control of the PCS and the SCU to ensure the safety of the power system during power consumption and the power quality; the PCS is a charge and discharge execution unit; the GRU (Gated Recurrent Unit Network, that is, a recurrent neural network). Among them, the control center can be a terminal, a server, or a system combined by a terminal and a server. Among them, the terminal can be but is not limited to a computer, a personal computer, a laptop computer, etc., and the server can be implemented by an independent server or a server cluster composed of multiple servers. Among them, when the control center is a terminal, the terminal uses an active calibration method and a cloud passive state-of-charge calibration strategy to perform state-of-charge calibration respectively under different state-of-charge conditions of the battery cluster and under different maintenance duration conditions of different state-of-charge, so as to ensure that the state-of-charge calibration can be performed under any state conditions of the battery cluster, and this solution designs different battery state calculation methods for different states of the battery cluster, thereby greatly reducing the SOC calculation error under the condition of parallel connection of multiple clusters of batteries and improving the SOC calibration accuracy under the condition of parallel connection of multiple clusters of batteries.

[0065] In an exemplary embodiment, as Figure 2 shown, a method for calibrating the state of charge of a battery is provided, and this method is applied to Figure 1Taking the case where the control center is a terminal as an example, it includes the following steps S201 to S204. Among them:

[0066] Step S201: Obtain the state of charge of the battery clusters of multiple clusters of DC battery cabinets, the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets, and the current calibrated time of multiple clusters of DC battery cabinets.

[0067] In this embodiment, the terminal obtains the state of charge in each battery cabinet of multiple clusters of DC battery cabinets through the SCU to obtain the state of charge of the battery clusters. Then, the terminal uses the timing module to detect in real time the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets and the current calibrated time of multiple clusters of DC battery cabinets.

[0068] Step S202: When the current calibrated time of multiple clusters of DC battery cabinets is lower than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets is greater than the preset duration, perform a state-of-charge calibration process on multiple clusters of DC battery cabinets through the cloud passive state-of-charge calibration strategy.

[0069] In this embodiment, when the current calibrated time of multiple clusters of DC battery cabinets is lower than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets is greater than the preset duration, the terminal performs a state-of-charge calibration process on multiple clusters of DC battery cabinets through the cloud passive state-of-charge calibration strategy. Specifically, for example, after multiple clusters of DC battery cabinets complete the last calibration, the summary list updates the calibration time and resets this calibration time to zero. Then, when it is determined that the current swing time is less than 14 * 24 hours (i.e., the current calibrated time of multiple clusters of DC battery cabinets is lower than the preset time threshold), the SOC is less than 30% (the state of charge of the battery clusters is the preset state of charge), and it has been stationary for more than 1 hour (the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets is greater than the preset duration), the terminal performs a state-of-charge calibration process on multiple clusters of DC battery cabinets through the cloud passive state-of-charge calibration strategy. Specifically, the calibration process of the cloud passive state-of-charge calibration strategy will be described in detail later.

[0070] Step S203: When the current calibrated time of multiple clusters of DC battery cabinets is higher than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the duration for maintaining the state of charge of the battery clusters of multiple clusters of DC battery cabinets is greater than the preset duration, perform a state-of-charge calibration process on multiple clusters of DC battery cabinets through the active state-of-charge calibration strategy.

[0071] In this embodiment, when the current calibration time of the multi-cluster DC battery cabinet is higher than the preset time threshold, the state of charge of the battery cluster is the preset state of charge, and the duration for maintaining the state of charge of the multi-cluster DC battery cabinet is greater than the preset duration (i.e., conditions completely opposite to the judgment conditions of the cloud passive state of charge calibration strategy), the terminal performs state of charge calibration processing on the multi-cluster DC battery cabinet through the active state of charge calibration strategy. Specifically, the calibration process of the active state of charge calibration strategy will be described in detail later.

