Method, device, system and electronic equipment for determining battery state of charge

Abstract

The application discloses a battery state of charge determination method, device, system and electronic equipment, and belongs to the technical field of batteries. The method comprises the following steps: in the case that the state of charge of a battery reaches a target correction point, the battery is controlled to enter a target working condition, so that the battery appears a step response, the target working condition is that charging operations, discharging operations and standing operations with different charging rates are performed on the battery for multiple times; and the state of charge of the battery in the target working condition is obtained according to a Kalman filtering method. The method sets the target correction point, performs the target working condition to make the battery appear the step response, can overcome the limitation that the Kalman filtering method has low estimation accuracy when current and voltage parameters do not change, can also correct and compensate accumulated errors caused by long-time online estimation of other state of charge estimation methods, and improves the accuracy and precision of state of charge estimation.

Description

Technical Field

[0001] This application belongs to the field of battery technology, and in particular relates to a method, apparatus, system and electronic device for determining the state of charge of a battery. Background Technology

[0002] Accurate estimation of the battery's state of charge (SOC) is fundamental to ensuring the proper operation of an energy storage system. An accurate SOC can also prevent overcharging and over-discharging, thus extending battery life.

[0003] With the increasing variety of battery types, strategies for estimating the state of charge (SOC) are also becoming more diverse. A single estimation method is typically only applicable to specific operating conditions. For example, the ampere-hour integration method has good short-term estimation accuracy, but long-term application leads to cumulative errors, reducing estimation accuracy. Existing estimation methods have significant limitations, cannot adapt to the SOC estimation of different batteries, and result in low accuracy. Summary of the Invention

[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method, apparatus, system, and electronic device for determining the state of charge of a battery, improving the accuracy of state of charge estimation, and applicable to different types of batteries.

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

[0006] When it is determined that the state of charge of the battery has reached the target correction point, the battery is controlled to enter the target operating condition, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations and resting operations with different charge and discharge rates on the battery.

[0007] The state of charge of the battery under the target operating condition is determined using the Kalman filter method.

[0008] According to the method for determining the state of charge of a battery in this application, by setting a target correction point and executing a target operating condition to make the battery exhibit a step response, the limitation of low estimation accuracy of the Kalman filter method when the current and voltage parameters do not change can be overcome. It can also correct and compensate for the errors caused by long-term online estimation of other state of charge estimation methods, thereby improving the accuracy and precision of state of charge estimation.

[0009] According to one embodiment of this application, the method further includes:

[0010] If it is determined that the state of charge of the battery has not reached the target correction point, the state of charge of the battery is determined according to the ampere-hour integration method.

[0011] According to one embodiment of this application, the state of charge of the battery includes at least two target correction points throughout the entire cycle, and the state of charge difference between two adjacent target correction points is the target state of charge difference.

[0012] According to one embodiment of this application, the charge / discharge rate corresponding to the target operating condition is determined based on the charge / discharge capacity of the battery under the actual operating conditions of the current operating mode.

[0013] According to one embodiment of this application, the battery is a type II energy storage battery. The step of controlling the battery to enter the target operating condition after determining that the battery's state of charge has reached the target correction point includes:

[0014] When it is determined that the battery is in a plateau period and the state of charge of the battery has reached the target correction point, the battery is controlled to enter the target operating condition.

[0015] According to one embodiment of this application, determining that the battery is in a plateau phase includes:

[0016] Obtain the voltage change rate of the battery;

[0017] If the voltage change rate is less than a first threshold, the battery is determined to be in the plateau period.

[0018] According to one embodiment of this application, the battery is a type II energy storage battery, and the method further includes:

[0019] If it is determined that the battery is in a plateau period and the battery's state of charge has not reached the target correction point, the battery's state of charge is determined according to the ampere-hour integration method.

[0020] According to one embodiment of this application, the battery is a type II energy storage battery, and the method further includes:

[0021] If the battery is determined to be in a non-plateau period, the state of charge of the battery in the non-plateau period is obtained according to the Kalman filter method.

[0022] Secondly, this application provides a device for determining the state of charge of a battery, the device comprising:

[0023] The first processing module is used to control the battery to enter a target operating condition when it is determined that the battery's state of charge has reached the target correction point, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations, and resting operations on the battery at different charge and discharge rates.

[0024] The second processing module is used to determine the state of charge of the battery under the target operating condition according to the Kalman filter method.

[0025] Thirdly, this application provides a system for determining the state of charge of a battery, comprising:

[0026] The system includes a battery, a data acquisition and control module, and an edge computing module, wherein the battery is connected to the data acquisition and control module, and the data acquisition and control module is connected to the edge computing module.

[0027] The acquisition and control module is used to acquire the current and voltage data of the battery operation and transmit the current and voltage data of the battery operation to the edge computing module;

[0028] The edge computing module is used to calculate the state of charge of the battery based on the current and voltage data of the battery operation, and to feed back the calculation result of the state of charge of the battery to the acquisition and control module.

