On-line monitoring method and device for capacity fading of battery array of energy storage device

Abstract

The invention relates to an energy storage device battery array capacity recession online monitoring method and device, and the method comprises the steps: collecting the basic data of a battery array, and screening an initial charging interval and an initial discharging interval according to the current data; screening out an effective charging interval and an effective discharging interval according to the initial charging interval and the initial discharging interval; screening out an approximate constant-current charging interval and an approximate constant-current discharging interval according to the effective charging interval and the effective discharging interval; screening a large SOC change charging interval and a large SOC change discharging interval according to the approximate constant-current charging interval and the approximate constant-current discharging interval; calculating an available charging capacity according to the large SOC change charging interval, and calculating an available discharging capacity according to the large SOC change discharging interval; and calculating the capacity recession degree of the battery array according to the available charging capacity and the available discharging capacity. According to the invention, the evaluation granularity of the health degree of the energy storage device can be improved, so that the evaluation result is more comprehensive and accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of energy storage devices, and in particular to an online monitoring method and device for capacity decay of a battery array of an energy storage device. Background Art

[0002] The health of an energy storage device is often based on the overall system, characterizing the degree of attenuation of the overall capacity of the energy storage device. However, an energy storage device is usually composed of multiple battery arrays that work together to store and release electrical energy. The capacity, internal resistance, and consistency of each battery array vary, which not only makes the overall health assessment of the energy storage device inaccurate, but also fails to reflect the health of each battery array.

[0003] The lack of online evaluation methods for the available capacity of battery arrays has become a shortcoming that affects the service life and reliability of energy storage devices. How to use the existing collected data to evaluate the health of each battery array is the key to improving the operating performance of energy storage devices. In order to independently evaluate the available battery capacity of a single battery array online, more sophisticated monitoring and evaluation methods need to be introduced. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for online monitoring of capacity decay of a battery array of an energy storage device, which can improve the granularity of assessment of the health of the energy storage device and make the assessment result more comprehensive and accurate.

[0005] The technical solution adopted by the present invention to solve the technical problem is: to provide an online monitoring method for capacity decay of a battery array of an energy storage device, comprising the following steps:

[0006] Collecting basic data of the battery array, the basic data including current data and state of charge data, and screening an initial charging interval and an initial discharging interval according to the current data;

[0007] Filter out an effective charging interval according to the charging current data at each moment in the initial charging interval, and filter out an effective discharging interval according to the discharging current data at each moment in the initial discharging interval;

[0008] Screening out an approximate constant current charging interval based on the charging current data at each moment in the effective charging interval, and screening out an approximate constant current discharging interval based on the discharging current data at each moment in the effective discharging interval;

[0009] The charging interval with large SOC variation is selected based on the charging state of charge data at each moment in the approximately constant current charging interval, and the discharging interval with large SOC variation is selected based on the discharging state of charge data at each moment in the approximately constant current discharging interval;

[0010] The available charging capacity is calculated based on the charging current data and charging state of charge data in the charging interval with large SOC changes, and the available discharging capacity is calculated based on the discharging current data and discharging state of charge data in the discharging interval with large SOC changes;

[0011] The capacity decay degree of the battery array is calculated based on the available charge capacity and the available discharge capacity.

[0012] The screening of the initial charging interval and the initial discharging interval according to the current data is specifically: allocating basic data with current data less than 0 to the initial charging interval, and allocating basic data with current data greater than 0 to the initial discharging interval.

[0013] The effective charging interval is selected based on the charging current data at each moment in the initial charging interval, and the effective discharging interval is selected based on the discharging current data at each moment in the initial discharging interval, specifically:

[0014] Compare the charging current data at each moment in the initial charging interval with the charging current screening threshold, and assign basic data whose absolute value of the charging current data is greater than or equal to the charging current screening threshold to the effective charging interval;

[0015] The discharge current data at each moment in the initial discharge interval are compared with the discharge current threshold, and the basic data whose discharge current data is greater than or equal to the discharge current threshold is allocated to the effective discharge interval.

