An intelligent detection method and system for storage battery faults

Abstract

The present invention relates to the technical field of measuring electrical variables, and specifically relates to an intelligent detection method and system for battery faults. The method includes: determining the aging degree of a single battery by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single battery in a battery pack; correcting the current voltage value of the single battery by using the terminal voltage data, capacity data, and aging degree of the single battery; correcting the capacity value by using the capacity data and ambient temperature data of the single battery; determining the voltage deviation degree and capacity deviation degree between the corrected voltage value and corrected capacity value and the corresponding average voltage and average capacity in the series circuit where the single battery is located; determining the fault abnormality degree of the single battery by using the voltage deviation degree and capacity deviation degree, and determining the faulty battery by using the fault abnormality degree. Through the intelligent detection method for battery faults, the accuracy of battery abnormality detection is improved, and the faulty battery with fault abnormalities can be more accurately located.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring electrical variables, and particularly to an intelligent detection method and system for battery failures. Background Art

[0002] In a photovoltaic system, as an important energy storage device, the battery is in the harshest working environment and has a relatively high failure rate. Therefore, the battery is not only an important device in the photovoltaic system but also the weakest link. The batteries in a photovoltaic system are generally a battery pack composed of multiple single batteries connected in series and parallel. Such a battery system operating in a battery pack can better store and convert electrical energy.

[0003] The battery is a key energy storage device in the photovoltaic system. As the battery is used, the geometric structure of the battery plates inevitably gradually changes, the agglomerate structure of its active substances gradually decays during the charge and discharge process, and there are differences in the physical structure and electrolyte density of each single battery, resulting in inconsistencies in the capacity and terminal voltage of the batteries, causing unbalanced failures between the batteries, which will lead to abnormal operation of the photovoltaic system. For example, the series battery pack is undercharged, resulting in the system being unable to supply power normally, or the charging currents of the parallel battery packs are not equal, the high-voltage battery pack is undercharged, and the low-voltage battery pack is overcharged, accelerating the damage of the two groups of batteries, etc. Therefore, it is necessary to detect the unbalanced failures between the batteries. However, the current battery failure detection technology is difficult to accurately locate the single battery with abnormalities, so as to replace it and protect the normal operation of the entire energy storage and photovoltaic system. Summary of the Invention

[0004] In order to solve the technical problem of how to accurately locate a single battery with abnormal failures in a battery pack, the purpose of the present invention is to provide an intelligent detection method and system for battery failures, and the specific technical solutions adopted are as follows:

[0005] The present invention provides an intelligent detection method for battery failures, and the method includes:

[0006] Determine the aging degree of a single battery by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single battery in the battery pack;

[0007] Correct the current voltage value of the single battery by using the terminal voltage data, capacity data, and aging degree of the single battery to obtain the current corrected voltage value;

[0008] Correct the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and ambient temperature data of the single battery to obtain the current corrected capacity value;

[0009] Determine the voltage deviation degree and capacity deviation degree between the current corrected voltage value and the current corrected capacity value and the corresponding average voltage and average capacity in the series circuit where the single cell is located, respectively;

[0010] Use the voltage deviation degree and capacity deviation degree to determine the fault abnormality degree of the single cell, and use the fault abnormality degree to determine the faulty cell.

[0011] Further, the steps of determining the aging degree of a single cell by using the charge-discharge cycle times, capacity data, and ambient temperature data of the single cell in the battery pack include:

[0012] Use the capacity value differences between adjacent charge-discharge cycle periods of the single cell in the battery pack under the same charging condition and / or the same discharging condition respectively to determine the capacity attenuation coefficient of the single cell;

[0013] Use the capacity attenuation coefficient, the charge-discharge cycle times, and the difference between the real-time temperature value of the environment where the single cell is located and the standard ambient temperature to determine the aging degree of the single cell.

[0014] Further, the steps of determining the capacity attenuation coefficient of the single cell by using the capacity value differences between adjacent charge-discharge cycle periods of the single cell in the battery pack under the same charging condition and / or the same discharging condition respectively include:

[0015] Determine the first capacity value difference after the preset discharging duration between adjacent charge-discharge cycle periods of the single cell;

[0016] Determine the second capacity value difference when the single cell is fully charged between adjacent charge-discharge cycle periods;

[0017] Determine the variance of the absolute differences between all the lower limit capacity measurement values of the single cell and the preset lower limit capacity standard value;

[0018] Use the first capacity value difference, the second capacity value difference, and the variance of the absolute differences to calculate the capacity attenuation coefficient of the single cell.

[0019] Further, the steps of correcting the current voltage value of the single cell to obtain the current corrected voltage value by using the terminal voltage data, capacity data, and aging degree of the single cell include:

[0020] Use the terminal voltage differences corresponding to the same data order between any two different charge-discharge cycle periods of the single cell to determine the overall instability degree of the terminal voltage of the single cell;

[0021] Determine the inverse normalization value of the Pearson correlation coefficient between the terminal voltage data and the capacity data;

[0022] The current voltage value of a single cell is corrected using the overall instability degree, the inverse normalization value, and the aging degree to obtain the current corrected voltage value.