[0029] The acquisition and control module is used to control the battery to perform a target operating condition when it is determined that the state of charge of the battery has reached the target correction point, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations and resting operations with different charge and discharge rates on the battery. The edge computing module is used to determine the state of charge of the battery under the target operating condition according to the Kalman filtering method.

[0030] Fourthly, this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for determining the state of charge of a battery as described in the first aspect above.

[0031] Fifthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining the state of charge of a battery as described in the first aspect above.

[0032] In a sixth aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining the state of charge of a battery as described in the first aspect above.

[0033] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0034] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0035] Figure 1 This is one of the flowcharts illustrating the method for determining the state of charge of a battery provided in the embodiments of this application;

[0036] Figure 2 This is a second schematic flowchart of the method for determining the state of charge of a battery provided in the embodiments of this application;

[0037] Figure 3 This is a schematic diagram of the current and voltage response of the battery under target operating conditions provided in the embodiments of this application;

[0038] Figure 4 This is a schematic diagram of the stages of the method for determining the state of charge of a battery provided in the embodiments of this application;

[0039] Figure 5 This is a schematic diagram of the structure of the battery state of charge determination device provided in the embodiments of this application;

[0040] Figure 6 This is a schematic diagram of the structure of the battery state of charge determination system provided in the embodiments of this application;

[0041] Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0043] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0044] The following description, in conjunction with the accompanying drawings, details the method for determining the state of charge of a battery, the apparatus for determining the state of charge of a battery, the electronic device, and the readable storage medium provided in the embodiments of this application through specific implementations and application scenarios.

[0045] The method for determining the state of charge of the battery can be applied to the terminal, and can be executed by the hardware or software in the terminal.

[0046] The terminal includes, but is not limited to, portable communication devices such as mobile phones or tablets with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but rather a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).

[0047] The following embodiments describe a terminal including a display and a touch-sensitive surface. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, mouse, and joystick.

[0048] The state of charge (SOC) of a battery is a parameter used to characterize the remaining capacity of a battery.

[0049] In a type of energy storage battery represented by ternary lithium batteries, the battery's operating voltage and state of charge have a linear relationship, and there is a unique mapping relationship between the operating voltage and the state of charge.

[0050] In the second type of energy storage battery, represented by lithium iron phosphate batteries, the battery's operating voltage has a non-linear relationship with its state of charge. The battery's operating voltage has a plateau period, meaning that the operating voltage or current corresponding to different states of charge of the battery remains unchanged.

[0051] Estimating the state of charge (SOC) of batteries is an essential key technology for energy storage systems. The main methods for SOC estimation are as follows:

[0052] I. Integral method using ampere-hours.

[0053] The state of charge (SOC) is estimated by integrating instantaneous current. Instantaneous current data can be obtained directly, and the short-term estimation accuracy is good. However, due to the influence of sampling error, there is a cumulative error in long-term application, which causes the estimated SOC value to gradually deviate. Moreover, it is not possible to accurately estimate the SOC value of each battery in a series battery pack. This method can be used for Class I and Class II energy storage batteries.

[0054] II. Kalman Filtering.

[0055] The state of charge (SOC) is estimated using the Kalman filter algorithm based on battery current and voltage data. This method effectively eliminates the interference of sampling errors and random errors based on the ampere-hour integration method, resulting in high diagnostic accuracy. This method works well for Class I energy storage batteries. However, for Class II energy storage batteries, the voltage and current values ​​do not change during the plateau period, and there is no information disturbance update, which makes the Kalman filter unable to estimate effectively, resulting in reduced accuracy.

[0056] Based on the above analysis, it can be seen that the Kalman filter algorithm has a high accuracy in estimating the SOC of Type I batteries. For Type II batteries, due to the special characteristic that the current and voltage parameters do not change during the plateau period, the ampere-hour integration method has the limitation of cumulative error and is only suitable for short-term estimation. The Kalman filter requires changing parameter values ​​to effectively estimate recursively, which also has certain limitations.

[0057] Existing estimation methods have significant limitations, cannot adapt to the state of charge estimation of different batteries, and have low accuracy.

[0058] The battery state of charge determination method provided in this application can overcome the limitations of existing state of charge estimation methods and achieve accurate online state of charge estimation for all types of energy storage batteries.

[0059] The method for determining the state of charge of a battery provided in this application embodiment can be executed by an electronic device or a functional module or entity in an electronic device that can implement the method for determining the state of charge of a battery. The electronic devices mentioned in this application embodiment include, but are not limited to, mobile phones, tablets, computers, cameras, and wearable devices. The method for determining the state of charge of a battery provided in this application embodiment will be described below using an electronic device as the execution subject.

[0060] like Figure 1 As shown, the method for determining the state of charge of the battery includes steps 110 and 120.

[0061] Step 110: Once it is determined that the battery's state of charge has reached the target correction point, control the battery to enter the target operating condition.