[0016] The method of selecting an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval and selecting an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval is specifically as follows:

[0017] Calculate the difference between the charging current at the first moment and the charging current at the nth moment in the effective charging interval, and divide the difference by the charging current at the first moment. When the absolute value of the result is less than or equal to the charging current fluctuation threshold, the basic data corresponding to the charging current is assigned to the approximate constant current charging interval; when the absolute value of the result is greater than the charging current fluctuation threshold, the charging current at the nth moment is assigned to the approximate constant current charging interval. ch,n As the starting time point of the next effective charging interval;

[0018] Calculate the difference between the discharge current at the first moment and the discharge current at the nth moment in the effective discharge interval, and divide the difference by the discharge current at the first moment. When the absolute value of the result is less than or equal to the discharge current fluctuation threshold, the basic data corresponding to the discharge current data is allocated to the approximate constant current discharge interval; when the absolute value of the result is greater than the discharge current fluctuation threshold, the charging current at the nth moment is used as the starting time point of the next effective discharge interval.

[0019] The method of selecting a charging interval with a large SOC change according to the charging state of charge data at each moment in the approximately constant current charging interval and selecting a discharging interval with a large SOC change according to the discharging state of charge data at each moment in the approximately constant current discharging interval is specifically as follows:

[0020] Calculate the difference between the charging state of charge at the first moment and the charging state of charge at the last moment in the approximate constant current charging interval, and when the absolute value of the result is greater than the charging state of charge data fluctuation threshold, allocate the basic data corresponding to the charging state of charge data to the large SOC change charging interval;

[0021] The difference between the discharge state of charge at the first moment and the discharge state of charge at the last moment in the approximate constant current discharge interval is calculated. When the absolute value of the result is greater than the discharge state of charge data fluctuation threshold, the basic data corresponding to the discharge state of charge data is allocated to the large SOC change discharge interval.

[0022] The available charging capacity is expressed as: C j″,N =[C r,j″ ,N], the available discharge capacity is expressed as: D k″,M =[D r,k″ ,M], where C j″,N is the expression of available charging capacity in the j″th large SOC change charging interval, C r,j″ is the available charging capacity of the j″th large SOC change charging interval, expressed as: i ch,t is the charging current data at time t in the j″th large SOC change charging interval, is the first moment in the j″th large SOC change charging interval, t n″ is the last moment in the j″th large SOC change charging interval, is the charging state of charge data at the first moment in the j″th large SOC change charging interval, is the charging state of charge data at the last moment in the j″th large SOC change charging interval, N is the evaluation time of the available charging capacity; D k″,M is the expression of the available discharge capacity in the k″th large SOC change discharge interval, D r,k″ is the available discharge capacity of the k″th large SOC change discharge interval, expressed as: i dis,t is the discharge current data at time t in the k″th large SOC change discharge interval, is the first moment in the k″th large SOC change discharge interval, t m″ is the last moment in the k″th large SOC change charging interval, is the discharge state data at the first moment in the k″th large SOC change discharge interval, is the discharge state data at the last moment in the k″th large SOC change discharge interval, and M is the evaluation time of the available discharge capacity.

[0023] The capacity decay degree of the battery array is calculated based on the available charging capacity and the available discharging capacity, specifically: the average value of all available charging capacities in a preset period is subtracted from the average value of all available discharging capacities in a preset period to obtain an average difference, and then the average difference is divided by the average value of all available charging capacities in the preset period to obtain the capacity decay degree of the battery array.

