CN117991101A - Performance degradation and service life early warning method and system for energy storage lithium battery - Google Patents
Performance degradation and service life early warning method and system for energy storage lithium battery Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 77
- 238000004146 energy storage Methods 0.000 title claims abstract description 76
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 title claims abstract description 43
- 229910052744 lithium Inorganic materials 0.000 title claims abstract description 43
- 230000015556 catabolic process Effects 0.000 title claims description 18
- 238000006731 degradation reaction Methods 0.000 title claims description 18
- 238000012360 testing method Methods 0.000 claims abstract description 65
- 238000001514 detection method Methods 0.000 claims abstract description 27
- 230000008595 infiltration Effects 0.000 claims abstract description 11
- 238000001764 infiltration Methods 0.000 claims abstract description 11
- 238000004458 analytical method Methods 0.000 claims abstract description 6
- 239000008151 electrolyte solution Substances 0.000 claims abstract description 5
- 238000012216 screening Methods 0.000 claims abstract description 5
- 238000007600 charging Methods 0.000 claims description 32
- 230000008569 process Effects 0.000 claims description 23
- 230000004044 response Effects 0.000 claims description 14
- 239000003792 electrolyte Substances 0.000 claims description 13
- 230000010287 polarization Effects 0.000 claims description 13
- 238000001453 impedance spectrum Methods 0.000 claims description 12
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 230000005540 biological transmission Effects 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 8
- 239000003990 capacitor Substances 0.000 claims description 7
- 230000000694 effects Effects 0.000 claims description 7
- 238000002474 experimental method Methods 0.000 claims description 7
- 238000010277 constant-current charging Methods 0.000 claims description 6
- 238000007405 data analysis Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000010280 constant potential charging Methods 0.000 claims description 3
- 238000000354 decomposition reaction Methods 0.000 claims description 3
- 230000005284 excitation Effects 0.000 claims description 3
- 238000001556 precipitation Methods 0.000 claims description 3
- 230000007547 defect Effects 0.000 abstract description 10
- 230000007423 decrease Effects 0.000 abstract description 3
- 238000000157 electrochemical-induced impedance spectroscopy Methods 0.000 description 44
- 230000003068 static effect Effects 0.000 description 27
- 238000003860 storage Methods 0.000 description 14
- 230000036541 health Effects 0.000 description 11
- 239000000463 material Substances 0.000 description 11
- 230000008859 change Effects 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 5
- 238000009826 distribution Methods 0.000 description 4
- 230000032683 aging Effects 0.000 description 3
- 238000004590 computer program Methods 0.000 description 3
- 238000007599 discharging Methods 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 239000000243 solution Substances 0.000 description 3
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 238000002847 impedance measurement Methods 0.000 description 2
- 229910001416 lithium ion Inorganic materials 0.000 description 2
- GELKBWJHTRAYNV-UHFFFAOYSA-K lithium iron phosphate Chemical compound [Li+].[Fe+2].[O-]P([O-])([O-])=O GELKBWJHTRAYNV-UHFFFAOYSA-K 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
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- 238000011160 research Methods 0.000 description 2
- 239000000523 sample Substances 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 1
- 239000002253 acid Substances 0.000 description 1
- 239000002390 adhesive tape Substances 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 238000010351 charge transfer process Methods 0.000 description 1
- 229910052802 copper Inorganic materials 0.000 description 1
- 239000010949 copper Substances 0.000 description 1
- 230000001351 cycling effect Effects 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 230000002708 enhancing effect Effects 0.000 description 1
- 230000034964 establishment of cell polarity Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000011065 in-situ storage Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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Abstract
A performance decline and life-span early warning method and system of the energy storage lithium battery, S1, choose the voltage pin of BMS of a battery module to draw out repeatedly to each cluster power station of the energy storage power station, make into the terminal of EIS test; s2, performing off-line test on the EIS under different SOC intervals of the battery; s3, judging whether the impedance performance of the battery is consistent according to the test result, and if not, entering S4; s4, standing the battery with inconsistent battery impedance, and obtaining the internal resistance of the battery by using a second-order RC equivalent circuit model when the voltage of the battery is reduced to the platform voltage; s5, judging whether the internal resistance characteristics of the batteries are consistent, if not, entering S6; s6: screening all batteries of the energy storage power station, selecting the battery with the internal resistance value of 0.1% at the front, detecting the electrolyte solution infiltration condition of the screened battery, and analyzing the failure reason of the battery; and S7, selecting the battery exceeding the detection standard according to the fault analysis result to replace the battery core in advance, wherein the defect of the battery can be found in advance.
