Battery charging state estimation method, system and device, medium and product

Abstract

The invention discloses a battery charging state estimation method, system and device, a medium and a product. The method comprises: determining a working state of a battery; when the working state is a standing state, calibrating the open-circuit voltage of the battery according to the working temperature of the battery at the current moment, and determining an initial battery charging state according to the calibrated open-circuit voltage; when the working state is a dynamic operation state, estimating the charging state of the battery by adopting a capacity correction ampere-hour integral method based on the initial charging state of the battery; and returning to judge the working state of the battery until the life cycle of the battery is ended. According to the method, the initial battery charging state is calibrated based on the calibrated open-circuit voltage, and online estimation of the battery charging state is carried out by adopting a capacity correction ampere-hour integral method based on the calibrated initial battery charging state, so that accumulated errors during estimation of the battery charging state by adopting the ampere-hour integral method can be eliminated; and the estimation accuracy of the SOC is effectively improved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of battery management technology, and in particular to a method, system, device, medium, and product for estimating a battery charging state. Background Art

[0002] The battery's state of charge (SOC) is a core parameter in battery management systems. SOC indicates the battery's current remaining charge and is a key indicator for determining battery endurance and proper usage. In marine applications, accurate SOC estimation not only improves battery utilization efficiency and extends battery life, but also prevents potential failures and ensures safe ship operation.

[0003] The ampere-hour integration method is a widely used algorithm for estimating battery SOC. It doesn't examine the electrochemical reactions within the battery or the relationships between various parameters. Instead, it focuses solely on the system's external characteristics. By monitoring the charge and discharge of the battery in real time, it estimates the remaining charge at any given moment. The principle behind the ampere-hour integration method is relatively simple: the difference between the initial SOC and the consumed SOC represents the current SOC. The consumed SOC is derived primarily from the integration of the discharge current over time.

[0004] The ampere-hour integration method calculates SOC based on current integration. However, the ampere-hour integration method is easily affected by sensor accuracy, resulting in error accumulation, resulting in poor SOC estimation accuracy. Summary of the Invention

[0005] The present invention provides a battery state of charge estimation method, system, device, medium and product to solve the problem that the ampere-hour integration method is easily affected by sensor accuracy, resulting in error accumulation and poor SOC estimation accuracy.

[0006] According to one aspect of the present invention, a method for estimating a battery state of charge is provided, comprising:

[0007] Determine the working status of the battery;

[0008] When the working state is a static state, calibrating the open circuit voltage of the battery according to the current working temperature of the battery, and determining the initial battery charging state according to the calibrated open circuit voltage;

[0009] When the working state is a dynamic operating state, estimating the battery charging state by using an ampere-hour integration method of a corrected capacity based on the initial battery charging state, wherein the ampere-hour integration method of the corrected capacity uses a correction coefficient to correct the rated capacity of the battery;

[0010] Return to executing the determination of the working status of the battery until the life cycle of the battery ends.

[0011] According to another aspect of the present application, there is provided a battery management system, comprising:

[0012] a judging module configured to judge a working state of the battery;

[0013] a calibrating module configured to calibrate an open circuit voltage of the battery according to a working temperature of the battery at a current time when the working state is a static state, and determine an initial state of charge of the battery according to the calibrated open circuit voltage;

[0014] an estimating module configured to estimate the state of charge of the battery based on the initial state of charge of the battery by using a modified capacity ampere-hour integral method when the working state is a dynamic running state, wherein the modified capacity ampere-hour integral method uses a correction coefficient to modify a rated capacity of the battery.

[0015] According to another aspect of the present application, there is provided a battery-powered device, comprising:

[0016] at least one processor;

[0017] and a memory connected in communication with the at least one processor;

[0018] wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method for estimating the state of charge of the battery according to any one of the embodiments of the present application.

[0019] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to implement the method for estimating the state of charge of the battery according to any one of the embodiments of the present application when executed by the processor.

[0020] According to another aspect of the present application, there is provided a computer program product comprising a computer program for implementing the method for estimating the state of charge of the battery according to any one of the embodiments of the present application when executed by a processor.