[0072] Step S204, after completing the calibration process, update the state of charge of the battery clusters in the multi-cluster DC battery cabinet and the duration for maintaining the state of charge of the multi-cluster DC battery cabinet.

[0073] In this embodiment, after the terminal completes the calibration process, it updates the state of charge of the battery clusters in the multi-cluster DC battery cabinet and the duration for maintaining the state of charge of the multi-cluster DC battery cabinet. Among them, updating the state of charge of the battery pack is the process of re-calibrating the state of charge of each battery cabinet, and the process of updating the duration for maintaining the state of charge of the multi-cluster DC battery cabinet is to zero the duration for maintaining the state of charge of each battery cabinet and then recalculate the duration.

[0074] Based on the above solution, through the active calibration method and the cloud passive state of charge calibration strategy, the state of charge calibration is carried out respectively under different states of charge of the battery cluster and different durations for maintaining the state of charge, so as to ensure that the state of charge calibration can be carried out under any state conditions of the battery cluster. And this solution designs different battery state calculation methods for different states of the battery cluster, thus greatly reducing the SOC calculation error under the condition of multi-cluster battery parallel connection and improving the SOC calibration accuracy under the condition of multi-cluster battery parallel connection.

[0075] Optionally, performing state of charge calibration processing on the multi-cluster DC battery cabinet through the cloud passive state of charge calibration strategy includes: obtaining the full battery data of the multi-cluster DC battery cabinet in the whole time period, and judging whether the multi-cluster DC battery cabinet meets the state of charge calibration conditions based on the current full battery data; when the multi-cluster DC battery cabinet meets the state of charge calibration conditions, calculating the current state of charge of the multi-cluster DC battery cabinet through the state of charge recognition model based on the current full battery data; sending the current state of charge to the local state calibration unit in the way of cloud distribution, and performing state of charge calibration processing on the multi-cluster DC battery cabinet through the local state calibration unit based on the current state of charge.

[0076] In this embodiment, the terminal obtains the full battery data of multiple clusters of DC battery cabinets at all times, and based on the current full battery data, determines whether the multiple clusters of DC battery cabinets meet the state of charge calibration conditions. Among them, the full battery data at all times includes the full battery data collected from the white battery at each collection time point. Among them, the full battery data includes but is not limited to the battery voltage value, battery current value, and battery temperature value of each battery cabinet. Specifically, it includes but is not limited to battery data such as the maximum voltage, maximum cell temperature, minimum cell temperature, number of closed contactor clusters, and minimum cluster continuous charging current. The specific judgment process will be described in detail later.

[0077] Then, when the multiple clusters of DC battery cabinets meet the state of charge calibration conditions, the terminal calculates the current state of charge of the multiple clusters of DC battery cabinets based on the current full battery data through the state of charge recognition model. Among them, the state of charge recognition model is a time series prediction model obtained by training a large amount of sample data based on the established GRU network structure.

[0078] After that, the terminal sends the current state of charge to the local state calibration unit in the way of cloud distribution, and based on the current state of charge, the local state calibration unit performs state of charge calibration processing on the multiple clusters of DC battery cabinets.

[0079] Based on the above solution, through the cloud passive calibration method, the state of charge of the battery can be accurately calculated under the low state of charge of the battery, thus ensuring the calibration accuracy of the multiple parallel-connected battery cabinets under the low state of charge of the battery.

[0080] Optionally, determining whether the multiple clusters of DC battery cabinets meet the state of charge calibration conditions based on the current full battery data includes: identifying the battery voltage value of the multiple clusters of DC battery cabinets, the battery current value of the multiple clusters of DC battery cabinets, and the battery temperature value of the multiple clusters of DC battery cabinets based on the full battery data; training the initial state of charge recognition model based on the battery voltage value, battery current value, and battery temperature value, and when the number of training times of the initial state of charge recognition model is lower than the preset number of training times, return to execute the step of obtaining the current full battery data of the multiple clusters of DC battery cabinets; when the number of training times of the initial state of charge recognition model is not lower than the preset number of training times, use the initial state of charge recognition model obtained in the last iteration as the target state of charge recognition model, and determine that the multiple clusters of DC battery cabinets meet the state of charge calibration conditions.