[0023] Further, the steps of determining the overall instability degree of the terminal voltage of a single cell using the terminal voltage difference corresponding to the same data order between any two different charge-discharge cycle periods of the single cell include:

[0024] Determining the instability degree of the terminal voltage of the single cell for the two different charge-discharge cycle periods using the terminal voltage difference corresponding to the same data order between any two different charge-discharge cycle periods of the single cell and the number of terminal voltages within any charge-discharge cycle period;

[0025] Calculating the overall instability degree of the terminal voltage of the single cell using each instability degree and the number of cycles of all charge-discharge cycle periods.

[0026] Further, the steps of correcting the reference capacity value corresponding to the current voltage value in the associated reference data using the capacity data and the ambient temperature data of the single cell to obtain the current corrected capacity value include:

[0027] Determining the temperature difference between the ambient temperature value corresponding to the last capacity measurement value in the capacity data and the standard ambient temperature;

[0028] Correcting the reference capacity value corresponding to the current voltage value in the associated reference data using the preset capacity ambient coefficient and the temperature difference to obtain the current corrected capacity value.

[0029] Further, the average voltage includes the average value of the current corrected voltage values of all cells in the series circuit where the single cell is located; the average capacitance includes the average value of the current corrected capacity values of all cells in the series circuit where the single cell is located;

[0030] The steps of determining the fault abnormality degree of the single cell using the voltage deviation degree and the capacity deviation degree include:

[0031] Calculating the fault abnormality degree of the single cell using the voltage deviation degree, the capacity deviation degree, and the preset capacity control error.

[0032] Further, before the steps of determining the fault abnormality degree of the single cell using the voltage deviation degree and the capacity deviation degree, the method further includes:

[0033] Determining the current of the first branch and the current of the second branch in the two parallel branches where the battery pack is located and the absolute current difference between the two branch currents;

[0034] Comparing the absolute current difference with the preset current change threshold to determine whether the battery pack is an abnormal battery pack;

[0035] When the battery pack is determined to be an abnormal battery pack, perform the step of determining the degree of fault abnormality of a single battery using the degree of voltage deviation and the degree of capacity deviation.

[0036] Furthermore, the step of determining the faulty battery using the degree of fault abnormality includes:

[0037] Compare the degree of fault abnormality with a preset abnormality threshold to determine whether a single battery is a faulty battery.

[0038] The present invention also provides an intelligent battery fault detection system, which is used to implement the intelligent battery fault detection method described in any one of the above; the system includes:

[0039] An aging monitoring module, which is used to determine the aging degree of a single battery in the battery pack by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single battery;

[0040] A voltage correction module, which is used to correct the current voltage value of a single battery by using the terminal voltage data, capacity data, and aging degree of the single battery to obtain the current corrected voltage value;

[0041] A capacity correction module, which is used to correct the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and ambient temperature data of the single battery to obtain the current corrected capacity value;

[0042] A deviation calculation module, which is used to determine the degree of voltage deviation and the degree of capacity deviation between the current corrected voltage value and the current corrected capacity value and the corresponding average voltage and average capacity in the series circuit where the single battery is located, respectively;

[0043] A fault location module, which is used to determine the degree of fault abnormality of a single battery by using the degree of voltage deviation and the degree of capacity deviation, and determine the faulty battery by using the degree of fault abnormality.

[0044] The present invention has the following beneficial effects:

[0045] By comprehensively analyzing the charge and discharge cycle times, changes in capacity data, and changes in ambient temperature data of the battery, the present invention determines the aging degree of the battery, and obtains the corrected value of the battery terminal voltage according to the fluctuation of the battery (terminal) voltage data, the similarity between its capacity curve, and the aging degree, reducing the influence of battery aging and the harshness of the ambient temperature on relevant electrical parameters. Furthermore, according to the capacity data, ambient temperature data, and the reference capacity value corresponding to the current voltage value, the corrected value of the battery capacity is obtained, and the fault abnormality analysis of the battery in the corresponding circuit connection mode in the photovoltaic system is fully analyzed, improving the accuracy of detecting the imbalance and abnormality between batteries, and thus being able to more accurately locate the battery with fault abnormality, so as to replace the abnormal battery and realize the normal operation of the energy storage system and the photovoltaic system. Brief Description of the Drawings

[0046] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0047] Figure 1 It is a flowchart of the steps of an intelligent battery fault detection method provided by an embodiment of the present invention;

[0048] Figure 2 It is a refined flowchart of step S1 in an intelligent battery fault detection method provided by an embodiment of the present invention;

[0049] Figure 3 It is a refined flowchart of step S2 in an intelligent battery fault detection method provided by an embodiment of the present invention;

[0050] Figure 4 It is a refined flowchart of step S3 in an intelligent battery fault detection method provided by an embodiment of the present invention;

[0051] Figure 5 It is a schematic structural diagram of the hardware operating environment of an intelligent battery fault detection device related to the embodiment solution of the present invention;

[0052] Figure 6 It is a schematic framework diagram of an intelligent battery fault detection system related to the embodiment solution of the present invention. Detailed Embodiments

[0053] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following, in combination with the drawings and preferred embodiments, details the specific embodiments, structures, features, and effects of an intelligent battery fault detection method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0054] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0055] The following specifically describes the specific solution of an intelligent battery fault detection method provided by the present invention in combination with the drawings.

[0056] Embodiment 1:

[0057] For an intelligent battery fault detection method provided by the present invention, please refer to Figure 1 , which shows a flowchart of the steps of the intelligent battery fault detection method provided by an embodiment of the present invention.