[0021] The technical solution of the embodiments of the present application calibrates the initial state of charge of the battery based on the calibrated open circuit voltage, and estimates the state of charge of the battery on-line based on the calibrated initial state of charge by using the modified capacity ampere-hour integral method, thereby solving the accumulated error of the ampere-hour integral method when estimating the state of charge of the battery, and achieving the beneficial effect of effectively improving the estimation accuracy of the SOC.

[0022] It is to be understood that the details set forth in the description contained herein do not limit the scope of the embodiments of the application. Other embodiments of the application will be readily apparent to one of ordinary skill in the art from the description herein, and it will be understood that the scope of the present application should not necessarily be limited by the preferred embodiments, and should only be defined by the appended claims, and equivalents thereof. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without any creative effort.

[0024] Figure 1 A flowchart of a battery charge state estimation method provided for the first embodiment of the present application;

[0025] Figure 2 A flowchart of a battery charge state estimation method provided for the second embodiment of the present application;

[0026] Figure 3 A flowchart of a battery charge state estimation method provided for the third embodiment of the present application;

[0027] Figure 4 A flowchart of a battery charge state estimation method provided for the fourth embodiment of the present application;

[0028] Figure 5 A flowchart of a battery charge state estimation method provided for the specific embodiment of the present application;

[0029] Figure 6 A structural schematic diagram of a battery management system provided for the fifth embodiment of the present application;

[0030] Figure 7 A structural schematic diagram of a battery power supply device for the battery charge state estimation method of the embodiment of the present application. DETAILED DESCRIPTION

[0031] For the better understanding of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those skilled in the art without creative efforts should fall into the protection scope of the present application. It should be understood that the steps in the method embodiments of the present application can be executed in different orders and / or in parallel. In addition, the method embodiments can include additional steps and / or omit the execution of the illustrated steps. The scope of the present application is not limited in this respect.

[0032] The term "comprising" and variations thereof as used herein are used inclusively, i.e., "comprising, but not limited to." The term "based on" is "based at least in part on." The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments." Related terms are defined below in the description of the application.

[0033] It should be noted that the terms "first", "second", and the like, used in the description and the claims of the present application as well as above-mentioned appended drawings, are used to distinguish similar objects, and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the data thus used can be interchanged, where appropriate, so that the embodiments of the application described herein can be carried out in other than the order illustrated or described herein. Furthermore, the terms "comprising" and "having," and variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, product, or apparatus that comprises a list of steps or units is not necessarily limited to those steps or units that are explicitly listed, but can include additional steps or units that are not expressly listed or inherent to such process, method, product, or apparatus.

[0034] It should be noted that the modification of "one" or "multiple" mentioned in the present application is illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise explicitly indicated in the context, it should be understood as "one or more".

[0035] The names of the messages or information exchanged between the devices in the embodiments of the present application are only for illustrative purposes, and are not intended to limit the scope of the messages or information.

[0036] Embodiment one

[0037] Figure 1A flowchart of a battery state of charge estimation method provided by Embodiment One of the present application. This method is applicable to the estimation of the state of charge of a lithium iron phosphate battery pack. The method can be executed by a battery state of charge estimation device, which can be implemented in software and / or hardware and is generally integrated into a battery-powered device. In this embodiment, the battery-powered device includes but is not limited to electric vehicles, hybrid electric vehicles, consumer electronics, medical devices, hybrid electric ships, and all-electric ships, etc. The battery-powered device can contain a battery management system.

[0038] As shown in Figure 1 A battery state of charge estimation method provided by Embodiment One of the present application includes the following steps:

[0039] S110, determine the working state of the battery.

[0040] The battery can be a lithium iron phosphate battery. Lithium iron phosphate (LiFePO4) is a type of lithium-ion battery that uses lithium iron phosphate as the positive electrode material. Its basic structure includes:

[0041] Positive electrode material: composed of lithium iron phosphate (LiFePO4), with excellent safety and cycle life. Lithium iron phosphate has a layered structure, which can stably insert and remove lithium ions, ensuring high stability and long life of the battery.

[0042] Negative electrode material: graphite is commonly used as the negative electrode material. Graphite has good electrical conductivity and moderate electrochemical properties, which is conducive to the insertion and extraction of lithium ions.

[0043] Electrolyte: generally uses organic solvents containing lithium salts as electrolytes, such as LiPF6 dissolved in carbonate solvents. The role of the electrolyte is to provide a conductive channel for lithium ions to ensure the smooth progress of the charging and discharging process of the battery.