[0081] In this embodiment, the terminal identifies the battery voltage values of multiple clusters of DC battery cabinets, the battery current values of multiple clusters of DC battery cabinets, and the battery temperature values of multiple clusters of DC battery cabinets based on the full battery data. Then, the terminal trains the initial state of charge (SOC) recognition model based on the battery voltage values, battery current values, and battery temperature values, and when the number of training times of the initial SOC recognition model is lower than the preset number of training times, it returns to execute the step of obtaining the current full battery data of multiple clusters of DC battery cabinets. Among them, when training the model, after the terminal obtains the full battery data, it also needs to obtain the SOC of the multiple clusters of DC battery cabinets calibrated when each full battery data is collected. Then, based on the SOC and the full battery data, the model is trained. Wherein, the preset number of training times is the number of training times preset by the staff on the terminal. Since the time series prediction model is trained by using the full battery data of the multiple clusters of DC battery cabinets collected over the entire period, the SOC of the multiple clusters of DC battery cabinets can be effectively identified.

[0082] When the number of training times of the initial SOC recognition model is not lower than the preset number of training times, the terminal uses the initial SOC recognition model obtained in the last iteration as the target SOC recognition model, and determines that the multiple clusters of DC battery cabinets meet the SOC calibration condition. Wherein, the SOC calibration condition is the preset number of training times.

[0083] Based on the above solution, by means of collecting while training, the recognition accuracy and comprehensiveness of the target SOC recognition model are optimized in real time.

[0084] Optionally, the SOC calibration process for multiple clusters of DC battery cabinets is performed through an active SOC calibration strategy, including: randomly selecting a target single cluster of batteries in the multiple clusters of DC battery cabinets and disconnecting the battery scheduling response mode of the target single cluster of batteries; controlling the target single cluster of batteries to be powered on through the power-on control unit, and when the highest single-cell voltage of the target single cluster of batteries reaches the full charge calibration voltage threshold, replacing the current SOC of the target single cluster of batteries with a preset SOC calibration value to obtain the new SOC of the target single cluster of batteries; performing SOC calibration processing on the target single cluster of batteries based on the new SOC and restoring the battery scheduling response mode of the target single cluster of batteries; reselecting the target single cluster of batteries that have not been selected as the target single cluster of batteries in the multiple clusters of DC battery cabinets and returning to execute the step of disconnecting the battery scheduling response mode of the target single cluster of batteries until it is determined that the SOC calibration process of all single clusters of batteries is completed, and determining that the SOC calibration process of the multiple clusters of DC battery cabinets is completed.

[0085] In this embodiment, the terminal randomly selects a target single cluster of batteries from multiple clusters of DC battery cabinets and cuts off the battery scheduling response mode of the target single cluster of batteries. The purpose of cutting off the battery scheduling response mode of the target single cluster of batteries is to calibrate the state of charge (SOC) of the target single cluster of batteries offline, avoiding the problem of low accuracy in calibrating the SOC due to the battery scheduling response. This improves the accuracy of calibrating the SOC of the target single cluster of batteries.

[0086] Then, the terminal controls the target single cluster of batteries to be powered on through the power-on control unit. When the highest single-cell voltage of the target single cluster of batteries reaches the full charge calibration voltage threshold, based on the preset SOC calibration value, the current SOC of the target single cluster of batteries is replaced to obtain the new SOC of the target single cluster of batteries. The specific power-on process will be described in detail later, and the full charge calibration voltage threshold is a voltage threshold preset by the staff in the terminal, which is used to determine the end moment of battery charging.