[0058] The method includes:

[0059] Step S1, determining the aging degree of a single battery by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single battery in the battery pack;

[0060] A battery pack is generally formed by connecting multiple batteries in series.

[0061] Obtain the capacity data of each battery in the battery pack at historical times, and then a capacity curve can be generated; obtain the terminal voltage data of each battery in the battery pack, and then a terminal voltage curve can be generated; obtain the associated reference data of the capacity and terminal voltage of the battery, and then a reference curve can be generated; obtain the charge and discharge cycle times of each battery in the battery pack; obtain the temperature data of the environment where the battery is located and the standard ambient temperature.

[0062] It should be noted that in the battery pack in the scenario of this embodiment, each battery has a separate electronic control unit that can monitor the relevant information of the battery.

[0063] Among them, the capacity curve can be a curve formed by obtaining the capacity values of the most recent 10 working cycle periods through a battery capacity detector. A complete charge and discharge cycle is a working cycle period, so the working cycle period can also be called the charge and discharge cycle period, and the specific working cycle period can be adjusted according to actual needs. The terminal voltage curve of the battery can also be the terminal voltage of the most recent 10 working cycle periods, which is specifically obtained through a voltmeter, and the current value can be obtained through an ammeter. The reference curve of the capacity and terminal voltage of the battery is a reference curve of the capacity and terminal voltage obtained by measuring a normal battery with a battery capacity detector and a voltmeter at the standard ambient temperature. Each terminal voltage corresponds to a unique capacity value. In the coordinate system, different capacity values can be set on the horizontal axis, and the voltage values corresponding to different capacity values can be set on the vertical axis. The temperature data of the environment where the battery is located can be a temperature sequence composed of the ambient temperature values corresponding to 10 working cycle periods with the time unit of days. The standard ambient temperature can be set to 25 degrees Celsius, and it can be adjusted according to needs specifically.

[0064] Specifically, please refer to Figure 2 , step S1 includes:

[0065] Step S11, determining the capacity attenuation coefficient of a single battery by using the capacity value differences between adjacent charge and discharge cycle periods of the single battery in the battery pack under the same charging condition and / or the same discharging condition;

[0066] More specifically, step S11 includes:

[0067] Determine the first capacity value difference between adjacent charge-discharge cycle periods of a single battery after a preset discharge duration;

[0068] Determine the second capacity value difference when a single battery is fully charged between adjacent charge-discharge cycle periods;

[0069] Determine the variance of the absolute differences between all lower limit capacity measurement values of a single battery and a preset lower limit capacity standard value;

[0070] Calculate the capacity attenuation coefficient of the single battery by using the first capacity value difference, the second capacity value difference, and the variance of the absolute differences.

[0071] In step S12, determine the aging degree of the single battery by using the capacity attenuation coefficient, the number of charge-discharge cycles, and the difference between the real-time temperature value of the environment where the single battery is located and the standard environment temperature.

[0072] Since the capacity of the battery will gradually decrease during actual use, with the increase of the number of charge-discharge cycles, the battery capacity will decay significantly, that is, aging occurs, and the change of the environmental temperature will accelerate aging. The aging speed will be more serious in a high-temperature environment than in a normal temperature environment for a long time. To facilitate better analysis of backward batteries (faulty and abnormal batteries), it is necessary to analyze the aging degree of the storage battery.

[0073] Obtain all the maximum capacity values and minimum capacity values in the capacity curve of the i-th battery in the battery pack, and use the capacity curve between adjacent maximum capacity values and minimum capacity values as a working cycle period of the i-th battery.

[0074]

[0075] In the above formula, is the average value of the differences (the first capacity value difference) between all adjacent capacity values after the preset discharge duration in all working cycle periods in the capacity curve of the i-th battery in the battery pack. Here, adjacent can be right adjacent. In this embodiment, the preset duration can be taken as 10 minutes, which can be adjusted specifically; is the number of all maximum capacity values in the capacity curve of the i-th battery in the battery pack, is the absolute difference (the second capacity value difference) between the a-th maximum capacity value and the (a + 1)-th maximum capacity value in the capacity curve of the i-th battery in the battery pack, is the variance of the absolute differences between all minimum capacity values (lower limit capacity measurement values) and the preset lower limit capacity standard value in the capacity curve of the i-th battery in the battery pack. The preset capacity value can be 20%, is the capacity attenuation coefficient of the i-th battery in the battery pack.

[0076] The logic of the above formula: It represents the difference in capacity values after discharging for a period of time in adjacent working cycle periods. If there is no capacity attenuation in the battery, then the capacity is basically the same after working for a period of time in each working cycle. If aging causes capacity attenuation, then the amount of electricity that the battery can store will decrease, and the capacity will change after working for a period of time. The larger it is, the more likely there is capacity attenuation; It represents the difference in capacity when the battery is fully charged in adjacent working cycle periods. The larger this value is, the more serious the capacity attenuation is; It represents the difference between the measured value of the lower limit capacity and the set standard lower limit capacity. The larger this value is, the more serious the over-discharge caused by capacity attenuation of the battery and the more serious the capacity attenuation is.