[0044] Separator: The separator is a porous material, usually made of polyethylene (PE) or polypropylene (PP). The main role of the separator is to isolate the positive and negative electrode materials to prevent short circuits while allowing lithium ions to pass through.

[0045] The working principle of the lithium iron phosphate battery is based on the insertion and extraction of lithium ions:

[0046] Charging process: During the charging process, an external power source applies a voltage through the positive and negative electrodes of the battery. Lithium ions are removed from the positive electrode material (LiFePO4) and move to the negative electrode material (graphite) through the electrolyte. Electrons flow through the external circuit, thus completing the charging process.

[0047] Discharge process: in the discharge process, lithium ions in the negative electrode material are deintercalated, return to the positive electrode material through the electrolyte, and at the same time, electrons flow through the external circuit to provide power to the load, thereby completing the discharge.

[0048] In this embodiment, the working state of the battery can be determined according to the current, voltage and temperature of the battery.

[0049] S120, when the working state is the static state, the open circuit voltage of the battery is calibrated according to the working temperature at the current time, and the initial battery state of charge is determined according to the calibrated open circuit voltage.

[0050] In this embodiment, when the battery is in a static state, the working temperature of the battery will affect the open circuit voltage of the battery, and the battery management system can perform open circuit voltage calibration. The open circuit voltage refers to the potential difference between the positive and negative electrodes when the external circuit has no current flowing through and the battery reaches equilibrium. After a long period of static state, there is a fixed functional relationship between the terminal voltage (i.e. open circuit voltage) of the battery and the state of charge SOC of the battery.

[0051] The initial battery state of charge can be determined in the following two ways:

[0052] Method one: the initial battery state of charge is calculated according to the working temperature of the battery at the current time, the terminal voltage of the battery and the double input model, wherein the double input model represents the fixed functional relationship between the terminal voltage of the battery and the working temperature of the battery and the battery state of charge.

[0053] Method two: the initial battery state of charge is obtained according to the working temperature of the battery at the current time and the open circuit voltage value and the three-dimensional mapping relationship table, wherein the three-dimensional mapping relationship table includes the mapping relationship between the working temperature of the battery, the open circuit voltage value and the battery state of charge.

[0054] S130, when the working state is the dynamic running state, the battery state of charge is estimated by adopting the ampere-hour integral method with a correction capacity based on the initial battery state of charge. The correction coefficient is used to correct the rated capacity of the battery in the ampere-hour integral method.

[0055] The correction coefficient can include a temperature correction coefficient, a cycle number correction coefficient and a charge-discharge current ratio correction coefficient.

[0056] In this embodiment, since the working temperature of the battery, the cycle number of the battery and the working current have an effect on the capacity, the rated capacity of the battery in the ampere-hour integral method can be corrected to the real-time effective capacity by the correction coefficient, and the battery state of charge can be estimated by the following formula:

[0057]

[0058] In the above formula, C N _new is the real-time effective capacity, SOC(0) is the initial battery state of charge, and I is the current of the battery.

[0059] The temperature correction coefficient can be calculated according to the current temperature and a temperature correction relationship; the charge-discharge current rate correction coefficient can be calculated according to the current current condition and a charge-discharge current rate correction relationship; and the cycle number correction coefficient can be calculated according to the battery cycle number and a cycle number correction relationship.

[0060] S140, returning to execute the judgment on the working state of the battery until the life cycle of the battery ends. The SOC estimation exists in the whole life cycle of the battery and is a real-time estimation process.

[0061] In the embodiment, after the current SOC estimation ends, it is necessary to return to step S110 to re-judge the working state of the battery, to execute the SOC online estimation according to different working states, and to repeat the above process until the life cycle of the battery ends and the SOC online estimation stops.