[0087] After that, the terminal performs SOC calibration processing on the target single cluster of batteries based on the new SOC and restores the battery scheduling response mode of the target single cluster of batteries. The restoration of the battery scheduling response mode is to restore the normal operation process of the target single cluster of batteries, so that the calibrated single cluster of batteries can still operate normally. After that, the terminal re-selects the target single cluster of batteries that have not been selected as the target single cluster of batteries in the multiple clusters of DC battery cabinets and returns to execute the step of cutting off the battery scheduling response mode of the target single cluster of batteries until it is determined that all single cluster of batteries have completed the SOC calibration processing, and it is determined that the multiple clusters of DC battery cabinets have completed the SOC calibration processing. The above method is to perform battery calibration on each single cluster of batteries separately. Moreover, by powering on the battery for battery calibration, each battery has an SOC value of 100% after calibration. This ensures the calibration accuracy of multiple clusters of batteries and can also charge the batteries, avoiding the problem that a low SOC affects the normal operation of the batteries.

[0088] Based on the above solution, through the battery calibration process after power-on, while ensuring the calibration accuracy of the multiple clusters of battery cabinets, the service life of the batteries and the progress of maintaining the normal operation state are improved.

[0089] Optionally, before replacing the current state of charge of the target single cluster battery with a new state of charge based on a preset state of charge calibration value, it further includes: identifying the minimum continuous charge value of the target single cluster battery based on the battery specification information of the target single cluster battery, and performing continuous charging processing on the target single cluster battery through the power-on control unit based on the minimum continuous charge value; detecting the current battery voltage value of the target single cluster battery, and when the current battery voltage value is lower than the full charge calibration voltage threshold, returning to execute the step of detecting the current battery voltage value of the target single cluster battery until the current battery voltage value is equal to the full charge calibration voltage threshold, and determining that the highest single cell voltage of the target single cluster battery reaches the full charge calibration voltage threshold.

[0090] In this embodiment, the terminal identifies the minimum continuous charge value of the target single cluster battery based on the battery specification information of the target single cluster battery, and performs continuous charging processing on the target single cluster battery through the power-on control unit based on the minimum continuous charge value. Among them, before the charging starts, the terminal checks the continuous charging ammeter based on the two conditions of the maximum voltage and the maximum cell temperature, and the maximum voltage and the minimum cell temperature of the cell. Output the current available continuous charging current value, and take the minimum of the two. The continuous charging current value of the stack output by the SCU = the number of closed contactor clusters * the minimum continuous charging current of the cluster; since the PCS power control is set by the EMS, it is necessary to upload the continuous charging current value of the stack output by the SCU to the EMS through Ethernet communication. The EMS sets the PCS charging power according to the cell SOP and starts charging, effectively ensuring the service life of the battery.

[0091] Among them, after the charging process starts, it combines the Ah integration and the full charge voltage calibration strategy. The calculation method of Ah integration is as follows:

[0092] After power-on, the terminal reads the cumulative charge capacity InitChrgCapAh and the cumulative discharge capacity InitDchaCapAh at the current moment; then, the terminal calculates the capacity change DeltaCap during the charge and discharge process (negative for charging and positive for discharging), and the calculation formula is as follows:

[0093]

[0094] Among them, calculate △SOC:

[0095]

[0096] The terminal iteratively calculates the SOC of all cells based on the Ah integration according to the following formula:

[0097]

[0098] When the highest single cell voltage is charged to the full charge calibration threshold, the terminal calibrates the SOC of the target single cluster battery to 100%.

[0099] Then, the terminal detects the current battery voltage value of the target single-cluster battery. When the current battery voltage value is lower than the full charge calibration voltage threshold, it returns to execute the step of detecting the current battery voltage value of the target single-cluster battery until the current battery voltage value is equal to the full charge calibration voltage threshold, and determines that the highest single-cell voltage of the target single-cluster battery reaches the full charge calibration voltage threshold. Specifically, when the SOC of the target battery cluster is charged to 100%, the SCU sets the stack request charging current = 0, updates and uploads it to the EMS. The EMS controls the PCS to switch to standby, and the SCU issues a power-down command to the cluster with SOC of 100% to complete the full charge calibration and exit the charging state.