Description
Technical Field
The invention relates to the field of health state analysis and early warning of large-scale energy storage system lithium ion batteries, in particular to an energy storage battery health state judging method based on battery impedance characteristics and ultrasonic detection technology.
Background
At present, a lithium iron phosphate battery is generally adopted as an important energy storage unit in the new energy storage power station, and compared with a traditional ternary battery and a lead-acid battery, the lithium iron phosphate battery has the advantages of being large in energy density, long in cycle life, small in self-discharge rate, free of memory effect, green, environment-friendly and the like, supports stepless expansion, is suitable for large-scale electric energy storage, and has good application prospects in the fields of renewable energy power generation safety grid connection, power grid peak regulation and frequency modulation, distributed power stations, UPS power supplies and the like.
In the cycling process of the energy storage battery, the problem of inconsistent capacity, internal resistance and open-circuit voltage can occur along with the aging of the battery, and the problems are mainly reflected in capacity attenuation and internal resistance increase, and if an abnormal battery is not found in time, the abnormal battery can be short-circuited in the battery to cause thermal runaway, so that huge economic loss and safety hazard are caused to the energy storage power station. Therefore, the static battery of the energy storage power station is selected, EIS off-line test is carried out on the static battery, a second-order RC equivalent circuit model of the battery of the energy storage power station is established, the impedance change trend of the battery of the energy storage power station is researched by combining the static battery and the second-order RC equivalent circuit model, and further the aging and aging mechanisms of the battery of the energy storage power station are researched, so that an off-line identification method for the health life state of the battery of the energy storage is formed.
Electrochemical Impedance Spectroscopy (EIS) is a non-destructive parametric measurement and efficient method of battery dynamic behavior measurement. Compared with the online alternating current impedance testing technology, the EIS has high offline testing precision, high speed and high practicability, the impedance value and the like of each equivalent circuit element can be analyzed by using the EIS result, and the testing method scans from very low frequency to very high frequency to realize the electrochemical interface reaction research in a wide frequency range. Ultrasonic detection technology is applied in more fields, ultrasonic imaging scanning technology utilizes sound waves to conduct in-situ nondestructive imaging on sensitivity of physical and chemical changes in the battery core, and detects state change information in the battery, so that offline identification of the health state of the energy storage battery is achieved.
The offline identification method for detecting the internal resistance of the energy storage battery and the ultrasonic offline detection technology are organically combined, so that the comprehensive evaluation of the battery health state can be accurately and reliably carried out, and compared with the prior art, the method has obvious progress.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a performance degradation and life early warning method and system of an energy storage lithium battery, wherein an EIS impedance spectrum and a second-order circuit RC equivalent model of the battery are used for analyzing the performance degradation mechanism of the energy storage lithium battery; the ultrasonic detection technology can further find the defects inside the battery, overcomes the defect that the traditional detection technology cannot make the external measurement parameters consistent with the internal parameters to represent the special effects of the battery, enhances and analyzes the failure cause of the battery, and enables the defects of the battery to be found in advance and the service life of the battery to be early warned.
The invention adopts the following technical scheme.
A performance degradation and life early warning method of an energy storage lithium battery comprises the following steps:
S1, circularly selecting voltage pins of a battery management system BMS of a battery module according to set circulation times for each cluster of power stations of the energy storage power station to be repeatedly led out, and manufacturing an EIS test terminal;
s2, performing EIS off-line test on the selected battery module from low frequency to high frequency in different SOC intervals of the battery;
S3, judging whether the impedance performance of the battery is consistent according to the test result, if so, replacing the inner core of the battery is not needed; if not, entering S4;
s4, standing the battery with inconsistent battery impedance, and when the voltage of the battery drops to a preset platform voltage, establishing a second-order RC equivalent circuit model of the battery of the energy storage power station, and obtaining the internal resistance of the battery by using the second-order RC equivalent circuit model;
s5, judging whether the internal resistance characteristics of the batteries are consistent, if so, judging that the battery inner core does not need to be replaced, and if not, entering S6;
s6: screening all batteries of the energy storage power station, selecting the battery with the internal resistance value of 0.1% at the front, detecting the electrolyte solution infiltration condition of the screened battery, and analyzing the failure reason of the battery;
And S7, selecting out the battery exceeding the detection standard according to the fault analysis result to replace the battery inner core in advance, so as to realize the life early warning of the energy storage lithium battery.