[0077]

[0078] In the above formula, is the number of charge and discharge cycles of the i-th battery in the battery pack; is a linear normalization function for normalization, is the aging degree of the i-th battery in the battery pack, is the average of the absolute differences between each temperature value (which can be the real-time temperature value in days) in the temperature data of the environment where the i-th battery is located and the standard ambient temperature.

[0079] The logic of the above formula: When the number of charge and discharge cycles of the battery in the battery pack is larger, and at the same time the capacity attenuation coefficient and temperature of the battery change more compared with the standard ambient temperature, it indicates that the aging degree of the battery is more serious. With the repeated charge and discharge cycles, this difference continues to increase, gradually forming a so-called lagging battery, that is, a faulty abnormal battery.

[0080] Step S2, using the terminal voltage data, capacity data, and aging degree of a single battery, correct the current voltage value of the single battery to obtain the current corrected voltage value;

[0081] Specifically, please refer to Figure 3 Step S2 includes:

[0082] Step S21, using the difference in terminal voltage corresponding to the same data order between any two different charge and discharge cycle periods of a single battery, determine the overall instability degree of the terminal voltage of the single battery;

[0083] More specifically, step S21 includes:

[0084] Determine the instability degree of the terminal voltage of a single cell for any two different charge-discharge cycle periods by using the terminal voltage difference corresponding to the same data order between any two different charge-discharge cycle periods of the single cell and the number of terminal voltages within any charge-discharge cycle period;

[0085] Calculate the overall instability degree of the terminal voltage of the single cell by using each instability degree and the number of cycles of all charge-discharge cycle periods.

[0086] Step S22, determine the inverse normalization value of the Pearson correlation coefficient between the terminal voltage data and the capacity data;

[0087] Step S23, correct the current voltage value of the single cell by using the overall instability degree, the inverse normalization value, and the aging degree to obtain the current corrected voltage value.

[0088] As the storage battery ages, the energy stored and released through chemical reactions inside the storage battery will decrease due to the gradual loss of the active substances inside the battery, and the amount of active substances available for reaction decreases, resulting in the terminal voltage of the storage battery dropping too fast during discharge and the terminal voltage curve tending to be unstable. If the influence of the aging degree on the terminal voltage is not analyzed, it will lead to errors when analyzing the lagging battery based on the terminal voltage subsequently. Ideally, the relevant electrical parameters can be determined according to the reference curve of the capacity and the terminal voltage. Knowing the voltage can determine the capacity, and knowing the capacity can determine the voltage. At the same time, if the aging degree of the battery and the more unstable the terminal voltage curve are, the more serious the aging damage to the battery is, and the more the current voltage value should be increased.

[0089] Take the terminal voltage curve segment corresponding to each working cycle period of the i-th battery in the battery pack on the terminal voltage curve of the i-th battery as the terminal voltage working cycle period of the i-th battery. Since the capacity and the terminal voltage of the storage battery are relatively closely related, when the capacity of the storage battery is lower, its terminal voltage is also lower. The above analyzed a working cycle period of the storage battery based on the capacitance. Here, the working cycle period is corresponding on the terminal voltage curve, and the change of the terminal voltage under the same working cycle period is analyzed, and then the corrected voltage value is determined to more accurately judge the lagging battery. For example, the working cycle period is from the 5th second to the 10th second, and the voltage curve segment from the 5th second to the 10th second is obtained on the terminal voltage curve as a terminal voltage working cycle period.

[0090]

[0091] In the above formula, is the number of terminal voltages within any terminal voltage working cycle period in the terminal voltage curve of the i-th battery in the battery pack, is the c-th voltage value within the b-th terminal voltage working cycle period in the terminal voltage curve of the i-th battery in the battery pack, is the c-th voltage value within the m-th end voltage working cycle of the i-th battery in the battery pack, where m is is the instability degree of the end voltage between the b-th and -th end voltage working cycles of the i-th battery in the battery pack.

[0092] Formula logic: represents the difference in end voltage corresponding to the data order within any two different end voltage working cycles of the i-th battery in the battery pack. When the difference in end voltage corresponding to the data order is larger, that is, the end voltages are different under the same discharge condition with similar capacities, it indicates that the end voltage curve is more unstable, and the end voltage of the battery is more severely affected by aging.

[0093]

[0094] In the above formula, is the number of all end voltage working cycles in the end voltage curve of the i-th battery in the battery pack, is the overall instability degree of the end voltage curve of the i-th battery in the battery pack.

[0095]

[0096] In the above formula, is the inverse normalization value of the Pearson correlation coefficient between the end voltage curve and the capacity curve of the i-th battery in the battery pack. Specifically, it is inversely normalized through the function exp(-x), where x represents the input, is the aging degree of the i-th battery in the battery pack; is the current corrected voltage value of the i-th battery in the battery pack, is the current voltage value of the i-th battery in the battery pack, where the current voltage value is the last voltage value in the end voltage curve of the i-th battery.

[0097] Formula logic: When the Pearson correlation coefficient between the end voltage curve and the capacity curve of the i-th battery in the battery pack is smaller, it indicates that the aging effect destroys the relationship between the end voltage curve and the capacity curve. Ideally, relevant electrical parameters can be determined based on the reference curve of capacity and end voltage. Knowing the voltage can determine the capacity, and knowing the capacity can determine the voltage. At the same time, if the aging degree of the battery and the end voltage curve are more unstable, the more serious the aging damage to the battery, and the more the current voltage value should be increased. Therefore, is used to correct the current voltage value to obtain the current corrected voltage value of the i-th battery in the battery pack.