[0024] The technical solution adopted by the present invention to solve the technical problem is: to provide an online monitoring device for capacity decay of a battery array of an energy storage device, comprising:

[0025] A first screening module is used to collect basic data of the battery array, the basic data including current data and state of charge data, and screen the initial charging interval and the initial discharging interval according to the current data;

[0026] A second screening module, used to screen out effective charging intervals according to charging current data at each moment in the initial charging interval, and to screen out effective discharging intervals according to discharging current data at each moment in the initial discharging interval;

[0027] A third screening module, used to screen out an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval, and to screen out an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval;

[0028] A fourth screening module, for screening out a large SOC change charging interval according to the charging state of charge data at each moment in the approximately constant current charging interval, and screening out a large SOC change discharging interval according to the discharging state of charge data at each moment in the approximately constant current discharging interval;

[0029] An available capacity calculation module is used to calculate the available charging capacity according to the charging current data and the charging state of charge data in the charging interval with large SOC changes, and to calculate the available discharging capacity according to the discharging current data and the discharging state of charge data in the discharging interval with large SOC changes;

[0030] The capacity decay calculation module is used to calculate the capacity decay of the battery array according to the available charging capacity and the available discharging capacity.

[0031] The technical solution adopted by the present invention to solve its technical problem is: to provide an electronic device, including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the above-mentioned method for online monitoring capacity degradation of a battery array of an energy storage device are implemented.

[0032] The technical solution adopted by the present invention to solve its technical problem is: providing a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned energy storage device battery array capacity degradation online monitoring method are implemented.

[0033] Beneficial Effects

[0034] Due to the adoption of the above-mentioned technical solution, the present invention has the following advantages and positive effects compared with the prior art: The present invention can independently evaluate the available charge and discharge capacity of the battery array, improve the granularity of the assessment of the health of the energy storage device, and make the assessment result more comprehensive and accurate. The present invention proposes a capacity decay index for the battery array based on the difference in charge and discharge capacity, quantifies the decay performance of the battery array, and promotes the improvement of the overall life of the energy storage device. The present invention selects a charge and discharge interval with large SOC changes to reduce the available capacity assessment error caused by SOC accuracy. The present invention utilizes existing collected data without adding additional data collection costs, and has strong portability and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of a method for online monitoring capacity decay of a battery array of an energy storage device according to a first embodiment of the present invention;

[0036] Figure 2 Schematic diagram of calculation results of charging capacity and discharging capacity in an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The present invention will be further described below in conjunction with specific embodiments. It should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms fall within the scope limited by the appended claims of the application equally.

[0038] The first embodiment of the present invention relates to an online monitoring method for capacity decay of a battery array of an energy storage device, such as Figure 1 As shown, the following steps are included:

[0039] Step 1: Collect basic data A of the battery array t , the basic data A t Including current data i t and state of charge data St , and according to the current data i t Filter initial charging interval A ch,t and initial discharge interval A dis,t Among them, the basic data of the battery array A t It can be expressed as: A t =[i t ,S t ], when screening, if the basic data with current data less than 0 is assigned to the initial charging interval, the basic data with current data greater than 0 is assigned to the initial discharging interval, that is, when i t <0, it means the battery array is charging, which is marked as C t =[i ch,t ,S ch,t ] and added to the initial charging interval A ch,t Inside, when i t >0, it means the battery array is discharging, which is marked as D t =[i dis,t ,S dis,t ] and added to the initial discharge interval A dis,t Inside.

[0040] Step 2, according to the initial charging area A ch,t The charging current data at each moment in the interval is used to filter out the effective charging interval, and the initial discharge area A dis,t The effective discharge interval is selected by the discharge current data at each moment in the interval.

[0041] In this step, when screening the effective charging interval, the initial charging interval A ch,t The charging current data at each moment in ch,t Respectively with the charging current screening threshold i ch,int (i ch,int ≥0), and the basic data whose absolute value of charging current data is greater than or equal to the charging current screening threshold is assigned to the effective charging interval, that is, when |i ch,t |≥i ch,int , then it is considered that the charging current data i ch,t Corresponding basic data C t =[i ch,t ,S ch,t ] belongs to the effective charging interval, so it is added to the effective charging interval. Among them, the jth effective charging interval can be marked as in, and They are the charging current data at the first moment t1 and the last moment t n Charging current data at and They are the charging state data at the first time t1 and the last time t n The charging state of charge data at the time.