The step S2 specifically comprises the following steps:
Before EIS test, charging the battery to a specified SOC and standing; the BMS outputs an alternating current excitation signal to the battery, acquires an alternating voltage response signal, obtains complex impedance after processing, and outputs battery EIS data after sweep frequency measurement is completed; repeating the test, and recording impedance spectrum data of the battery SOC at different temperatures and different seasons within the range of 0-10% and 80% -100% at intervals of 5% SOC.
In the EIS test process, the method further comprises:
And carrying out Fourier decomposition on the measured data to calculate an impedance value, and simultaneously observing the temperature, open circuit voltage and impedance spectrum data of the battery through the BMS, and recording the data.
Charging the battery to a specified SOC and standing before performing EIS testing on the battery specifically includes:
Constant-current charging is carried out on the battery; constant voltage charging is carried out when the voltage of the battery reaches the rated voltage, and charging is stopped when the current reaches the charging cut-off current; then constant-current discharge is carried out on the battery, and when the battery reaches the discharge cut-off voltage, the discharge is stopped, so that the battery is a cycle failure;
and charging the energy storage lithium battery with fixed capacity to the interval of 0-10% and 80-100% through charge and discharge circulation, carrying out EIS test every 5% SOC in the interval, standing for 10min after the end of charging every 5% SOC at the initial time of EIS test, and carrying out test after standing for 2H at the end point of the interval, wherein the scanning frequency is lkHz-100 mHz.
In the step S4 of the above-mentioned method,
In the charge-discharge cycle, the battery is kept still after being fully charged, the voltage is reduced to the platform voltage at the moment, the battery which is reduced to the platform voltage within the preset time is selected, and the internal resistance characteristic of the battery is obtained by utilizing the RC equivalent circuit model at 5s, 10s and 50s after the voltage is reduced.
The obtaining the internal resistance characteristic of the battery by using the RC equivalent circuit model specifically comprises the following steps:
the internal resistance of the battery is equivalent to a series resistance element, a second-order RC equivalent circuit model is established based on the open circuit voltage at two ends of the battery, and the mathematical expression of the model is as follows:
Wherein U ocv is open circuit voltage, I is current, end voltage of Uo second-order RC equivalent circuit, R 0 is ohmic internal resistance, R1 and R2 are polarized internal resistance, C1 and C2 are polarized capacitance, and U1 and U2 are voltages on R1 and R2 respectively; in the process of constant current discharge of the battery, the dynamic circuit electric quantity expression is as follows:
At the standing moment when the battery is charged, according to The method is used for identifying the ohmic internal resistance R 0, wherein Em is the peak voltage when charging to a certain SOC value, and U o(0) is the initial terminal voltage in a standing stage;
According to Obtaining a time constant tau, wherein U 1(0),U2 (0) is the initial voltage at two ends of the capacitor at the moment of ending each pulse; τ is the polarization effect response time;
In the 80% -100% constant current charging process, standing for 1min every 5% SOC, identifying parameter values when standing for 5s, 10s and 50s, and in a standing time period, the current input is 0, and can be regarded as response when RC link zero input is performed, wherein the terminal voltage can be expressed as:
The voltage at two ends of the polarized internal resistance is as follows:
The battery polarization voltage is basically unchanged at the moment of the end of charging, and can be obtained by the following steps:
Wherein t k is the loading time for charging 5% SOC, and R1 and R2 are obtained by substituting U 1(0) Filling material - Static state ,U2(0) Filling material - Static state ,τ1 Filling material - Static state ,τ2 Filling material - Static state obtained in the process of charging-standing for 5s, 10s and 50 s; c 1 and C 2 are obtained according to the time constant expression, and RC link identification parameters during standing for 5s, 10s and 50s are completed;
and calculating the total internal resistance R Total (S) = R0+R1+R2, and taking the battery with the maximum total internal resistance R Total (S) as a standard for selecting one thousandth of batteries.
The step S6 specifically comprises the following steps:
Observing a second-order RC parameter to identify whether the screened battery with the resistance value being 0.1% in front of all batteries has external faults or not, and if no obvious appearance damage exists, further performing ultrasonic detection; based on the ultrasonic transmission principle, the electrolyte infiltration condition inside the battery is scanned, the electrolyte is analyzed to be unevenly distributed or the part where gas production occurs, and the fault reason of the battery is enhanced and analyzed.