[0062] The battery state of charge estimation method provided in the first embodiment of the application first judges the working state of the battery; then when the working state is the static state, the open-circuit voltage of the battery is calibrated according to the working temperature of the battery at the current moment, and the initial battery state of charge is determined according to the calibrated open-circuit voltage; when the working state is the dynamic running state, the battery state of charge is estimated by the ampere-hour integral method with a corrected capacity based on the initial battery state of charge, wherein the ampere-hour integral method with a corrected capacity corrects the rated capacity of the battery by using a correction coefficient; and finally, the judgment on the working state of the battery is executed until the life cycle of the battery ends. The above method calibrates the initial battery state of charge based on the calibrated open-circuit voltage, and estimates the battery state of charge online by the ampere-hour integral method with a corrected capacity based on the calibrated initial battery state of charge, which can eliminate the accumulated error in the estimation of the battery state of charge by the ampere-hour integral method, and effectively improve the estimation accuracy of the SOC.

[0063] On the basis of the above embodiments, variant embodiments of the above embodiments are proposed. It should be noted that, in order to make the description brief, only the differences from the above embodiments are described in the variant embodiments.

[0064] In one embodiment, the judgment on the working state of the battery includes: monitoring the current value of the battery, the voltage value of the battery and the battery temperature in real time; and judging the working state of the battery according to the current value of the battery and the change trend of the voltage value of the battery and the battery temperature within a preset time length.

[0065] The preset time length can be at least 30 minutes, if the current value of the battery is always 0 within 30 minutes, the voltage of the battery and the temperature of the battery tend to be flat, and the battery is determined to be in a static state; otherwise, the battery is in a dynamic running state.

[0066] Embodiment two

[0067] Figure 2 A flowchart of a battery state of charge estimation method provided by Embodiment Two of the application is shown in the figure, and Embodiment Two is optimized on the basis of the above-mentioned embodiments. For details of Embodiment Two, please refer to Embodiment One.

[0068] As Figure 2 shown, the battery state of charge estimation method provided by Embodiment Two of the application includes the following steps:

[0069] S210, determining the working state of the battery.

[0070] S220, when the working state is a static state, obtaining the working temperature and open-circuit voltage value of the battery at the current time.

[0071] S230, determining the initial battery state of charge according to the working temperature and open-circuit voltage value of the battery at the current time through a double-input model.

[0072] The double-input model represents a fixed function relationship between the open-circuit voltage and the working temperature of the battery and the battery state of charge.

[0073] The double-input model is a fitting function established according to the open-circuit voltage values of the battery at different working temperatures and different SOC obtained through experiments:

[0074] SOC=f(U oc ,T)

[0075] Wherein U oc represents the open-circuit voltage, and T represents the working temperature of the battery.

[0076] In this embodiment, the working temperature and open-circuit voltage value of the battery monitored at the current time are substituted into the fitting function to calculate the battery state of charge SOC, which is used as the initial state of charge.

[0077] S240, when the working state is a dynamic running state, the initial battery state of charge is used to estimate the battery state of charge by adopting the ampere-hour integral method with a corrected capacity.

[0078] The ampere-hour integral method with a corrected capacity corrects the rated capacity of the battery by using a correction coefficient.

[0079] S250, determining whether the life cycle of the battery is over.

[0080] If the battery life cycle ends, the battery charging state estimation is completed; if the battery life cycle has not ended, the process returns to step S210 and is re-executed until the battery life cycle ends.

[0081] A second embodiment of the present invention provides a method for estimating the state of charge of a battery. The method corrects the initial SOC through a dual-input model, thereby improving the estimation accuracy of the SOC.

[0082] Example 3

[0083] Figure 3 This is a flow chart of a method for estimating the battery charging state provided by the third embodiment of the present invention. This third embodiment is optimized based on the above embodiments. For details not yet provided in this embodiment, please refer to the first embodiment.

[0084] like Figure 3 As shown, a method for estimating a battery charging state provided by a third embodiment of the present invention includes the following steps:

[0085] S310: Determine the working status of the battery.

[0086] S320: When the working state is the static state, obtain the working temperature and open circuit voltage value of the battery at the current moment.

[0087] S330 , obtaining an initial battery charging state by searching a three-dimensional mapping relationship table according to the current operating temperature and open circuit voltage value of the battery.

[0088] The three-dimensional mapping relationship table is established based on the open circuit voltage of the battery at different operating temperatures and different battery charging states.

[0089] Among them, the open circuit voltage of the battery at different operating temperatures and different battery charging states can be obtained through experiments.

[0090] In this embodiment, when the operating temperature and open circuit voltage of the battery are known, the current battery charging state can be found according to the mapping relationship between the battery operating temperature, open circuit voltage and SOC, and used as the initial charging state.