[0100] Based on the above solution, by calculating the capacity change during the charge and discharge process, the accuracy of the full charge calibration of the target single-cluster battery is identified.

[0101] Optionally, updating the state of charge of the battery clusters in the multi-cluster DC battery cabinet and the duration of maintaining the state of charge of the battery clusters in the multi-cluster DC battery cabinet includes: identifying the current state of charge of the multi-cluster DC battery cabinet, and replacing the state of charge of the battery clusters in the multi-cluster DC battery cabinet with the current state of charge; resetting the duration of maintenance to zero to complete the update task of the duration of maintaining the state of charge of the battery clusters in the multi-cluster DC battery cabinet.

[0102] In this embodiment, the terminal identifies the current state of charge of the multi-cluster DC battery cabinet, and replaces the state of charge of the battery clusters in the multi-cluster DC battery cabinet with the current state of charge. Then, the terminal resets the duration of maintenance to zero to complete the update task of the duration of maintaining the state of charge of the battery clusters in the multi-cluster DC battery cabinet.

[0103] Based on the above solution, by updating the state of charge of the battery clusters and the duration of maintenance, the real-time analysis efficiency of the state of charge of the battery clusters in the multi-cluster DC battery cabinet is improved, and the accuracy of identification when the state of charge of the battery clusters is identified again later is ensured.

[0104] This application also provides an example of calibrating the state of charge of a battery, as Figure 3 shown. The specific processing process includes the following steps:

[0105] Step S301, obtain the state of charge of the battery clusters in the multi-cluster DC battery cabinet, the duration of maintaining the state of charge of the battery clusters in the multi-cluster DC battery cabinet, and the current calibration time of the multi-cluster DC battery cabinet.

[0106] Step S302, obtain the full battery data of the multi-cluster DC battery cabinet during the entire period.

[0107] Step S303 , based on the battery full quantity data, identifying the battery voltage values ​​of the multiple-cluster DC battery cabinets, the battery current values ​​of the multiple-cluster DC battery cabinets, and the battery temperature values ​​of the multiple-cluster DC battery cabinets.

[0108] Step S304, based on the battery voltage value, the battery current value, and the battery temperature value, the initial state of charge recognition model is trained, and when the number of training times of the initial state of charge recognition model is less than the preset number of training times, the step of obtaining the current full battery data of the multi-cluster DC battery cabinet is returned to.

[0109] Step S305, when the training times of the initial state of charge recognition model is not less than the preset training times, the initial state of charge recognition model obtained by the last iteration is used as the target state of charge recognition model, and it is determined that the multi-cluster DC battery cabinet meets the state of charge calibration condition.

[0110] Step S306, when the multi-cluster DC battery cabinet meets the charge state calibration condition, the current charge state of the multi-cluster DC battery cabinet is calculated based on the current battery full quantity data through the charge state recognition model.

[0111] Step S307, the current state of charge is sent to the local state calibration unit through the cloud, and based on the current state of charge, the local state calibration unit performs charge state calibration processing on the multiple clusters of DC battery cabinets.

[0112] Step S308: randomly select a target single cluster of batteries in the multi-cluster DC battery cabinet, and isolate the battery scheduling response mode of the target single cluster of batteries.

[0113] Step S309: Control the target battery cluster to perform power-on processing through the power-on control unit.

[0114] Step S310 , based on the battery specification information of the target battery cluster, identifying the minimum continuous charging value of the target battery cluster, and performing continuous charging processing on the target battery cluster through the power-on control unit based on the minimum continuous charging value.

[0115] Step S311, detecting the current battery voltage value of the target single-cluster battery, and when the current battery voltage value is lower than the full calibration voltage threshold, returning to the step of detecting the current battery voltage value of the target single-cluster battery, until the current battery voltage value is equal to the full calibration voltage threshold, determining that the highest single cell voltage of the target single-cluster battery reaches the full calibration voltage threshold.