The step S7 specifically comprises the following steps:
And (3) replacing the inner core of the battery with appearance faults and exceeding the standard of gas yield and lithium precipitation of the battery detected in ultrasonic detection according to the detection result of the step (S6).
The application also discloses a performance decline and life early-warning system for the performance of the energy storage lithium battery by utilizing the life early-warning method, which comprises an EIS test module, a data analysis module, a charge-discharge circulation module, a second-order RC model identification module and a fault test and identification module,
The EIS test module circularly selects a battery module in each cluster of power stations of the energy storage power station, repeatedly leads out voltage pins of a battery management system of the battery module, and performs EIS test on each cluster of batteries from low frequency to high frequency in different SOC intervals of the batteries;
The data analysis module is used for analyzing whether the impedance characteristic and the internal resistance characteristic of the battery are consistent or not and judging whether to continue testing or not;
The charge-discharge circulation module performs charge-discharge circulation on the battery to enable the battery to reach a specific SOC value and stand;
the second-order RC model identification module establishes a second-order RC model, and the internal resistance of the battery is identified by utilizing the RC model;
The fault test and identification module performs fault test on the appointed battery and determines the battery of which the inner core needs to be replaced according to the test result. The initial wet state of the cell needs to be checked before the cell is cycled because the defect in the process of making the cell may be the presence of bubbles in the cell.
The impedance measurement method of the battery adopts an EIS impedance spectrum parameter method for measurement.
The battery circulation environment needs to be controlled in the battery circulation process, and the influence of other factors on the experiment is reduced under the condition that the temperature is close to the room temperature.
Compared with the prior art, the method has the beneficial effects that 1, the EIS offline test is carried out on the static energy storage battery of the large energy storage power station, the second-order RC equivalent circuit model of the energy storage power station battery is built, the impedance change trend of the static energy storage battery is researched by combining the EIS offline test and the second-order RC equivalent circuit model, the health state of the battery can be accurately detected, and the method for identifying the health life state of the energy storage battery offline is formed.
2. The invention utilizes ultrasonic detection to observe the corresponding battery infiltration condition, the ultrasonic detection has the advantages of high sensitivity, strong universality and the like, the ultrasonic detection does not need to process, coat and disassemble the battery, the micro-change of the internal material of the battery is detected by utilizing the acoustic performance difference caused by the physical property change of the internal material of the battery on the premise of not damaging the internal material of the battery, the health state of the battery can be intuitively and rapidly monitored through imaging, the internal defect of the battery is searched, and the safety of the battery is ensured.
Drawings
FIG. 1 is a flow chart of a method for evaluating performance degradation and life early warning of an energy storage lithium battery;
FIG. 2 is a second-order RC equivalent circuit diagram of the energy storage lithium battery provided by the invention;
fig. 3 is a graph of internal resistance characteristics of an energy storage lithium battery provided by the present invention;
FIG. 4 is a graph of internal resistance of the battery at 5, 10 and 50s when the battery is stationary in the discharging process of the energy storage power station;
FIG. 5 is an EIS spectrum of a battery at 50% SOC provided by the present invention;
FIG. 6 is an EIS impedance spectrum equivalent circuit model of the energy storage lithium battery provided by the invention;
FIG. 7 is an EIS impedance spectrum of the energy storage lithium battery provided by the invention under different SOCs;
Fig. 8 is an initial electrolyte infiltration state diagram of the energy storage lithium battery provided by the invention;
Fig. 9 is a schematic diagram of an electrolyte infiltration state of an energy storage lithium battery with gas generation at a part of the positions provided by the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. The described embodiments of the application are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art without making any inventive effort, are within the scope of the present application.
The invention adopts the following technical scheme.