[0091] S340: When the working state is a dynamic operating state, estimate the battery charging state by using an ampere-hour integration method of corrected capacity based on the initial battery charging state.

[0092] The ampere-hour integration method for correcting the capacity adopts a correction coefficient to correct the rated capacity of the battery.

[0093] S350: Determine whether the battery life cycle has ended.

[0094] If the battery life cycle ends, the battery charging state estimation is completed; if the battery life cycle has not ended, the process returns to step S210 and is re-executed until the battery life cycle ends.

[0095] A second embodiment of the present invention provides a method for estimating a battery state of charge. The method corrects an initial SOC by looking up a three-dimensional mapping table, thereby improving the accuracy of SOC estimation.

[0096] Example 4

[0097] Figure 4 This is a flow chart of a method for estimating the battery charging state provided by the fourth embodiment of the present invention. This fourth embodiment is optimized based on the above embodiments. For details not yet fully described in this embodiment, please refer to the above embodiments.

[0098] like Figure 4 As shown, a method for estimating a battery charging state provided by a fourth embodiment of the present invention includes the following steps:

[0099] S410: Determine the working status of the battery.

[0100] S420: When the working state is the static state, calibrate the open circuit voltage of the battery according to the current working temperature of the battery, and determine the initial battery charging state according to the calibrated open circuit voltage.

[0101] S430: When the working state is a dynamic operating state, determine the temperature correction coefficient according to the real-time temperature of the battery using a temperature correction equation.

[0102] It should be noted that the execution order of steps S430 to S450 is not limited.

[0103] The temperature correction relationship is determined as follows: based on the real-time operating temperature of the battery, the nominal capacity of the battery is obtained through a mathematical relationship or a multi-dimensional lookup table, and the temperature correction relationship is determined based on the nominal capacity of the battery at different operating temperatures and the actual available capacity of the battery at different temperatures.

[0104] Among them, through temperature-capacity, rate-capacity, cyclic charge and discharge experiments and multi-temperature HPPC experiments, a mathematical relationship or multi-dimensional lookup table can be established between the battery nominal capacity and the battery operating temperature, battery cycle number and charge and discharge rate.

[0105] In this embodiment, the temperature correction coefficient can be calculated by inputting the collected real-time operating temperature of the battery into a temperature correction equation.

[0106] S440, determining the cycle number correction coefficient according to the current cycle number of the battery through a cycle number correction relationship.

[0107] The cycle number correction relationship is determined according to the cycle number of the battery through a mathematical relationship or a multi-dimensional lookup table to obtain the nominal capacity of the battery, and according to the nominal capacity of the battery under different cycle numbers and the actual available capacity of the battery under different cycle numbers.

[0108] The mathematical relationship or the multi-dimensional lookup table between the nominal capacity of the battery and the working temperature of the battery, the cycle number of the battery and the charge-discharge rate of the battery can be established through temperature-capacity, rate-capacity, cycle charge-discharge experiments and multi-temperature HPPC experiments.

[0109] In this embodiment, the current cycle number of the battery collected is input into the cycle number correction relationship to calculate the cycle number correction coefficient.

[0110] S450, determining the charge-discharge current rate correction coefficient according to the real-time current of the battery through a charge-discharge current rate correction relationship.

[0111] The charge-discharge current rate correction relationship is determined according to the charge-discharge rate of the battery through a mathematical relationship or a multi-dimensional lookup table to obtain the nominal capacity of the battery, and according to the nominal capacity of the battery under different charge-discharge rates and the actual available capacity of the battery under different charge-discharge rates.

[0112] The mathematical relationship or the multi-dimensional lookup table between the nominal capacity of the battery and the working temperature of the battery, the cycle number of the battery and the charge-discharge rate of the battery can be established through temperature-capacity, rate-capacity, cycle charge-discharge experiments and multi-temperature HPPC experiments.

[0113] In this embodiment, the real-time current collected is input into the charge-discharge current rate correction relationship to calculate the charge-discharge current rate correction coefficient.

[0114] S460, correcting the rated capacity of the battery according to the temperature correction coefficient, the cycle number correction coefficient and the charge-discharge current rate correction coefficient.