[0062] In this embodiment, the battery can be a type I energy storage battery or a type II energy storage battery, and the target correction point is a preset state of charge value.

[0063] For example, the target correction points set for the battery include points with a state of charge (SOC) of 10%, 20%, 30%, and 40%. When the SOC of the battery reaches the SOC value of the target correction point, the battery is controlled to enter the target operating condition, causing the battery to exhibit a step response and estimating the current accurate SOC of the battery.

[0064] In some embodiments, the battery is a type II energy storage battery, and step 110 may include:

[0065] Once it is determined that the battery is in a plateau phase and the battery's state of charge has reached the target correction point, the battery is controlled to enter the target operating condition.

[0066] Among them, the battery can be a type II energy storage battery with a plateau period. When the battery is in the plateau period, its operating voltage or current remains unchanged.

[0067] A target correction point is set during the battery's plateau period. At the target correction point, the battery is controlled to enter the target operating condition, causing the battery to exhibit a step response, in order to measure and estimate the battery's current state of charge.

[0068] The target operating conditions involve performing multiple charging, discharging, and resting operations on the battery at different charge / discharge rates.

[0069] In this embodiment, the target operating condition includes multiple charging operations, discharging operations, and resting operations with different charge-discharge rates, providing a dynamic operating condition with continuously changing charge-discharge rates, which causes significant step response changes in the operating voltage and current of a type I energy storage battery or a type II energy storage battery in a plateau period.

[0070] In practice, the target operating condition can be a simplified version of the Federal Urban Driving Schedule (FUDS) dynamic stress test (DST), which is a standard operating condition for testing the charge and discharge characteristics of a battery under dynamic conditions.

[0071] The DST operating condition is characterized by repeatedly charging, discharging, and resting the battery at different rates within a short period of time to obtain rapid step response changes in the battery current and voltage parameters.

[0072] For example, such as Figure 3 As shown, under DST conditions, the battery's current and voltage exhibit a step-like response change.

[0073] The following describes a specific DST condition. Table 1 shows the steps in the DST condition over a period of 360 seconds.

[0074] Table 1

[0075]

[0076] Where k is the charge / discharge rate coefficient of the DST operating condition. For example, the charging rate of step 3 is 0.5 times the base charging rate, and the duration represents the duration of the charging operation, discharging operation and resting operation.

[0077] It should be noted that the target operating condition involves performing multiple charging, discharging, and resting operations on the battery at different charge-discharge rates. The charge-discharge rates are different between each operation. For example, the charging rate in step 2 is 0.25, while that in step 3 is 0.5. The charge-discharge rate is different for each step and each operation.

[0078] Step 120: Determine the state of charge of the battery under the target operating condition using the Kalman filter method.

[0079] Once the battery's state of charge reaches the target correction point, the target operating condition is executed, causing a significant step response change in the battery's operating voltage and current. The Kalman filter method is used to obtain the battery's state of charge under the target operating condition, which is an accurate estimate of the real-time state of charge value.

[0080] Among them, the Kalman filter method is mainly used for estimating the state of actual systems in engineering applications.

[0081] In this embodiment, the battery's operating voltage and current under the target operating conditions can be obtained. Using the operating voltage and current as input parameters, the state of charge can be calculated using the Kalman filter method.

[0082] In practice, nonlinear Kalman filtering methods can be used for charge state estimation, such as the extended Kalman filter (EKF), unscented Kalman filter (UKF), and capacitive Kalman filter (CKF).

[0083] Under the target operating conditions, the battery current and voltage exhibit significant characteristic changes, and the Kalman filter SOC estimation method is highly accurate under these conditions.

[0084] In this embodiment, when the battery's state of charge (SOC) has not reached the target correction point, other SOC estimation methods such as the ampere-hour integral method can be used to estimate the SOC. Different SOC estimation methods are used alternately during the plateau period, and the estimated SOC is periodically corrected by Kalman filtering, which effectively improves the accuracy of SOC estimation.

[0085] Taking the target operating condition as DST as an example.

[0086] When the battery reaches the 20% SOC correction point during charging or discharging, the DST (Discharge-Side Response) cycle is initiated. During the DST cycle, the battery exhibits a step response, and the data characteristics change significantly. Kalman filtering is used for SOC estimation and correction. After the DST cycle ends, if the battery has not reached the next correction point, the battery continues to execute the original charging and discharging strategy, and the ampere-hour integration method is used for SOC estimation. Once the battery reaches the next correction point, Kalman filtering is used again for SOC estimation, and this cycle repeats.

[0087] It should be noted that for Class II energy storage batteries, executing the target operating condition at the target correction point during the plateau period can overcome the limitation of Kalman filtering in reducing estimation accuracy when parameters remain unchanged during the plateau period, and can also solve the problem of cumulative error caused by using a fixed state of charge estimation method for a long time during the plateau period, thus effectively improving the accuracy of state of charge estimation.