[0098] Step S3: Using the capacity data and ambient temperature data of a single battery, correct the reference capacity value corresponding to the current voltage value in the associated reference data to obtain the current corrected capacity value.

[0099] Specifically, please refer to Figure 4 , Step S3 includes:

[0100] Step S31: Determine the temperature difference between the ambient temperature value corresponding to the last capacity measurement value in the capacity data and the standard ambient temperature.

[0101] Step S32: Using the preset capacity ambient coefficient and the temperature difference, correct the reference capacity value corresponding to the current voltage value in the associated reference data to obtain the current corrected capacity value.

[0102] At different ambient temperatures, the actual capacity of the battery changes to a certain extent. In a low-temperature environment, the actual capacity of the battery will decrease; in a high-temperature environment, the capacity will increase. If the influence of the harsh environment on the end capacity is not analyzed, errors will occur when analyzing the lagging battery later. Therefore, the current capacity is corrected according to the capacity at the reference temperature and the change of the ambient temperature to obtain the corrected value of the battery capacity.

[0103]

[0104] In the above formula, is the reference capacity value corresponding to the current voltage value of the i-th battery in the battery pack in the reference curve of capacity and terminal voltage, is the preset capacity temperature coefficient, which is used to reflect the influence of the harsh environment on the capacity. In this application, .01 is described, represents the ambient temperature value when measuring the last capacity value (the last capacity measurement value) in the capacity curve of the i-th battery in the battery pack, is the ambient temperature value corresponding to the reference curve of capacity and terminal voltage, that is, the standard ambient temperature; is the current corrected capacity value of the i-th battery in the battery pack.

[0105] Formula logic: Ideally, based on the reference curve of capacity and terminal voltage, the corresponding relationship between voltage and capacity can be determined mutually. However, due to the aging of the battery and the influence of the harsh environment, the capacity value will change to a certain extent, which is not the capacity value in the ideal situation. By analyzing the difference between the actual temperature and the standard ambient temperature, the initial reference capacity value is corrected. The smaller the temperature difference, the smaller the influence on the battery, and the less the correction. Finally, the current corrected capacity value of the i-th battery in the battery pack is obtained.

[0106] Step S4, determine the voltage deviation degree and capacity deviation degree between the current corrected voltage value and the current corrected capacity value of the single cell and the corresponding average voltage and average capacity in the series circuit where the single cell is located;

[0107] The average voltage includes the average value of the current corrected voltage values of all the cells in the series circuit where the single cell is located; the average capacitance includes the average value of the current corrected capacity values of all the cells in the series circuit where the single cell is located.

[0108] By detecting the corrected voltage and corrected capacity values of each cell in the series battery pack, judge the degree to which a single cell deviates from the average level. The greater the deviation, the more backward the cell is.

[0109] Step S5, determine the fault abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree, and determine the faulty cell by using the fault abnormality degree.

[0110] Specifically, the steps of determining the fault abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree include:

[0111] Calculate the fault abnormality degree of the single cell by using the voltage deviation degree, the capacity deviation degree and the preset capacity control error.

[0112] Battery packs are generally connected in series and in parallel. These two connection methods can effectively meet different voltage and capacity requirements, and thus improve the energy storage capacity of the battery pack. The main function of series connection is to increase the total voltage of the battery pack, and the main function of parallel connection is to increase the total capacity of the battery pack. The capacity of each cell (in ampere-hours (Ah)) is its ability to store electrical energy. The capacity of a single cell is fixed, but by connecting multiple cells in parallel, the total capacity of the battery pack is equal to the sum of the capacities of all the cells. If there is a backward cell in the series battery pack, the back electromotive force of this cell will increase, causing the voltage of this cell to increase, and thus causing the voltage of the entire battery pack to increase, resulting in insufficient charging of the entire battery pack. Therefore, it is necessary to analyze the abnormality degree of each cell in the series battery pack.

[0113] Assume that the i-th cell in the battery pack is a cell in a certain series branch.

[0114]

[0115] In the above formula, is the current corrected voltage value of the i-th cell in the battery pack, is the average value of the current corrected voltage values of all the cells in the series branch where the i-th cell in the battery pack is located, is the current corrected capacity value of the i-th cell in the battery pack, is the average value of the current corrected capacity values of all the batteries in the series branch where the i-th battery in the battery pack is located. is a preset capacity control error value. It can be adjusted as needed. is the degree of fault abnormality of the i-th battery in the battery pack.

[0116] Formula logic: The current of each battery in the series branch is equal. If there is a voltage value in the series branch that deviates from the average level, the more it deviates, the more abnormal it is. At the same time, analyze whether the capacitance deviates significantly. Since the lower limit of the reasonable use of the battery is generally to retain 20% of the residual capacity to avoid deep discharge of some batteries, if the capacity of a battery deviates too much from the average level, that is, the more it exceeds the capacity control error value, the more abnormal it is.

[0117] The steps to determine the faulty battery using the degree of fault abnormality include:

[0118] Compare the degree of fault abnormality with a preset abnormality threshold to determine whether a single battery is a faulty battery.