[0115] The correction formula is as follows:

[0116] C N_new = C N × η T × η H × η P

[0117] In the above formula, C Nrepresents the rated capacity of the battery, C N_new represents the real-time effective capacity, η T represents the temperature correction coefficient, η H represents the cycle number correction coefficient, η P represents the charge-discharge current rate correction coefficient.

[0118] S470, determining whether the life cycle of the battery is completed.

[0119] If the life cycle of the battery is completed, the estimation of the state of charge of the battery is completed; if the life cycle of the battery is not completed, the step S210 is returned to be executed again until the life cycle of the battery is completed.

[0120] The battery state of charge estimation method provided by the fourth embodiment of the present application uses the temperature correction coefficient, the cycle number correction coefficient and the charge-discharge current rate correction coefficient to correct the rated capacity of the battery to obtain the real-time effective capacity, and estimates the SOC based on the real-time effective capacity through the ampere-hour integration method, so that the estimation accuracy of the SOC can be effectively improved.

[0121] The embodiment of the present application provides a specific implementation mode on the basis of the technical solutions of the above-mentioned embodiments.

[0122] As a specific implementation mode of the present application, Figure 5 The flow chart of the battery state of charge estimation method provided by the specific embodiment of the present application is shown in Figure 5 , and includes the following flow:

[0123] Step 1, real-time monitoring and state judgment.

[0124] The battery management system monitors the current, voltage and temperature of the battery in real time, and judges whether the battery is currently in a “dynamic running state” or a “long-time static state” according to the current value of the battery and the change trend of the voltage and temperature within 30 minutes.

[0125] Step 2, performing the initialization calibration and online estimation of the SOC.

[0126] When the battery is currently in the “long-time static state”, the battery management system performs the open circuit voltage calibration, collects the terminal voltage U oc and the temperature T of the current battery, and calculates the initial SOC value through the established fitting function SOC=f(U oc , T) or the lookup three-dimensional mapping relationship table.

[0127] In order to overcome the defect that the open circuit voltage OCV is affected by the temperature, the open circuit voltage values of the battery at different working temperatures and different SOCs are obtained through experiments, and a T-OCV-SOC three-dimensional mapping relationship table or a fitting function SOC=f(Uoc

[0128] When the battery is currently in the "dynamic running state", the battery management system performs the dynamic correction ampere-hour integration method, collects real-time current conditions, working temperature of the battery, cycle number and other parameters based on the initial SOC value SOC(0), inputs the environmental temperature (i.e. the working temperature of the battery) into the temperature correction coefficient η T The relationship (i.e. the temperature correction relationship) obtains the temperature correction coefficient η T The cycle number is inputted into the cycle correction coefficient η H The relationship (i.e. the cycle correction relationship) obtains the cycle correction coefficient η H The current condition is inputted into the current correction coefficient η P The relationship (i.e. the charge-discharge current rate correction relationship) obtains the rate correction coefficient η P ; the real-time effective capacity C N _new is calculated by C N ×η T ×η H ×η P The real-time effective capacity C N _new is calculated, and the online integral estimation of SOC is performed according to the following formula:

[0129]

[0130] Wherein, C N is the rated capacity of the battery, η T represents the temperature correction coefficient, η H represents the cycle correction coefficient, and η P represents the charge-discharge current rate correction coefficient.

[0131] Step 3, periodic closed-loop correction.

[0132] The battery management system repeatedly performs step 1 during operation, and once it is detected that the battery enters the "long-time stationary state" from the "dynamic running state", the battery management system automatically performs step 2 for open-circuit voltage calibration and online estimation, so as to eliminate the error accumulated by the ampere-hour integration method during operation, and realize long-term high accuracy of SOC estimation.

[0133] Example five

[0134] Figure 6 A structural schematic diagram of a battery management system provided for the fifth embodiment of the application, which can be applied to the estimation of the state of charge of a lithium iron phosphate battery pack, wherein the device can be realized by software and / or hardware, and is generally integrated on a battery-powered device.

[0135] As Figure 6 ​As shown, the device comprises a judging module 110, a calibration module 120 and an estimation module 130.

[0136] The judging module 110 is configured to judge the working state of the battery.

[0137] The calibration module 120 is configured to, when the working state is the static state, calibrate the open circuit voltage of the battery according to the working temperature of the battery at the current time, and determine the initial battery state of charge according to the calibrated open circuit voltage.