[0116] Step S312 , when the highest cell voltage of the target battery cluster reaches the full charge calibration voltage threshold, the current state of charge of the target battery cluster is replaced based on the preset state of charge calibration value to obtain a new state of charge of the target battery cluster.

[0117] Step S313: Based on the new state of charge, perform state-of-charge calibration processing on the target single cluster battery, and restore the battery scheduling response mode of the target single cluster battery.

[0118] Step S314: In the multi-cluster DC battery cabinet, re-screen the target single cluster batteries that have not been screened as the target single cluster battery, and return to execute the step of cutting off the battery scheduling response mode of the target single cluster battery until it is determined that the multi-cluster DC battery cabinet has completed the state-of-charge calibration processing when all single cluster batteries have completed the state-of-charge calibration processing.

[0119] Step S315: Identify the current state of charge of the multi-cluster DC battery cabinet, and replace the state of charge of the battery cluster of the multi-cluster DC battery cabinet with the current state of charge.

[0120] Step S316: Reset the maintenance duration to complete the update task of the maintenance duration of the multi-cluster DC battery cabinet in the state of charge of the battery cluster.

[0121] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0122] Based on the same inventive concept, the embodiments of the present application also provide a device for calibrating the state of charge of a battery for implementing the method for calibrating the state of charge of a battery involved above. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the device for calibrating the state of charge of a battery provided below can refer to the limitations on the method for calibrating the state of charge of a battery in the above text, and will not be repeated here.

[0123] In an exemplary embodiment, as Figure 4 shown, a device for calibrating the state of charge of a battery is provided, including: an acquisition module 410, a first calibration module 420, a second calibration module 430, and an update module 440, where:

[0124] An acquisition module 410, configured to acquire the state of charge of battery clusters of a multi-cluster DC battery cabinet, the duration for which the multi-cluster DC battery cabinet maintains the state of charge of the battery clusters, and the current calibration time of the multi-cluster DC battery cabinet;

[0125] A first calibration module 420, configured to perform a state of charge calibration process on the multi-cluster DC battery cabinet through a cloud passive state of charge calibration strategy when the current calibration time of the multi-cluster DC battery cabinet is lower than a preset time threshold, the state of charge of the battery clusters is a preset state of charge, and the duration for which the multi-cluster DC battery cabinet maintains the state of charge of the battery clusters is greater than a preset duration;

[0126] A first calibration module 430, configured to perform a state of charge calibration process on the multi-cluster DC battery cabinet through an active state of charge calibration strategy when the current calibration time of the multi-cluster DC battery cabinet is higher than the preset time threshold, the state of charge of the battery clusters is the preset state of charge, and the duration for which the multi-cluster DC battery cabinet maintains the state of charge of the battery clusters is greater than the preset duration;

[0127] An update module 440, configured to update the state of charge of the battery clusters of the multi-cluster DC battery cabinet and the duration for which the multi-cluster DC battery cabinet maintains the state of charge of the battery clusters after the calibration process is completed.

[0128] Optionally, the first calibration module 420 is specifically configured to:

[0129] Acquire the full battery data of the multi-cluster DC battery cabinet over the entire period, and based on the current full battery data, determine whether the multi-cluster DC battery cabinet meets the state of charge calibration conditions;

[0130] When the multi-cluster DC battery cabinet meets the state of charge calibration conditions, calculate the current state of charge of the multi-cluster DC battery cabinet through a state of charge recognition model based on the current full battery data;

[0131] Send the current state of charge to the local state calibration unit in a manner of being sent from the cloud, and perform a state of charge calibration process on the multi-cluster DC battery cabinet through the local state calibration unit based on the current state of charge.