[0119] When the degree of fault abnormality is greater, it means that it is more likely to be a lagging battery, that is, there may be a faulty battery in the battery pack. The preset abnormality threshold can be set to 0.8, and this preset abnormality threshold can be adjusted as needed. Normalize the above-mentioned degree of fault abnormality and compare it with the preset abnormality threshold. If it is greater than or equal to the abnormality threshold, regard this battery as a lagging battery; otherwise, regard it as a normal battery.

[0120] After detecting the lagging batteries, the staff can replace these lagging batteries with spare batteries in time to ensure the normal operation of the system.

[0121] In one embodiment, before step S5, the method further includes:

[0122] Determine the current of the first branch and the current of the second branch in the two parallel branches where the battery pack is located and the absolute current difference between the two branch currents;

[0123] Compare the absolute current difference with a preset current change threshold to determine whether the battery pack is an abnormal battery pack;

[0124] In the case where the battery pack is determined to be an abnormal battery pack, execute the steps of determining the degree of fault abnormality of a single battery using the degree of voltage deviation and the degree of capacity deviation.

[0125] In a parallel battery pack, ideally, the currents in the two parallel branches are the same, and the two battery packs can operate normally. However, due to battery imbalance, in actual operation, the currents of the two battery packs are often not equal, and the more single cells connected in series in the battery pack, the greater the difference in current. When charging at a constant voltage, the charging levels of the two groups of batteries are different. The high-voltage battery pack is undercharged, and the low-voltage battery pack is overcharged.

[0126] Suppose battery pack A and battery pack B are operating in parallel. The current in the branch where battery pack A is located is (the current of the first branch), and the current in the branch where battery pack B is located is (the current of the second branch), + is the total current .

[0127] Obtain the currents of the two parallel branches respectively, and denote them as and respectively. Obtain the absolute difference between and . The preset current change threshold is 0.3, which can be adjusted according to the actual situation. If the absolute difference between and is greater than the preset current change threshold, it indicates that there are abnormal batteries in the battery packs of the two parallel branches. Then, use the above steps to obtain the degree of fault abnormality to analyze the degree of abnormality of the two parallel branches respectively, and judge which branch has abnormal batteries. The specific process will not be repeated here. Just analyze the two parallel branches as two series circuits.

[0128] Formula logic: When the absolute difference between and is larger, it indicates that the two parallel branches are unbalanced. Ideally, the currents in the two parallel branches are equal. If there is a large difference, it indicates that there are lagging batteries. Therefore, analyze the two parallel branches based on the degree of abnormality analyzed above.

[0129] The present invention determines the aging degree of a storage battery by comprehensively analyzing the charge and discharge cycle times, the change of capacity data, and the change of ambient temperature data of the storage battery, and obtains a correction value of the terminal voltage of the storage battery according to the fluctuation of the (terminal) voltage data of the storage battery, the similarity between the voltage data and the capacity curve, and the aging degree, so as to reduce the influence of the aging of the storage battery and the harshness of the ambient temperature on relevant electrical parameters. Furthermore, according to the capacity data, the ambient temperature data, and the reference capacity value corresponding to the current voltage value, a correction value of the storage battery capacity is obtained, and the fault and abnormality analysis of the battery in the corresponding circuit connection mode in the photovoltaic system is fully analyzed, which improves the accuracy of detecting the imbalance and abnormality between storage batteries, and thus can more accurately locate the storage battery with faults and abnormalities, so as to replace the abnormal battery and realize the normal operation of the energy storage system and the photovoltaic system.

[0130] Embodiment 2:

[0131] The embodiment of the present invention further provides an intelligent storage battery fault detection device. The intelligent storage battery fault detection device can be a data calculation and processing device such as a computer, a server, or a combination of multiple devices.

[0132] As Figure 5 shown, Figure 5 is a schematic structural diagram of the hardware operating environment of the intelligent storage battery fault detection device involved in the embodiment of the present invention.

[0133] As Figure 5 shown, the intelligent storage battery fault detection device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display (Display) and an input unit such as a control panel. Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WIFI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may optionally be a storage device independent of the aforementioned processor 1001. The memory 1005, as a computer storage medium, may include an intelligent storage battery fault detection program.

[0134] Those skilled in the art can understand that Figure 5 the hardware structure shown in

[0135] Continue to refer toFigure 5 , Figure 5 The memory 1005, as a computer-readable storage medium, may include an operating system, a user interface module, a network communication module, and a battery failure intelligent detection program.

[0136] In Figure 5 , the network communication module is mainly used to connect to the server and can communicate with the server for data; while the processor 1001 can call the battery failure intelligent detection program stored in the memory 1005 and execute the steps in each of the above embodiments.

[0137] Based on the above hardware structure of the battery failure intelligent detection device, each embodiment for implementing the battery failure intelligent detection method of the present invention is realized.