[0138] The estimation module 130 is configured to, when the working state is the dynamic running state, estimate the battery state of charge by using the modified capacity ampere-hour integral method based on the initial battery state of charge, wherein the modified capacity ampere-hour integral method modifies the rated capacity of the battery by using a correction coefficient.

[0139] In this embodiment, the device first judges the working state of the battery by the judging module 110, then calibrates the open circuit voltage of the battery according to the working temperature of the battery at the current time when the working state is the static state by the calibration module 120, and determines the initial battery state of charge according to the calibrated open circuit voltage, and then estimates the battery state of charge by using the modified capacity ampere-hour integral method based on the initial battery state of charge when the working state is the dynamic running state by the estimation module 130, wherein the modified capacity ampere-hour integral method modifies the rated capacity of the battery by using a correction coefficient, and the above process is repeated until the life cycle of the battery ends.

[0140] The embodiment provides a battery management system, which can eliminate the accumulated error of the ampere-hour integral method for battery state of charge estimation, and effectively improves the estimation accuracy of SOC.

[0141] Further, the judging module 110 comprises:

[0142] The monitoring submodule is configured to monitor the current value of the battery, the voltage value of the battery and the working temperature of the battery in real time.

[0143] The judging submodule is configured to judge the working state of the battery according to the current value of the battery and the change trend of the voltage value of the battery and the working temperature of the battery within a preset time length.

[0144] On the basis of the above optimization, the calibration module 120 comprises a first calibration submodule and a second calibration submodule.

[0145] The first calibration submodule comprises:

[0146] The first acquisition unit is configured to acquire the working temperature and the open circuit voltage value of the battery at the current time.

[0147] The first calibration unit is configured to determine an initial battery state of charge according to the current time battery operating temperature and open circuit voltage value by a double-input model, wherein the double-input model represents a fixed function relationship between the open circuit voltage and the battery operating temperature and the battery state of charge.

[0148] The second calibration sub-module includes:

[0149] The second acquisition unit is configured to acquire an ambient temperature and an open circuit voltage value at a current time.

[0150] The second calibration unit is configured to acquire the initial battery state of charge according to the current time ambient temperature and open circuit voltage value by searching a three-dimensional mapping relationship table, wherein the three-dimensional mapping relationship table is established based on the open circuit voltage of the battery under different ambient temperatures and different battery states of charge.

[0151] Based on the above technical solution, the correction coefficient includes a temperature correction coefficient, a cycle number correction coefficient, and a charge-discharge current ratio correction coefficient.

[0152] Based on the above optimization, the estimation module 130 includes:

[0153] The first determination sub-module is configured to determine the temperature correction coefficient according to the real-time temperature of the battery by a temperature correction relationship.

[0154] The second determination sub-module is configured to determine the cycle number correction coefficient according to the current cycle number of the battery by a cycle number correction relationship.

[0155] The third determination sub-module is configured to determine the charge-discharge current ratio correction coefficient according to the real-time current of the battery by a charge-discharge current ratio correction relationship.

[0156] The correction sub-module is configured to correct the rated capacity of the battery according to the temperature correction coefficient, the cycle number correction coefficient, and the charge-discharge current ratio correction coefficient.

[0157] The above battery state of charge estimation device can execute the battery state of charge estimation method provided by any embodiment of the present application, and has the corresponding function modules and beneficial effects of the execution method.

[0158] Embodiment six

[0159] Figure 7 A structural schematic diagram of a battery-powered device 10 that can be used to implement embodiments of the present application is shown. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0160] As Figure 7As shown, the battery-powered device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the battery-powered device 10 can also be stored in the RAM 13. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0161] Various components in the battery-powered device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, speakers, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the battery-powered device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0162] The processor 11 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the method of estimating the state of charge of a battery.

[0163] In some embodiments, the method of estimating the state of charge of a battery can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the battery-powered device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method of estimating the state of charge of a battery described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the method of estimating the state of charge of a battery by any other appropriate means, such as by means of firmware.