[0042] In this step, when screening the effective discharge interval, the initial discharge area A dis,t The discharge current data at each moment in the interval i dis,t Respectively with the discharge current threshold i dis,int (i dis,int ≥0), and the basic data whose discharge current data is greater than or equal to the discharge current threshold is assigned to the effective discharge interval, that is, when i dis,t ≥i dis,int , then it is considered that the discharge current data i dis,t Corresponding basic data D t =[i dis,t ,S dis,t ] belongs to the effective discharge interval, so it is added to the effective discharge interval. Among them, the kth effective discharge interval can be marked as in, and are the discharge current data at the first moment t1 and the last moment t m The discharge current data at and are the discharge state data at the first time t1 and the last time t m The discharge state data at the time of discharge.

[0043] Step 3: select an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval, and select an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval.

[0044] In this step, when screening the approximate constant current charging interval, calculate the charging current at the first moment in the effective charging interval The charging current i at the nth moment ch,n The difference is divided by the charging current at the first moment. When the absolute value of the result is less than or equal to the charging current fluctuation threshold Δi ch (0<Δi ch <1), the basic data corresponding to the charging current data is assigned to the approximate constant current charging interval. Taking the calculation of the charging current data at the fourth moment in the effective charging interval as an example, when The basic data corresponding to the charging current data at the fourth moment Add to the approximate constant current charging range; when Then the charging current data at the fourth moment is used as the starting time point of the next effective charging interval, and the above calculation is performed on it, so that multiple approximate constant current charging intervals can be obtained. Among them, the j′th approximate constant current charging interval is marked as in, and are the first moment of the j'th approximate constant current charging interval The charging current data at the last moment t n' Charging current data at and are the first moment of the j′th approximate constant current charging interval The charge state data at the last moment t n' The charging state of charge data at the time.

[0045] In this step, when screening the approximate constant current discharge interval, calculate the discharge current at the first moment in the effective discharge interval The discharge current i at the nth moment dis,n and divide the difference by the discharge current at the first moment. When the absolute value of the result is less than or equal to the discharge current fluctuation threshold Δi dis (0<Δi dis <1), the basic data corresponding to the discharge current data is assigned to the approximate constant current discharge interval. Taking the calculation of the discharge current data at the fourth moment in the effective discharge interval as an example, when The basic data corresponding to the discharge current data at the fourth moment Added to the approximate constant current discharge interval, when The discharge current data at the fourth moment is used as the starting time point of the next effective discharge interval, and the above calculation is performed, so that multiple approximate constant current discharge intervals can be obtained. Among them, the k'th approximate constant current discharge interval segment is marked as in, and are the first moment of the k′th approximate constant current discharge interval The charging current data at the last moment t m' Charging current data at and are the first moment of the k′th approximate constant current discharge interval The discharge state data at the last moment t m′ The discharge state data at the time of discharge.

[0046] Step 4: filter out a charging interval with a large SOC change based on the charging state of charge data at each moment in the approximately constant current charging interval, and filter out a discharging interval with a large SOC change based on the discharging state of charge data at each moment in the approximately constant current discharging interval.

[0047] In this step, when the large SOC change charging interval is screened out, the charging state of charge at the first moment in the approximate constant current charging interval is calculated. The state of charge at the last moment When the absolute value of the result is greater than the charge state data fluctuation threshold ΔS ch , then the basic data corresponding to the charging state of charge data is allocated to the large SOC change charging interval. Taking the calculation of the charging state of charge data at the first moment in the approximate constant current charging area as an example, when The basic data corresponding to the charging state of charge data at the first moment Add to the large SOC change charging interval. Among them, the j'th large SOC change charging interval is marked as in, and They are the first moment of the j”th large SOC change charging interval. The charging current data at the last moment t n” Charging current data at and They are the first moment of the j”th large SOC change charging interval The state of charge data at the last moment t n” State of charge data at the time.