[0088] In practice, during other periods when the battery is in a plateau phase and has not reached the target correction point, the state of charge can be estimated using methods such as the ampere-hour integration method.

[0089] In this embodiment, a target correction point is set during the plateau period. By periodically targeting the target operating conditions, the limitation of the Kalman filter method in low estimation accuracy when the current and voltage parameters do not change is overcome. This allows the Kalman filter method to be effectively applied to Class II energy storage batteries to correct and compensate for the errors caused by long-term online estimation of other state of charge estimation methods (such as the ampere-hour integration method), thereby achieving real-time and accurate state of charge estimation.

[0090] It should be noted that for a certain type of energy storage battery, there is no plateau period. The target correction point is set directly, and the target operating condition is executed at the target correction point. The state of charge is estimated using the Kalman filter method. When the target correction point is not reached, other state of charge estimation methods (such as the ampere-hour integration method) are used for estimation.

[0091] The Kalman filter method only performs the target operating condition estimation at the target correction point. For other time periods outside the target correction point, other methods such as the ampere-hour integration method can be used for estimation, which will not affect the normal operation of the battery and can meet the battery's requirement to reach the required charge and discharge capacity within the specified operating time.

[0092] In practice, the target operating condition can be executed by issuing control commands through the battery's battery management system, without the need for additional devices or additional costs.

[0093] Understandably, the ampere-hour integration method has good short-term estimation accuracy, but accumulates errors over long-term applications. The Kalman filter method can eliminate the interference of sampling errors and random errors, but it cannot accurately estimate under conditions of no signal disturbance updates.

[0094] This application proposes a signal control and algorithm strategy to execute the target operating condition at the target correction point, causing the battery to exhibit a step response. This overcomes the limitations of the ampere-hour integration method and the Kalman filter method, and can effectively estimate the state of charge for any type of battery.

[0095] According to the battery state of charge determination method provided in the embodiments of this application, by setting a target correction point and executing a target operating condition to make the battery exhibit a step response, the limitation of low estimation accuracy of the Kalman filter method when the current and voltage parameters do not change can be overcome. It can also correct and compensate for the errors caused by long-term online estimation of other state of charge estimation methods, thereby improving the accuracy and precision of state of charge estimation.

[0096] In some embodiments, the method for determining the state of charge of the battery may further include:

[0097] If the battery's state of charge (SOC) has not reached the target correction point, the SOC is determined using the ampere-hour integration method.

[0098] Among them, the ampere-hour integration method estimates the state of charge (SOC) value by integrating the current response of the battery. In this embodiment, the battery's operating current is used as the input parameter, and the SOC is estimated by the ampere-hour integration method.

[0099] In practice, the calculation formula for the ampere-hour integration method can be as follows:

[0100] SOC(k)=SOC(k-1)+I(k) / (C p ·3600)

[0101] Where SOC(k) is the state of charge of the battery at time k, and C p I(k) is the rated capacity of the battery, I(k) is the operating current of the battery at time k, and SOC(k-1) is the state of charge of the battery at time k-1.

[0102] In this embodiment, when the battery's state of charge (SOC) has not reached the target correction point, the real-time SOC of the battery is obtained by the ampere-hour integration method; when the battery's SOC reaches the target correction point, the target operating condition is executed, and the real-time SOC of the battery is obtained by the Kalman filtering method, so as to accurately estimate the real-time SOC of the battery during the plateau period.

[0103] In some embodiments, the battery is a type II energy storage battery, and the method for determining the battery's state of charge may further include:

[0104] When the battery is determined to be in a plateau phase and its state of charge (SOC) has not reached the target correction point, the SOC is determined using the ampere-hour integral method. In this embodiment, the target operating condition is executed during the plateau phase, and the battery's current and voltage exhibit significant characteristic changes. At this time, the Kalman filter method provides high accuracy for estimating the SOC. During other periods of the plateau phase, the ampere-hour integral method is used. The two methods are alternated during the plateau phase, and the ampere-hour integral method is periodically corrected using the Kalman filter. This overcomes the limitation of the Kalman filter in reducing estimation accuracy when parameters remain unchanged during the plateau phase, and also solves the problem of cumulative error caused by long-term application of the ampere-hour integral method, effectively improving the accuracy of SOC estimation during the plateau phase.

[0105] In some embodiments, the battery is a type II energy storage battery, and the method for determining the battery's state of charge may further include:

[0106] Given that the battery is in a non-plateau period, the state of charge of the battery in the non-plateau period is obtained using the Kalman filter method.

[0107] Understandably, when a battery is not in a plateau phase, its voltage changes significantly, and the Kalman filter method can be used to accurately estimate the state of charge.

[0108] In some embodiments, the state of charge (SCC) period of the battery includes at least two target correction points, and the SCC difference between two adjacent target correction points is the target SCC difference.