[0164] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system on a chip systems (SOCs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0165] In some embodiments, the XX method can be implemented as a computer program tangibly embodied in a computer program product, the computer program being executed by a processor to implement the XX method of the present application, the computer program product can be understood to be a software product that mainly realizes the solution thereof through the computer program. The computer program for implementing the method of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus, so that the computer programs make the functions / operations specified in the flowcharts and / or block diagrams be implemented when executed by the processor. The computer programs can be executed entirely on a machine, partially on a machine, partially on a machine as a separate software package and partially on a remote machine, or entirely on a remote machine or server.

[0166] In the context of the present application, a computer readable storage medium can be a tangible medium that can contain or store the computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the above. Alternatively, the computer readable storage medium can be a machine readable signal medium. More specific examples of the machine readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disc read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0167] To provide for interaction with a user, the systems and techniques described here can be implemented on a battery-powered device having a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the battery-powered device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0168] The systems and techniques described here can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0169] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0170] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0171] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A method of estimating a state of charge of a battery, characterized by, The method comprises: judging the working state of the battery; when the working state is a static state, calibrating the open circuit voltage of the battery according to the working temperature of the battery at the current time, and determining the initial battery state of charge according to the calibrated open circuit voltage; when the working state is a dynamic running state, estimating the battery state of charge by using the modified capacity ampere-hour integral method based on the initial battery state of charge, wherein the modified capacity ampere-hour integral method modifies the rated capacity of the battery by using a correction coefficient; returning to judging the working state of the battery until the life cycle of the battery ends.

2. The method of claim 1, wherein, The judgment of the working state of the battery comprises: real-time monitoring of the current value of the battery, the voltage value of the battery and the working temperature of the battery; judging the working state of the battery according to the current value of the battery and the change trend of the voltage value of the battery and the working temperature of the battery within a preset time length.

3. The method of claim 1, wherein, Calibrating the open circuit voltage of the battery according to the working temperature of the battery at the current time, and determining the initial battery state of charge according to the calibrated open circuit voltage, comprises: obtaining the working temperature and open circuit voltage value of the battery at the current time; determining the initial battery state of charge by using a double-input model according to the working temperature and open circuit voltage value of the battery at the current time, wherein the double-input model represents the fixed function relationship between the open circuit voltage and the working temperature of the battery and the battery state of charge.

4. The method of claim 1, wherein, Calibrating the open circuit voltage of the battery according to the ambient temperature at the current time, and determining the initial battery state of charge according to the calibrated open circuit voltage, comprises: obtaining the ambient temperature and open circuit voltage value at the current time; obtaining the initial battery state of charge by looking up a three-dimensional mapping relationship table according to the ambient temperature and open circuit voltage value at the current time, wherein the three-dimensional mapping relationship table is established based on the open circuit voltage of the battery under different ambient temperatures and different battery states of charge.

5. The method according to any one of claims 1 to 4, characterized in that, The correction coefficient comprises a temperature correction coefficient, a cycle number correction coefficient and a charge-discharge current ratio correction coefficient.

6. The method of claim 5, wherein, The modified capacity ampere-hour integral method modifies the rated capacity of the battery by using a correction coefficient, comprising: determining the temperature correction coefficient by using a temperature correction relationship according to the real-time temperature of the battery; determining the cycle number correction coefficient by using a cycle number correction relationship according to the current cycle number of the battery; determining the charge-discharge current ratio correction coefficient by using a charge-discharge current ratio correction relationship according to the real-time current of the battery; modifying the rated capacity of the battery according to the temperature correction coefficient, the cycle number correction coefficient and the charge-discharge current ratio correction coefficient.

7. A battery management system, characterized by, The battery management system comprises: a judgment module for judging the working state of the battery; a calibration module for calibrating the open circuit voltage of the battery according to the working temperature of the battery at the current time when the working state is a static state, and determining the initial battery state of charge according to the calibrated open circuit voltage; an estimation module for estimating the battery state of charge by using the modified capacity ampere-hour integral method based on the initial battery state of charge when the working state is a dynamic running state, wherein the modified capacity ampere-hour integral method modifies the rated capacity of the battery by using a correction coefficient.

8. A battery powered device, characterized in that The battery powered device comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the method of estimating the state of charge of a battery according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a processor to implement the method of estimating the state of charge of a battery according to any one of claims 1-6 when executed by the processor.

10. A computer program product, characterised in that, The computer program product comprises a computer program which, when executed by a processor, implements the method of estimating the state of charge of a battery according to any one of claims 1-6.

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