[0048] When the large SOC change discharge interval is screened, the discharge state of charge at the first moment in the approximate constant current discharge interval is calculated With the last moment When the absolute value of the result is greater than the discharge state data fluctuation threshold ΔS dis (0<ΔS dis <1), the basic data corresponding to the discharge state data is allocated to the large SOC change discharge interval. Taking the calculation of the discharge state data at the first moment in the approximate constant current charging area as an example, when The basic data corresponding to the discharge state data at the first moment Added to the large SOC change discharge interval. Among them, the kth large SOC change discharge interval is marked as in, and are the first moment of the kth large SOC change discharge interval The discharge current data at the last moment tm” The discharge current data at and are the first moment of the kth large SOC change discharge interval The discharge state data at the last moment t m” The discharge state data at the time of discharge.

[0049] Step 5, calculating the available charging capacity based on the charging current data and the charging state of charge data in the charging interval with a large SOC change, and calculating the available discharging capacity based on the discharging current data and the discharging state of charge data in the discharging interval with a large SOC change.

[0050] In this step, the available charging capacity of the j'th large SOC change charging interval is expressed as: C j″,N =[C r,j″ ,N], where, C j″,N is the expression of available charging capacity in the j″th large SOC change charging interval, C r,j″ is the available charging capacity of the j″th large SOC change charging interval, expressed as: N is the evaluation time of available charging capacity, and N = t″ n is the last moment of the j″th large SOC change charging interval.

[0051] The available discharge capacity of the k″th large SOC change discharge interval is expressed as: D k″,M =[D r,k″ ,M], where D k″,M is the expression of the available discharge capacity in the k″th large SOC change discharge interval, D r,k″ is the available discharge capacity of the k″th large SOC change discharge interval, expressed as: M is the evaluation time of the available discharge capacity, and M = t" m is the last moment of the k″th large SOC change discharge interval.

[0052] Step 6: Calculate the capacity decay degree of the battery array according to the available charging capacity and the available discharging capacity.

[0053] In this step, the capacity decay rate η of the battery array ΔT Calculated according to a certain time period, the calculation method is:

[0054]

[0055] Where T is the last moment in the cycle, x is the number of available charging capacities in the cycle, AVE(C x ) is the average value of x available charge capacities in the cycle, y is the number of available discharge capacities in the cycle, AVE(Dy ) is the average value of y available discharge capacities in the cycle.

[0056] The following is the evaluation result of the available charge and discharge capacity of the battery array of the stationary energy storage device. A total of 201 charging intervals and 192 discharging intervals were screened out. The calculation results of the charge capacity and discharge capacity are as follows: Figure 2 As shown. According to the calculation results, the initial capacity of the battery is about 480Ah. As the battery ages, the battery capacity decays. In the later stage of battery aging, the battery's charge and discharge performance becomes unstable, and the battery charge and discharge capacity fluctuates between 250-350Ah, and finally decays to 300Ah. The charge and discharge capacity of the battery array is also more dispersed, and the capacity decay gradually increases.

[0057] It is not difficult to find that the present invention can independently evaluate the available charge and discharge capacity of the battery array, improve the granularity of the assessment of the health of the energy storage device, and make the assessment results more comprehensive and accurate. The present invention proposes a capacity decay index for the battery array based on the difference in charge and discharge capacity, quantifies the decay performance of the battery array, and promotes the improvement of the overall life of the energy storage device. The present invention selects a charge and discharge interval with large SOC changes to reduce the available capacity assessment error caused by SOC accuracy. The present invention utilizes existing collected data without adding additional data collection costs, and has strong portability and economy.