[0132] Optionally, the first calibration module 420 is specifically configured to:

[0133] Based on the full battery data, identify the battery voltage value of the multi-cluster DC battery cabinet, the battery current value of the multi-cluster DC battery cabinet, and the battery temperature value of the multi-cluster DC battery cabinet;

[0134] Based on the battery voltage value, the battery current value, and the battery temperature value, train the initial state of charge recognition model, and when the number of training times of the initial state of charge recognition model is lower than the preset number of training times, return to execute the step of obtaining the current full battery data of multiple clusters of DC battery cabinets;

[0135] When the number of training times of the initial state of charge recognition model is not lower than the preset number of training times, take the initial state of charge recognition model obtained in the last iteration as the target state of charge recognition model, and determine that the multiple clusters of DC battery cabinets meet the state of charge calibration conditions.

[0136] Optionally, the second calibration module 430 is specifically configured to:

[0137] Randomly select a target single cluster of batteries in multiple clusters of DC battery cabinets, and cut off the battery scheduling response mode of the target single cluster of batteries;

[0138] Through the power-on control unit, control the target single cluster of batteries to perform power-on processing, and when the highest single-cell voltage of the target single cluster of batteries reaches the full charge calibration voltage threshold, replace the current state of charge of the target single cluster of batteries based on the preset state of charge calibration value to obtain the new state of charge of the target single cluster of batteries;

[0139] Based on the new state of charge, perform state of charge calibration processing on the target single cluster of batteries, and restore the battery scheduling response mode of the target single cluster of batteries;

[0140] In the multiple clusters of DC battery cabinets, re-select the target single cluster of batteries that have not been selected as the target single cluster of batteries, and return to execute the step of cutting off the battery scheduling response mode of the target single cluster of batteries until it is determined that all single clusters of batteries have completed the state of charge calibration processing, and determine that the multiple clusters of DC battery cabinets have completed the state of charge calibration processing.

[0141] Optionally, the device further includes:

[0142] A power-on module, configured to identify the minimum continuous charge value of the target single cluster of batteries based on the battery specification information of the target single cluster of batteries, and based on the minimum continuous charge value, perform continuous charge processing on the target single cluster of batteries through the power-on control unit;

[0143] A detection module, configured to detect the current battery voltage value of the target single cluster of batteries, and when the current battery voltage value is lower than the full charge calibration voltage threshold, return to execute the step of detecting the current battery voltage value of the target single cluster of batteries until the current battery voltage value is equal to the full charge calibration voltage threshold, and determine that the highest single-cell voltage of the target single cluster of batteries reaches the full charge calibration voltage threshold.

[0144] Optionally, the update module 440 is specifically configured to:

[0145] Identify the current state of charge of the multi-cluster DC battery cabinet, and replace the state of charge of the battery cluster of the multi-cluster DC battery cabinet with the current state of charge;

[0146] Reset the duration to zero to complete the update task of the duration for maintaining the multi-cluster DC battery cabinet in the state of charge of the battery cluster.

[0147] Each module in the above device for calibrating the state of charge of the battery can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0148] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as Figure 5 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals in a wired or wireless manner. The wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. The computer program, when executed by the processor, implements a method for calibrating the state of charge of a battery. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0149] Those skilled in the art can understand, Figure 5The structure shown is only a block diagram of some of the structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component arrangement.

[0150] In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps of the method described in any one of the first aspects are implemented.

[0151] In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0152] In an embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of the method described in any one of the first aspects are implemented.

[0153] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0154] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0155] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0156] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for calibrating a battery state of charge, characterized in that: The method comprises: Acquire the battery cluster charge state of a multi-cluster DC battery cabinet, the duration for which the multi-cluster DC battery cabinet is in the battery cluster charge state, and the current calibration time of the multi-cluster DC battery cabinet; When the current calibration time of the multi-cluster DC battery cabinet is lower than the preset time threshold, the battery cluster state of charge is the preset state of charge, and the maintenance time of the multi-cluster DC battery cabinet in the battery cluster state of charge is longer than the preset time, the multi-cluster DC battery cabinet is calibrated for the state of charge through the cloud-based passive state of charge calibration strategy; After the calibration process is completed, the battery cluster charge states of the multi-cluster DC battery cabinet and the duration for which the multi-cluster DC battery cabinet is in the battery cluster charge state are updated.