A performance degradation and life early warning method of an energy storage lithium battery comprises the following steps:
S1, circularly selecting voltage pins of a battery management system BMS of a battery module according to set circulation times for each cluster of power stations of the energy storage power station to be repeatedly led out, and manufacturing an EIS test terminal;
s2, performing EIS off-line test on the selected battery module from low frequency to high frequency in different SOC intervals of the battery;
S3, judging whether the impedance performance of the battery is consistent according to the test result, if so, replacing the inner core of the battery is not needed; if not, entering S4;
s4, standing the battery with inconsistent battery impedance, and when the voltage of the battery drops to the platform voltage, establishing a second-order RC equivalent circuit model of the battery of the energy storage power station, and obtaining the internal resistance of the battery by using the second-order RC equivalent circuit model;
s5, judging whether the internal resistance characteristics of the batteries are consistent, if so, judging that the battery inner core does not need to be replaced, and if not, entering S6;
s6: screening all batteries of the energy storage power station, selecting the battery with the internal resistance value of 0.1% at the front, detecting the electrolyte solution infiltration condition of the screened battery, and analyzing the failure reason of the battery;
And S7, selecting out the battery exceeding the detection standard according to the fault analysis result to replace the battery inner core in advance, so as to realize the life early warning of the energy storage lithium battery.
The step S2 specifically comprises the following steps:
Before EIS test, charging the battery to a specified SOC and standing; the BMS outputs an alternating current excitation signal to the battery, acquires an alternating voltage response signal, obtains complex impedance after processing, and outputs battery EIS data after sweep frequency measurement is completed; repeating the test, and recording impedance spectrum data of the battery SOC at different temperatures and different seasons within the range of 0-10% and 80% -100% at intervals of 5% SOC.
In the EIS test process, the method further comprises:
And carrying out Fourier decomposition on the measured data to calculate an impedance value, and simultaneously observing the temperature, open circuit voltage and impedance spectrum data of the battery through the BMS, and recording the data.
Wherein the internal resistance characteristic curve chart of the energy storage lithium battery is shown in fig. 3;
Charging the battery to a specified SOC and standing before performing EIS testing on the battery specifically includes:
Constant-current charging is carried out on the battery; constant voltage charging is carried out when the voltage of the battery reaches the rated voltage, and charging is stopped when the current reaches the charging cut-off current; then constant-current discharge is carried out on the battery, and when the battery reaches the discharge cut-off voltage, the discharge is stopped, so that the battery is a cycle failure;
and charging the energy storage lithium battery with fixed capacity to the interval of 0-10% and 80-100% through charge and discharge circulation, carrying out EIS test every 5% SOC in the interval, standing for 10min after the end of charging every 5% SOC at the initial time of EIS test, and carrying out test after standing for 2H at the end point of the interval, wherein the scanning frequency is lkHz-100 mHz.
In the step S4 of the above-mentioned method,
In the charge-discharge cycle, the battery is kept still after being fully charged, the voltage is reduced to the platform voltage at the moment, the battery which is reduced to the platform voltage within the preset time is selected, and the internal resistance characteristic of the battery is obtained by utilizing the RC equivalent circuit model at 5s, 10s and 50s after the voltage is reduced.
The obtaining the internal resistance characteristic of the battery by using the RC equivalent circuit model specifically comprises the following steps:
the internal resistance of the battery is equivalent to a series resistance element, a second-order RC equivalent circuit model is established based on the open circuit voltage at two ends of the battery, and the mathematical expression of the model is as follows:
Wherein U ocv is open circuit voltage, I is current, end voltage of Uo second-order RC equivalent circuit, R 0 is ohmic internal resistance, R1 and R2 are polarized internal resistance, C1 and C2 are polarized capacitance, and U1 and U2 are voltages on R1 and R2 respectively; in the process of constant current discharge of the battery, the dynamic circuit electric quantity expression is as follows:
At the standing moment when the battery is charged, according to The method is used for identifying the ohmic internal resistance R 0, wherein Em is the peak voltage when charging to a certain SOC value, and U o(0) is the initial terminal voltage in a standing stage;
According to Obtaining a time constant tau, wherein U 1(0),U2 (0) is the initial voltage at two ends of the capacitor at the moment of ending each pulse; τ is the polarization effect response time;
In the 80% -100% constant current charging process, standing for 1min every 5% SOC, identifying parameter values when standing for 5s, 10s and 50s, and in a standing time period, the current input is 0, and can be regarded as response when RC link zero input is performed, wherein the terminal voltage can be expressed as:
When the battery is charged and stands for a period of time, the internal polarization effect is basically disappeared, namely the polarization voltage is 0, so that the charging stage from 80% -100% SOC to 5% SOC is regarded as zero-state response of RC link, and the voltage across the polarization capacitor is as follows:
The battery polarization voltage is basically unchanged at the moment of the end of charging, and can be obtained by the following steps:
Wherein t k is the loading time for charging 5% SOC, and R1 and R2 are obtained by substituting U 1(0) Filling material - Static state ,U2(0) Filling material - Static state ,τ1 Filling material - Static state ,τ2 Filling material - Static state obtained in the process of charging-standing for 5s, 10s and 50 s; c 1 and C 2 are obtained according to the time constant expression, and RC link identification parameters during standing for 5s, 10s and 50s are completed;
and calculating the total internal resistance R Total (S) = R0+R1+R2, and taking the battery with the maximum total internal resistance R Total (S) as a standard for selecting one thousandth of batteries.