[0138] In addition, the present invention also provides a battery failure intelligent detection system. Please refer to Figure 6 , the battery failure intelligent detection system includes:

[0139] An aging monitoring module A10, which is used to determine the aging degree of a single battery by using the charge and discharge cycle times, capacity data, and environmental temperature data of the single battery in the battery pack;

[0140] A voltage correction module A20, which is used to correct the current voltage value of the single battery by using the terminal voltage data, capacity data, and aging degree of the single battery to obtain the current corrected voltage value;

[0141] A capacity correction module A30, which is used to correct the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and environmental temperature data of the single battery to obtain the current corrected capacity value;

[0142] A deviation calculation module A40, which is used to determine the voltage deviation degree and capacity deviation degree between the current corrected voltage value and the current corrected capacity value and the corresponding average voltage and average capacity in the series circuit where the single battery is located;

[0143] A fault location module A50, which is used to determine the fault abnormality degree of the single battery by using the voltage deviation degree and capacity deviation degree, and determine the faulty battery by using the fault abnormality degree.

[0144] Furthermore, the aging monitoring module A10 is further used for:

[0145] Determining the capacity attenuation coefficient of the single battery by using the capacity value difference between adjacent charge and discharge cycle periods of the single battery in the battery pack under the same charging condition and / or the same discharging condition;

[0146] Determine the aging degree of a single battery by using the capacity attenuation coefficient, the number of charge and discharge cycles, and the difference between the real-time temperature value of the environment where the single battery is located and the standard environment temperature.

[0147] Furthermore, the aging monitoring module A10 is further configured to:

[0148] Determine the first capacity value difference after a preset discharge duration between adjacent charge and discharge cycles of the single battery;

[0149] Determine the second capacity value difference when the single battery is fully charged between adjacent charge and discharge cycles;

[0150] Determine the variance of the absolute differences between all lower limit capacity measurement values of the single battery and a preset lower limit capacity standard value;

[0151] Calculate the capacity attenuation coefficient of the single battery by using the first capacity value difference, the second capacity value difference, and the variance of the absolute differences.

[0152] Furthermore, the voltage correction module A20 is further configured to:

[0153] Determine the overall instability degree of the terminal voltage of the single battery by using the terminal voltage differences corresponding to the same data order between any two different charge and discharge cycles of the single battery;

[0154] Determine the inverse normalization value of the Pearson correlation coefficient between the terminal voltage data and the capacity data;

[0155] Correct the current voltage value of the single battery by using the overall instability degree, the inverse normalization value, and the aging degree to obtain the current corrected voltage value.

[0156] Furthermore, the voltage correction module A20 is further configured to:

[0157] Determine the instability degree of the terminal voltage of the single battery for any two different charge and discharge cycles by using the terminal voltage differences corresponding to the same data order between any two different charge and discharge cycles of the single battery and the number of terminal voltages within any charge and discharge cycle;

[0158] Calculate the overall instability degree of the terminal voltage of the single battery by using each instability degree and the number of cycles of all charge and discharge cycles.

[0159] Furthermore, the capacity correction module A30 is further configured to:

[0160] Determine the temperature difference between the environmental temperature value corresponding to the last capacity measurement value in the capacity data and the standard environmental temperature;

[0161] Using a preset capacity environment coefficient and temperature difference, correct the reference capacity value corresponding to the current voltage value in the associated reference data to obtain the current corrected capacity value.

[0162] Further, the fault location module A50 is further configured to:

[0163] Calculate the fault abnormality degree of a single battery by using the voltage deviation degree, the capacity deviation degree, and a preset capacity control error.

[0164] Further, the fault location module A50 is further configured to:

[0165] Determine the current of the first branch and the current of the second branch in the two parallel branches where the battery pack is located, and the absolute current difference between the two branch currents;

[0166] Compare the absolute current difference with a preset current change threshold to determine whether the battery pack is an abnormal battery pack;

[0167] In the case where the battery pack is determined to be an abnormal battery pack, perform the step of determining the fault abnormality degree of a single battery by using the voltage deviation degree and the capacity deviation degree.

[0168] Further, the fault location module A50 is further configured to:

[0169] Compare the fault abnormality degree with a preset abnormality threshold to determine whether a single battery is a faulty battery.

[0170] The specific implementation manner of the battery fault intelligent detection system of the present invention is basically the same as each embodiment of the above battery fault intelligent detection method, and will not be described in detail here.

[0171] In addition, the present invention also provides a computer-readable storage medium. A battery fault intelligent detection program is stored on the computer-readable storage medium of the present invention. When the battery fault intelligent detection program is executed by a processor, the steps of the battery fault intelligent detection method as described above are implemented.

[0172] Among them, the method implemented when the battery fault intelligent detection program is executed can refer to each embodiment of the battery fault intelligent detection method of the present invention, and will not be described in detail here.

[0173] It should be noted that: the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0174] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and the differences between each embodiment and other embodiments are emphasized.

[0175] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0176] The above are only the preferred embodiments of the present invention, and do not limit the protection scope of the present invention. Any equivalent structure / method transformation made by using the content of the specification and drawings of the present invention under the inventive concept of the present invention, or any direct / indirect application in other related technical fields is included in the protection scope of the present invention.