[0109] In this embodiment, during the battery's state of charge (SOC) cycle, a target correction point is set every target SOC difference. At the target correction point, the target operating condition is executed, and the SOC is estimated using the Kalman filter method.

[0110] In this embodiment, when the battery is a type II energy storage battery, at least two target correction points are set during the battery's plateau period, and the battery's state of charge cycle includes both plateau and non-plateau periods.

[0111] For example, the target state of charge difference can be 10%, and the range of 10%-90% state of charge is the plateau period, which includes seven target correction points: 20%, 30%, 40%, 50%, 60%, 70%, and 80%.

[0112] In some embodiments, the charge / discharge rate corresponding to the target operating condition is determined based on the charge / discharge capacity of the battery under the actual operating conditions of the current operating mode.

[0113] In this embodiment, the current operating mode can be either a charging operating mode or a discharging operating mode, and the actual operating condition is the normal operating condition of the current operating mode.

[0114] It is understandable that the battery's operating conditions include the actual operating conditions of the current operating mode and the target operating conditions. When the battery's state of charge reaches the target correction point, the target operating conditions are executed; when the battery's state of charge does not reach the target correction point, the actual operating conditions of the current operating mode are executed.

[0115] For Class II energy storage batteries, the operating conditions of the battery during the plateau period include normal operating conditions and target operating conditions. When the battery's state of charge reaches the target correction point, the target operating condition is executed; when the battery's state of charge does not reach the target correction point, the normal operating condition of the plateau period is executed.

[0116] The charge / discharge rate corresponding to the target operating condition is determined based on the actual charge / discharge capacity of the battery under the current operating mode. This ensures that when the target operating condition is executed at the corresponding charge / discharge rate, the battery's charge / discharge capacity is consistent with that under the original actual operating conditions, without affecting the battery's original charge / discharge capacity target.

[0117] The actual operating conditions of the current battery operating mode can be constant current charging, constant current discharging, constant power charging, or constant power discharging.

[0118] For example, using the DST condition as the target condition, the charge and discharge capacity under the DST condition is calculated based on the original normal operating condition of the battery during the plateau period, and then the charge and discharge rate corresponding to the target condition is obtained.

[0119] The formula for calculating the battery's original normal charging and discharging capacity is as follows:

[0120]

[0121] or,

[0122]

[0123] Among them, E pre P represents the total capacity that should have been charged and discharged under normal operating conditions during the DST operating period. i C represents the charge / discharge rate in constant power mode. i t represents the charge / discharge rate in constant current mode. i This indicates the execution time of the DST condition.

[0124] For example, the DST operating condition lasts for 360 seconds. During this period, the battery is originally scheduled to first perform a 3-minute charging operation at a rate of 0.5 coulombs (C) per minute, followed by a 3-minute charging operation at a rate of 1C per minute. The corresponding E pre =0.5C*3min / 1h+1C*3min / 1h=0.075Ah.

[0125] In this embodiment, the capacity accumulated by the battery within 360 seconds of executing the DST condition is equal to the capacity accumulated under the original normal condition. The capacity obtained in each step is the charge / discharge rate * time (s) / 3600. Then, the total capacity is obtained by summing up the capacities obtained in all steps.

[0126] The DST operating condition consists of 20 steps. During the execution of the DST operating condition, its charge / discharge capacity is E. dst =80k / 3600, where k is the charge / discharge rate coefficient.

[0127] The charge / discharge capacity under DST operating conditions should meet E dst =E pre and E dst ≥k, combined with E dst =80k / 3600, derive k=E pre / 45, to obtain the value of k, and control the execution of the target operating condition based on the charge / discharge rate coefficient k.

[0128] The charge / discharge rate of each step in the DST mode depends on the charge / discharge capacity under normal operating conditions. The larger the charge / discharge capacity under normal operating conditions, the larger the charge / discharge rate of each step in the DST mode will be. This can effectively ensure that the original charge / discharge capacity target of the battery will not be affected when the DST mode is executed.

[0129] In some embodiments, the battery is a type II energy storage battery, and determining that the battery is in a plateau period may include:

[0130] Obtain the rate of change of battery voltage;

[0131] If the rate of voltage change is less than the first threshold, the battery is determined to be in a plateau period.

[0132] Among them, the battery voltage change rate is used to characterize the degree of change in battery terminal voltage, and can be the ratio of the change in terminal voltage to time.

[0133] In this embodiment, the voltage change rate is used to determine whether the battery is currently in a plateau period. The battery voltage change rate is obtained. When the battery voltage change rate is less than a first threshold, the battery is determined to be in a plateau period. When the battery voltage change rate is greater than or equal to the first threshold, the battery is determined to be in a non-plateau period.

[0134] In practice, the following formula can be used to determine this:

[0135] ΔU=U(k)-U(k-1)

[0136] Where ΔU is the rate of change of voltage, U(k) is the voltage of the battery at time k, and U(k-1) is the voltage at time k-1.