[0058] A second embodiment of the present invention relates to an online monitoring device for capacity decay of a battery array of an energy storage device, comprising:

[0059] A first screening module is used to collect basic data of the battery array, the basic data including current data and state of charge data, and screen the initial charging interval and the initial discharging interval according to the current data;

[0060] A second screening module, used to screen out effective charging intervals according to charging current data at each moment in the initial charging interval, and to screen out effective discharging intervals according to discharging current data at each moment in the initial discharging interval;

[0061] A third screening module, used to screen out an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval, and to screen out an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval;

[0062] A fourth screening module, for screening out a large SOC change charging interval according to the charging state of charge data at each moment in the approximately constant current charging interval, and screening out a large SOC change discharging interval according to the discharging state of charge data at each moment in the approximately constant current discharging interval;

[0063] An available capacity calculation module is used to calculate the available charging capacity according to the charging current data and the charging state of charge data in the charging interval with large SOC changes, and to calculate the available discharging capacity according to the discharging current data and the discharging state of charge data in the discharging interval with large SOC changes;

[0064] The capacity decay calculation module is used to calculate the capacity decay of the battery array according to the available charging capacity and the available discharging capacity.

[0065] When the first screening module screens the initial charging interval and the initial discharging interval according to the current data, the basic data with current data less than 0 is allocated to the initial charging interval, and the basic data with current data greater than 0 is allocated to the initial discharging interval.

[0066] The second screening module comprises:

[0067] An effective charging interval screening unit, used to compare the charging current data at each moment in the initial charging interval with the charging current screening threshold value, and to allocate basic data whose absolute value of the charging current data is greater than or equal to the charging current screening threshold value to the effective charging interval;

[0068] The effective discharge interval screening unit is used to compare the discharge current data at each moment in the initial discharge interval with the discharge current threshold, and allocate the basic data whose discharge current data is greater than or equal to the discharge current threshold to the effective discharge interval.

[0069] The third screening module comprises:

[0070] Calculate the difference between the charging current at the first moment and the charging current at the nth moment in the effective charging interval, and divide the difference by the charging current at the first moment. When the absolute value of the result is less than or equal to the charging current fluctuation threshold, the basic data corresponding to the charging current is allocated to the approximate constant current charging interval; when the absolute value of the result is greater than the charging current fluctuation threshold, the charging current at the nth moment is used as the starting time point of the next effective charging interval;

[0071] Calculate the difference between the discharge current at the first moment and the discharge current at the nth moment in the effective discharge interval, and divide the difference by the discharge current at the first moment. When the absolute value of the result is less than or equal to the discharge current fluctuation threshold, the basic data corresponding to the discharge current data is allocated to the approximate constant current discharge interval; when the absolute value of the result is greater than the discharge current fluctuation threshold, the charging current at the nth moment is used as the starting time point of the next effective discharge interval.

[0072] The fourth screening module comprises:

[0073] A large SOC change charging interval screening unit is used to calculate the difference between the charging state of charge at the first moment and the charging state of charge at the last moment in the approximate constant current charging interval, and when the absolute value of the result obtained is greater than the charging state of charge data fluctuation threshold, the basic data corresponding to the charging state of charge data is allocated to the large SOC change charging interval;

[0074] The large SOC change discharge interval screening unit is used to calculate the difference between the discharge state of charge at the first moment and the discharge state of charge at the last moment in the approximate constant current discharge interval. When the absolute value of the result is greater than the discharge state of charge data fluctuation threshold, the basic data corresponding to the discharge state of charge data is allocated to the large SOC change discharge interval.

[0075] The available charging capacity is expressed as: C j″,N =[C r,j″ ,N], the available discharge capacity is expressed as: D k″,M =[D r,k″ ,M], where C j″,N is the expression of available charging capacity in the j″th large SOC change charging interval, C r,j″ is the available charging capacity of the j″th large SOC change charging interval, expressed as: i ch,t is the charging current data at time t in the j″th large SOC change charging interval, is the first moment in the j″th large SOC change charging interval, t n″ is the last moment in the j″th large SOC change charging interval, is the charging state of charge data at the first moment in the j″th large SOC change charging interval, is the charging state of charge data at the last moment in the j″th large SOC change charging interval, N is the evaluation time of the available charging capacity; D k″,M is the expression of the available discharge capacity in the k″th large SOC change discharge interval, D r,k″ is the available discharge capacity of the k″th large SOC change discharge interval, expressed as: i dis,t is the discharge current data at time t in the k″th large SOC change discharge interval, is the first moment in the k″th large SOC change discharge interval, t m″ is the last moment in the k″th large SOC change charging interval, is the discharge state data at the first moment in the k″th large SOC change discharge interval, is the discharge state data at the last moment in the k″th large SOC change discharge interval, and M is the evaluation time of the available discharge capacity.