2. The method according to claim 1, characterized in that The method of performing charge state calibration processing on the multi-cluster DC battery cabinet by using a cloud-based passive charge state calibration strategy includes: Obtaining full battery data of a multi-cluster DC battery cabinet at all times, and judging whether the multi-cluster DC battery cabinet meets a charge state calibration condition based on the current full battery data; When the multi-cluster DC battery cabinet meets the charge state calibration condition, based on the current battery full quantity data, the current charge state of the multi-cluster DC battery cabinet is calculated by a charge state identification model; The current state of charge is sent to a local state calibration unit via the cloud, and based on the current state of charge, the state of charge calibration process is performed on the multi-cluster DC battery cabinet via the local state calibration unit.

3. The method according to claim 2, characterized in that The determining, based on the current full battery data, whether the multi-cluster DC battery cabinet meets the state of charge calibration condition includes: Based on the battery full quantity data, identifying the battery voltage value of the multi-cluster DC battery cabinet, the battery current value of the multi-cluster DC battery cabinet, and the battery temperature value of the multi-cluster DC battery cabinet; Based on the battery voltage value, the battery current value, and the battery temperature value, an initial state of charge recognition model is trained, and when the number of training times of the initial state of charge recognition model is less than a preset number of training times, returning to execute the step of obtaining current full battery data of the multi-cluster DC battery cabinet; When the training times of the initial state of charge recognition model is not less than the preset training times, the initial state of charge recognition model obtained by the last iteration is used as the target state of charge recognition model, and it is determined that the multi-cluster DC battery cabinet meets the state of charge calibration condition.

4. The method according to claim 1, characterized in that Before replacing the current state of charge of the target single-cluster battery based on the preset state of charge calibration value to obtain a new state of charge of the target single-cluster battery, the method further includes: Based on the battery specification information of the target single-cluster battery, identifying the minimum continuous charging value of the target single-cluster battery, and based on the minimum continuous charging value, performing continuous charging processing on the target single-cluster battery through the power-on control unit; The current battery voltage value of the target single-cluster battery is detected, and when the current battery voltage value is lower than the full calibration voltage threshold, the step of returning to the step of detecting the current battery voltage value of the target single-cluster battery is executed until the current battery voltage value is equal to the full calibration voltage threshold, and it is determined that the highest single cell voltage of the target single-cluster battery reaches the full calibration voltage threshold.

5. The method according to claim 1, characterized in that The updating of the battery cluster charge state of the multi-cluster DC battery cabinet and the duration for which the multi-cluster DC battery cabinet is in the battery cluster charge state includes: Identifying a current state of charge of the multi-cluster DC battery cabinet, and replacing the battery cluster state of charge of the multi-cluster DC battery cabinet with the current state of charge; The maintenance time is reset to zero, completing the task of updating the maintenance time of the multi-cluster DC battery cabinet in the battery cluster charge state.

6. A battery state of charge calibration device, characterized in that: The device comprises: An acquisition module, used to acquire the battery cluster charge state of a multi-cluster DC battery cabinet, the duration for which the multi-cluster DC battery cabinet is in the battery cluster charge state, and the current calibration time of the multi-cluster DC battery cabinet; A first calibration module is used to perform a state of charge calibration process on the multi-cluster DC battery cabinet through a cloud-based passive state of charge calibration strategy when the current calibration time of the multi-cluster DC battery cabinet is lower than a preset time threshold, the state of charge of the battery cluster is a preset state of charge, and the maintenance time of the multi-cluster DC battery cabinet in the battery cluster state of charge is greater than a preset time; The updating module is used to update the battery cluster charge state of the multi-cluster DC battery cabinet and the maintenance time of the multi-cluster DC battery cabinet in the battery cluster charge state after completing the calibration process.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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