[0137] When ΔU is greater than or equal to the first threshold, it indicates that the battery voltage value changes significantly and the battery is in a non-plateau period; when ΔU is less than the threshold, it indicates that the battery voltage value is stable and the battery is in a plateau period.

[0138] In practice, the plateau period for Class II energy storage batteries is when the state of charge is between 10% and 90%. The actual situation of the batteries varies, and the judgment can be made based on the voltage change rate.

[0139] The first threshold is a pre-set voltage change rate threshold, which can be obtained through experimental measurement and induction.

[0140] This application embodiment uses a combination of Kalman filtering and ampere-hour integration to accurately estimate the battery state of charge.

[0141] The following example uses a battery as a type II energy storage battery to introduce an implementation of online state of charge estimation.

[0142] like Figure 2As shown, during the online estimation of state of charge, parameters such as the rate of voltage change are used to determine whether the battery is in a plateau phase.

[0143] When the battery is determined to be in a non-plateau period, the Kalman filter method is used to estimate the battery's state of charge (SOC), thus obtaining the SOC.

[0144] When it is determined that the battery is in a plateau period, it is necessary to further determine whether the battery's state of charge has reached the target correction point.

[0145] When the battery is determined to have reached the target correction point, the state of charge (SOC) value of the battery is estimated by executing the DST operating condition and using the Kalman filter method, thus obtaining the SOC value.

[0146] In this embodiment, in order to ensure that the battery performs charging and discharging according to the originally specified time and capacity, the charging and discharging capacity of the battery is required to remain the same under DST conditions as under the original normal operating conditions.

[0147] During other periods of the plateau period, that is, the periods when it is determined that the battery has not reached the target correction point, the state of charge of the battery is estimated using the ampere-hour integration method, thus obtaining the state of charge.

[0148] Take the battery charging process as an example.

[0149] like Figure 4 As shown, this illustrates the process of charging a battery from 0% to 100% state of charge.

[0150] Between 0% and 10%, the battery is in a non-plateau period. The state of charge is estimated using the Kalman filter method, and the battery is operating under normal conditions.

[0151] Between 10% and 90%, the battery is in a plateau period. A target correction point is set every 10%. When the target correction point is not reached, the state of charge is estimated using the ampere-hour integration method, and the battery operates under normal conditions. When the target correction point is reached, the DST condition is executed, and the state of charge is estimated using the Kalman filter method.

[0152] Between 90% and 100%, the battery is in a non-plateau period. The state of charge is estimated using the Kalman filter method, and the battery is operating under normal conditions.

[0153] It should be noted that the state of charge (SOC) estimation process during the discharge process is the same as that during the battery charging process. During the discharge process, the SOC of the battery is discharged from 100% to 0%. During the non-plateau period, the Kalman filter method is used to estimate the SOC. During the plateau period and when the target correction point is reached, the DST condition is executed, and the Kalman filter method is used to estimate the SOC. During the plateau period and when the target correction point is not reached, the ampere-hour integral method is used to estimate the SOC.

[0154] This application combines the ampere-hour integration method and the Kalman filter method, introducing a target correction point to overcome the application limitations of the Kalman filter method. This enables it to be effectively used for the estimation of the state of charge during the plateau period of Class II energy storage batteries. At the same time, it can also make up for the error accumulation of the ampere-hour integration method during the long-term estimation process. The combination of these complementary methods enables accurate estimation of the state of charge of the battery throughout its entire life cycle.

[0155] The battery state of charge determination method provided in this application can be executed by a battery state of charge determination device. This application uses an example of a battery state of charge determination device executing the battery state of charge determination method to illustrate the battery state of charge determination device provided in this application.

[0156] This application also provides a device for determining the state of charge of a battery.

[0157] like Figure 5 As shown, the device for determining the state of charge of the battery includes:

[0158] The first processing module 510 is used to control the battery to enter a target operating condition when it is determined that the battery's state of charge has reached the target correction point, so that the battery exhibits a step response. The target operating condition is to perform multiple target operations with different charge and discharge rates on the battery. The target operations include charging operation, discharging operation and resting operation.

[0159] The second processing module 520 is used to obtain the state of charge of the battery under the target operating condition according to the Kalman filter method.

[0160] The battery state of charge determination device provided in the embodiments of this application, by setting a target correction point and executing a target operating condition to make the battery exhibit a step response, can overcome the limitation of low estimation accuracy of the Kalman filter method when the current and voltage parameters do not change. It can also correct and compensate for the errors caused by long-term online estimation of other state of charge estimation methods, thereby improving the accuracy and precision of state of charge estimation.

[0161] In some embodiments, the first processing module 510 is further configured to obtain the state of charge of the battery according to the ampere-hour integration method when it is determined that the state of charge of the battery has not reached the target correction point.

[0162] In some embodiments, the state of charge (SCC) period of the battery includes at least two target correction points, and the SCC difference between two adjacent target correction points is the target SCC difference.