[0076] When the capacity decay calculation module calculates the capacity decay of the battery array based on the available charging capacity and the available discharging capacity, the average value of all available charging capacities in a preset period is subtracted from the average value of all available discharging capacities in a preset period to obtain an average difference, and then the average difference is divided by the average value of all available charging capacities in the preset period to obtain the capacity decay of the battery array.

[0077] A third embodiment of the present invention relates to an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the first embodiment of the method for online monitoring capacity degradation of a battery array of an energy storage device.

[0078] The fourth embodiment of the present invention relates to a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the method for online monitoring capacity degradation of a battery array of an energy storage device of the first embodiment are implemented.

[0079] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) that contain computer-usable program code.

[0080] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0081] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction method, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0082] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0083] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. An online monitoring method for capacity decay of a battery array of an energy storage device, characterized in that: The following steps are involved: Collecting basic data of the battery array, the basic data including current data and state of charge data, and screening an initial charging interval and an initial discharging interval according to the current data; Filter out an effective charging interval according to the charging current data at each moment in the initial charging interval, and filter out an effective discharging interval according to the discharging current data at each moment in the initial discharging interval; Screening out an approximate constant current charging interval based on the charging current data at each moment in the effective charging interval, and screening out an approximate constant current discharging interval based on the discharging current data at each moment in the effective discharging interval; The charging interval with large SOC variation is selected based on the charging state of charge data at each moment in the approximately constant current charging interval, and the discharging interval with large SOC variation is selected based on the discharging state of charge data at each moment in the approximately constant current discharging interval; The available charging capacity is calculated based on the charging current data and charging state of charge data in the charging interval with large SOC changes, and the available discharging capacity is calculated based on the discharging current data and discharging state of charge data in the discharging interval with large SOC changes; The capacity decay degree of the battery array is calculated based on the available charge capacity and the available discharge capacity.

2. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The screening of the initial charging interval and the initial discharging interval according to the current data is specifically: allocating basic data with current data less than 0 to the initial charging interval, and allocating basic data with current data greater than 0 to the initial discharging interval.

3. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The effective charging interval is selected based on the charging current data at each moment in the initial charging interval, and the effective discharging interval is selected based on the discharging current data at each moment in the initial discharging interval, specifically: Compare the charging current data at each moment in the initial charging interval with the charging current screening threshold, and assign basic data whose absolute value of the charging current data is greater than or equal to the charging current screening threshold to the effective charging interval; The discharge current data at each moment in the initial discharge interval are compared with the discharge current threshold, and the basic data whose discharge current data is greater than or equal to the discharge current threshold is allocated to the effective discharge interval.

4. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The method of selecting an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval and selecting an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval is specifically as follows: Calculate the difference between the charging current at the first moment and the charging current at the nth moment in the effective charging interval, and divide the difference by the charging current at the first moment. When the absolute value of the result is less than or equal to the charging current fluctuation threshold, allocate the basic data corresponding to the charging current at the nth moment to the approximate constant current charging interval; When the absolute value of the result is greater than the charging current fluctuation threshold, the charging current at the nth moment is taken as the starting time point of the next valid charging interval; Calculate the difference between the discharge current at the first moment and the discharge current at the nth moment in the effective discharge interval, and divide the difference by the discharge current at the first moment. When the absolute value of the result is less than or equal to the discharge current fluctuation threshold, allocate the basic data corresponding to the discharge current at the nth moment to the approximate constant current discharge interval; When the absolute value of the obtained result is greater than the discharge current fluctuation threshold, the discharge current at the nth moment is taken as the starting time point of the next effective charging interval.

5. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The method of selecting a charging interval with a large SOC change according to the charging state of charge data at each moment in the approximately constant current charging interval and selecting a discharging interval with a large SOC change according to the discharging state of charge data at each moment in the approximately constant current discharging interval is specifically as follows: Calculate the difference between the charging state of charge at the first moment and the charging state of charge at the last moment in the approximate constant current charging interval, and when the absolute value of the result is greater than the charging state of charge data fluctuation threshold, allocate the basic data corresponding to the charging state of charge data to the large SOC change charging interval; The difference between the discharge state of charge at the first moment and the discharge state of charge at the last moment in the approximate constant current discharge interval is calculated. When the absolute value of the result is greater than the discharge state of charge data fluctuation threshold, the basic data corresponding to the discharge state of charge data is allocated to the large SOC change discharge interval.

6. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The available charging capacity is expressed as: C j″,N =[C r,j″ ,N], the available discharge capacity is expressed as: D k″,M =[D r,k″ ,M], where C j″,N is the expression of available charging capacity in the j″th large SOC change charging interval, C r,j″ is the available charging capacity of the j″th large SOC change charging interval, expressed as: i ch,t is the charging current data at time t in the j″th large SOC change charging interval, is the first moment in the j″th large SOC change charging interval, t n″ is the last moment in the j″th large SOC change charging interval, is the charging state of charge data at the first moment in the j″th large SOC change charging interval, is the charging state of charge data at the last moment in the j″th large SOC change charging interval, N is the evaluation time of the available charging capacity; D k″,M is the expression of the available discharge capacity in the k″th large SOC change discharge interval, D r,k″ is the available discharge capacity of the k″th large SOC change discharge interval, expressed as: i dis,t is the discharge current data at time t in the k″th large SOC change discharge interval, is the first moment in the k″th large SOC change discharge interval, t m″ is the last moment in the k″th large SOC change charging interval, is the discharge state data at the first moment in the k″th large SOC change discharge interval, is the discharge state data at the last moment in the k″th large SOC change discharge interval, and M is the evaluation time of the available discharge capacity.

7. The method for online monitoring of capacity decay of a battery array of an energy storage device according to claim 1, characterized in that: The capacity decay degree of the battery array is calculated based on the available charging capacity and the available discharging capacity, specifically: the average value of all available charging capacities in a preset period is subtracted from the average value of all available discharging capacities in a preset period to obtain an average difference, and then the average difference is divided by the average value of all available charging capacities in the preset period to obtain the capacity decay degree of the battery array.

8. An online monitoring device for capacity decay of a battery array of an energy storage device, characterized in that: include: A first screening module is used to collect basic data of the battery array, the basic data including current data and state of charge data, and screen the initial charging interval and the initial discharging interval according to the current data; A second screening module, used to screen out effective charging intervals according to charging current data at each moment in the initial charging interval, and to screen out effective discharging intervals according to discharging current data at each moment in the initial discharging interval; A third screening module, used to screen out an approximate constant current charging interval according to the charging current data at each moment in the effective charging interval, and to screen out an approximate constant current discharging interval according to the discharging current data at each moment in the effective discharging interval; A fourth screening module, for screening out a large SOC change charging interval according to the charging state of charge data at each moment in the approximately constant current charging interval, and screening out a large SOC change discharging interval according to the discharging state of charge data at each moment in the approximately constant current discharging interval; An available capacity calculation module is used to calculate the available charging capacity according to the charging current data and the charging state of charge data in the charging interval with large SOC changes, and to calculate the available discharging capacity according to the discharging current data and the discharging state of charge data in the discharging interval with large SOC changes; The capacity decay calculation module is used to calculate the capacity decay of the battery array according to the available charging capacity and the available discharging capacity.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for online monitoring capacity degradation of a battery array of an energy storage device as claimed in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for online monitoring capacity degradation of a battery array of an energy storage device as claimed in any one of claims 1 to 8 are implemented.

Images