Claims

1. An intelligent detection method for battery faults, characterized in that, The method includes: S1: Determine the aging degree of a single cell by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single cell in the battery pack; S2: Correct the current voltage value of the single cell by using the terminal voltage data, capacity data, and aging degree of the single cell to obtain the current corrected voltage value; S3: Correct the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and ambient temperature data of the single cell to obtain the current corrected capacity value; S4: Determine the voltage deviation degree and capacity deviation degree between the current corrected voltage value and the corresponding average voltage and average capacity in the series circuit where the single cell is located; S5: Determine the fault anomaly degree of the single cell by using the voltage deviation degree and capacity deviation degree, and determine the faulty cell by using the fault anomaly degree; Among them, the associated reference data is obtained by detecting the capacity and terminal voltage at the standard ambient temperature; the step of determining the aging degree of the single cell by using the charge and discharge cycle times, capacity data, and ambient temperature data of the single cell in the battery pack includes: Determine the capacity attenuation coefficient of the single cell by using the capacity value differences between adjacent charge and discharge cycle periods of the single cell in the battery pack under the same charging condition and / or the same discharging condition; Determine the aging degree of the single cell by using the capacity attenuation coefficient, the charge and discharge cycle times, and the difference between the real-time temperature value of the environment where the single cell is located and the standard ambient temperature.

2. The intelligent battery fault detection method according to claim 1, characterized in that, The step of determining the capacity attenuation coefficient of the single cell by using the capacity value differences between adjacent charge and discharge cycle periods of the single cell in the battery pack under the same charging condition and / or the same discharging condition includes: Determine the first capacity value difference after a preset discharge duration between adjacent charge and discharge cycle periods of the single cell; Determine the second capacity value difference when the single cell is fully charged between adjacent charge and discharge cycle periods; Determine the variance of the absolute differences between all lower limit capacity measurement values of the single cell and the preset lower limit capacity standard value; Calculate the capacity attenuation coefficient of the single cell by using the first capacity value difference, the second capacity value difference, and the variance of the absolute differences.

3. The intelligent battery fault detection method according to claim 1, wherein The step of correcting the current voltage value of the single cell by using the terminal voltage data, capacity data, and aging degree of the single cell to obtain the current corrected voltage value includes: Determine the overall instability degree of the terminal voltage of the single cell by using the terminal voltage differences corresponding to the same data order between any two different charge and discharge cycle periods of the single cell; Determine the inverse normalization value of the Pearson correlation coefficient between the terminal voltage data and the capacity data; Correct the current voltage value of the single cell by using the overall instability degree, the inverse normalization value, and the aging degree to obtain the current corrected voltage value.

4. The intelligent battery fault detection method according to claim 3, characterized in that, The step of determining the overall instability degree of the terminal voltage of the single cell by using the terminal voltage differences corresponding to the same data order between any two different charge and discharge cycle periods of the single cell includes: Determine the instability degree of the terminal voltage of the single cell for the any two different charge and discharge cycle periods by using the terminal voltage differences corresponding to the same data order between any two different charge and discharge cycle periods of the single cell and the number of terminal voltages within any charge and discharge cycle period; The overall instability degree of the single-cell terminal voltage is calculated by using each instability degree and the number of cycles in all charge-discharge cycles.

5. The intelligent battery fault detection method according to claim 1, wherein The steps of correcting the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and ambient temperature data of the single cell to obtain the current corrected capacity value include: Determine the temperature difference between the ambient temperature value corresponding to the last capacity measurement value in the capacity data and the standard ambient temperature; Use the preset capacity ambient coefficient and the temperature difference to correct the reference capacity value corresponding to the current voltage value in the associated reference data to obtain the current corrected capacity value.

6. The intelligent battery fault detection method according to claim 1, characterized in that The average voltage includes the average value of the current corrected voltage values of all the cells in the series circuit where the single cell is located; the average capacitance includes the average value of the current corrected capacity values of all the cells in the series circuit where the single cell is located; The steps of determining the fault and abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree include: Calculate the fault and abnormality degree of the single cell by using the voltage deviation degree, the capacity deviation degree and the preset capacity control error.

7. The intelligent battery fault detection method according to claim 1, characterized in that, Before the steps of determining the fault and abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree, the method further includes: Determine the current of the first branch and the current of the second branch in the two parallel branches where the battery pack is located and the absolute current difference between the two branch currents; Compare the absolute current difference with the preset current change threshold to determine whether the battery pack is an abnormal battery pack; In the case where the battery pack is determined to be an abnormal battery pack, execute the steps of determining the fault and abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree.

8. The intelligent battery fault detection method according to claim 1, characterized in that, The steps of determining the faulty cell by using the fault and abnormality degree include: Compare the fault and abnormality degree with the preset abnormality threshold to determine whether the single cell is a faulty cell.

9. An intelligent detection system for battery faults, characterized in that, The system is used to implement the intelligent battery fault detection method according to any one of claims 1 to 8; the system includes: An aging monitoring module, which is used to determine the aging degree of the single cell by using the charge-discharge cycle times, capacity data and ambient temperature data of the single cell in the battery pack; A voltage correction module, which is used to correct the current voltage value of the single cell by using the terminal voltage data, capacity data and aging degree of the single cell to obtain the current corrected voltage value; A capacity correction module, which is used to correct the reference capacity value corresponding to the current voltage value in the associated reference data by using the capacity data and ambient temperature data of the single cell to obtain the current corrected capacity value; A deviation calculation module, which is used to determine the voltage deviation degree and the capacity deviation degree between the current corrected voltage value and the current corrected capacity value and the corresponding average voltage and average capacitance in the series circuit where the single cell is located respectively; A fault location module, which is used to determine the fault and abnormality degree of the single cell by using the voltage deviation degree and the capacity deviation degree, and determine the faulty cell by using the fault and abnormality degree.

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