[0163] In some embodiments, the charge / discharge rate corresponding to the target operating condition is determined based on the charge / discharge capacity of the battery under the actual operating conditions of the current operating mode.

[0164] In some embodiments, the battery is a type II energy storage battery, and the first processing module 510 is further configured to control the battery to enter the target operating condition when it is determined that the battery is in a plateau period and the state of charge of the battery has reached the target correction point.

[0165] In some embodiments, the first processing module 510 is further configured to acquire the voltage change rate of the battery;

[0166] If the rate of voltage change is less than the first threshold, the battery is determined to be in a plateau period.

[0167] In some embodiments, the first processing module 510 is further configured to determine the state of charge of the battery according to the ampere-hour integration method when it is determined that the battery is in a plateau period and the state of charge of the battery has not reached the target correction point.

[0168] In some embodiments, the battery is a type II energy storage battery, and the first processing module 510 is further configured to obtain the state of charge of the battery during the non-plateau period according to the Kalman filter method when it is determined that the battery is in a non-plateau period.

[0169] The device for determining the state of charge of the battery in this application embodiment can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0170] The device for determining the state of charge of the battery in this embodiment can be a device with an operating system. This operating system can be Android, iOS, or other possible operating systems; this embodiment does not specifically limit the specific operating system used.

[0171] The battery state of charge determination device provided in this application embodiment can achieve Figures 1 to 4The various processes implemented in the method implementation examples will not be described again here to avoid repetition.

[0172] This application also provides a system for determining the state of charge of a battery.

[0173] like Figure 6 As shown, the battery state of charge determination system of this application embodiment includes: a battery 630, a data acquisition and control module 620, and an edge computing module 610.

[0174] The battery 630 is connected to the acquisition and control module 620, and the acquisition and control module 620 is connected to the edge computing module 610.

[0175] The acquisition and control module 620 is used to acquire the current and voltage data of the battery 630 and transmit the current and voltage data of the battery 630 to the edge computing module 610.

[0176] In some embodiments, the acquisition and control module 620 may be a battery management system (BMS) or other battery management unit that can acquire current and voltage data of the battery 630 during operation.

[0177] The acquisition and control module 620 is connected to the edge computing module 610, and transmits the acquired current and voltage data of the battery 630 to the edge computing module 610 for the edge computing module 610 to calculate the state of charge.

[0178] The edge computing module 610 is used to calculate the state of charge of the battery 630 based on the current and voltage data of the battery 630, and feeds back the calculation result of the state of charge of the battery 630 to the acquisition and control module 620.

[0179] In some embodiments, the edge computing module 610 may be an edge box, a small industrial computer, or a micro server that is communicatively connected to the acquisition and control module 620.

[0180] The edge computing module 610 feeds back the calculated state of charge of the battery 630 to the acquisition and control module 620 in real time. When the acquisition and control module 620 determines that the state of charge of the battery 630 has reached the target correction point, it outputs a charge and discharge control command to the battery 630 to control the battery 630 to perform the target operating condition, so that the battery 630 exhibits a step response. The edge computing module 610 is used to determine the state of charge of the battery 630 under the target operating condition according to the Kalman filtering method.

[0181] The target operating condition involves performing multiple charging, discharging, and resting operations on the battery 630 at different charge / discharge rates.

[0182] In this embodiment, when the acquisition and control module 620 controls the battery 630 to perform the target operating condition, the edge computing module 610 determines the state of charge of the battery 630 under the target operating condition based on the current and voltage data of the battery 630 collected by the acquisition and control module 620 and the Kalman filter method.

[0183] In related technologies, the system BMS is often used to collect current and voltage data, estimate the state of charge, and perform corresponding battery control. However, the BMS has limited computing resources and cannot carry out more complex logical operations and higher-order algorithm models.

[0184] In this embodiment, the introduction of an edge computing module 610 to assist in calculation and diagnosis can effectively reduce the computational resource consumption of the BMS, while also supporting the operation of more complex logical operations and higher-order algorithm models. The algorithm operation function and the battery 630 control function are decoupled from the same device, allowing the two functions to be executed independently, which is also beneficial for later maintenance and iterative upgrades.

[0185] The battery state of charge determination system provided in the embodiments of this application, by setting a target correction point and executing a target operating condition to make the battery 630 exhibit a step response, can overcome the limitation of low estimation accuracy of the Kalman filter method when the current and voltage parameters do not change. It can also correct and compensate for the errors caused by long-term online estimation of other state of charge estimation methods, thereby improving the accuracy and precision of state of charge estimation.

[0186] In some embodiments, the edge computing module 610 can be used to determine the charge / discharge rate corresponding to the target operating condition based on the actual operating conditions of the battery 630's current operating mode, and feed back the charge / discharge rate corresponding to the target operating condition to the acquisition and control module 620.

[0187] In this embodiment, the acquisition and control module 620 is used to control the battery 630 to perform the target operating condition according to the charge and discharge rate corresponding to the target operating condition.

[0188] It should be noted that the charge / discharge rate corresponding to the target operating condition is determined based on the actual charge / discharge capacity of battery 630 under the current operating mode. This ensures that when the target operating condition is executed at the corresponding charge / discharge rate, the charge / discharge capacity of battery 630 is consistent with the charge / discharge capacity under the original actual operating conditions, and will not affect the original charge / discharge capacity target of battery 630.

[0189] In some embodiments, such as Figure 7As shown, this application embodiment also provides an electronic device 700, including a processor 701, a memory 702, and a computer program stored in the memory 702 and executable on the processor 701. When the program is executed by the processor 701, it implements the various processes of the above-described method embodiment for determining the state of charge of a battery and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0190] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0191] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described method embodiment for determining the state of charge of a battery, and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0192] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0193] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for determining the state of charge of a battery.

[0194] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0195] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0196] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0197] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

[0198] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0199] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for determining the state of charge of a battery, characterized in that, include: When it is determined that the state of charge of the battery has reached the target correction point, the battery is controlled to enter the target operating condition, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations and resting operations with different charge and discharge rates on the battery. The state of charge of the battery under the target operating condition is determined using the Kalman filter method. The method further includes: If it is determined that the state of charge of the battery has not reached the target correction point, the state of charge of the battery is determined according to the ampere-hour integration method. The battery is a type II energy storage battery. The step of controlling the battery to enter the target operating condition after determining that the battery's state of charge has reached the target correction point includes: When it is determined that the battery is in a plateau period and the state of charge of the battery has reached the target correction point, the battery is controlled to enter the target operating condition.

2. The method for determining the state of charge of a battery according to claim 1, characterized in that, The state of charge (SCC) period of the battery includes at least two target correction points, and the SCC difference between two adjacent target correction points is the target SCC difference.

3. The method for determining the state of charge of a battery according to claim 1, characterized in that, The charge / discharge rate corresponding to the target operating condition is determined based on the actual charge / discharge capacity of the battery under the current operating conditions.

4. The method for determining the state of charge of a battery according to claim 1, characterized in that, The determination that the battery is in a plateau phase includes: Obtain the voltage change rate of the battery; If the voltage change rate is less than a first threshold, the battery is determined to be in the plateau period.

5. The method for determining the state of charge of a battery according to any one of claims 1-4, characterized in that, The battery is a type II energy storage battery, and the method further includes: If it is determined that the battery is in a plateau period and the battery's state of charge has not reached the target correction point, the battery's state of charge is determined according to the ampere-hour integration method.

6. The method for determining the state of charge of a battery according to any one of claims 1-4, characterized in that, The battery is a type II energy storage battery, and the method further includes: If the battery is determined to be in a non-plateau period, the state of charge of the battery in the non-plateau period is determined according to the Kalman filter method.

7. A device for determining the state of charge of a battery, characterized in that, include: The first processing module is used to control the battery to enter a target operating condition when it is determined that the battery's state of charge has reached the target correction point, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations, and resting operations on the battery at different charge and discharge rates. The second processing module is used to determine the state of charge of the battery under the target operating condition according to the Kalman filter method. The first processing module is also used for: If it is determined that the state of charge of the battery has not reached the target correction point, the state of charge of the battery is determined according to the ampere-hour integration method. The battery is a type II energy storage battery, and the first processing module is further used for: When it is determined that the battery is in a plateau period and the state of charge of the battery has reached the target correction point, the battery is controlled to enter the target operating condition.

8. A system for determining the state of charge of a battery, characterized in that, include: The system includes a battery, a data acquisition and control module, and an edge computing module, wherein the battery is connected to the data acquisition and control module, and the data acquisition and control module is connected to the edge computing module. The acquisition and control module is used to acquire the current and voltage data of the battery operation and transmit the current and voltage data of the battery operation to the edge computing module; The edge computing module is used to calculate the state of charge of the battery based on the current and voltage data of the battery operation, and to feed back the calculation result of the state of charge of the battery to the acquisition and control module. The acquisition and control module is used to control the battery to perform a target operating condition when it is determined that the state of charge of the battery has reached the target correction point, so that the battery exhibits a step response. The target operating condition is to perform multiple charging operations, discharging operations and resting operations with different charge and discharge rates on the battery. The edge computing module is used to determine the state of charge of the battery under the target operating condition according to the Kalman filtering method. If it is determined that the state of charge of the battery has not reached the target correction point, the state of charge of the battery is determined according to the ampere-hour integration method. The battery is a type II energy storage battery. When it is determined that the battery is in a plateau period and the state of charge of the battery reaches the target correction point, the battery is controlled to enter the target operating condition.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for determining the state of charge of the battery as described in any one of claims 1-6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for determining the state of charge of a battery as described in any one of claims 1-6.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining the state of charge of the battery as described in any one of claims 1-6.

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