The step S6 specifically comprises the following steps:
Observing a second-order RC parameter to identify whether the screened battery with the resistance value being 0.1% in front of all batteries has external faults or not, and if no obvious appearance damage exists, further performing ultrasonic detection; based on the ultrasonic transmission principle, the electrolyte infiltration condition inside the battery is scanned, the electrolyte is analyzed to be unevenly distributed or the part where gas production occurs, and the fault reason of the battery is enhanced and analyzed.
The step S7 specifically comprises the following steps:
And (3) replacing the inner core of the battery with appearance faults and exceeding the standard of gas yield and lithium precipitation of the battery detected in ultrasonic detection according to the detection result of the step (S6).
The application also discloses a performance decline and life early-warning system for the performance of the energy storage lithium battery by utilizing the life early-warning method, which comprises an EIS test module, a data analysis module, a charge-discharge circulation module, a second-order RC model identification module and a fault test and identification module,
The EIS test module circularly selects a battery module in each cluster of power stations of the energy storage power station, repeatedly leads out voltage pins of a battery management system of the battery module, and performs EIS test on each cluster of batteries from low frequency to high frequency in different SOC intervals of the batteries;
The data analysis module is used for analyzing whether the impedance characteristic and the internal resistance characteristic of the battery are consistent or not and judging whether to continue testing or not;
The charge-discharge circulation module performs charge-discharge circulation on the battery to enable the battery to reach a specific SOC value and stand;
the second-order RC model identification module establishes a second-order RC model, and the internal resistance of the battery is identified by utilizing the RC model;
The fault test and identification module performs fault test on the appointed battery and determines the battery of which the inner core needs to be replaced according to the test result. The initial wet state of the cell needs to be checked before the cell is cycled because the defect in the process of making the cell may be the presence of bubbles in the cell.
The impedance measurement method of the battery adopts an EIS impedance spectrum parameter method for measurement.
The battery circulation environment needs to be controlled in the battery circulation process, and the influence of other factors on the experiment is reduced under the condition that the temperature is close to the room temperature.
The batteries in the energy storage power station will rest for a period of time after being charged. Fig. 1 is a general flow chart for evaluating performance degradation and life early warning methods of an energy storage lithium battery.
Selecting a voltage pin of a BMS of a module for each cluster of power stations of the energy storage power station to be repeatedly led out to manufacture an EIS test terminal;
Carrying out EIS off-line test on each cluster of batteries of the energy storage power station from low frequency to high frequency in different SOC intervals, and establishing a data set all the year round;
sinusoidal voltage and frequency settings. The differential equation of the response of the reaction system can be approximately considered to satisfy the linearity condition as long as the magnitude of the applied voltage is less than the thermal voltage U T.
Wherein: r is an air constant, T is absolute temperature, F is Faraday constant, K is Boltzmann constant, and e is electron charge.
EIS analysis cells exhibit inductive reactance properties in the high frequency region, caused by the porous electrode structure and connecting leads. The battery is greatly affected by temperature in a high frequency region. The experiment requires correct screening of the faulty battery so that no study is made on the high frequency region. Semicircle in the mid-band is generally considered to be relevant to the charge transfer process of the battery. This region of the low-band cell with a sloping upward trend symbolizes the impedance of the diffusion process of lithium ions at the two electrodes, the Warburg impedance. This area is often ignored, even not measured, because the longer time required to measure impedance at lower frequencies is generally not studied.
The amplitude of the sinusoidal voltage selected in the experiment is 10mV, and the frequency is 1kHz-100mHz.
According to EIS impedance spectrums of different batteries under different SOCs, observing and evaluating the health state of the whole module, and if the health states are inconsistent, further detecting the health states or directly replacing the batteries; if the results are consistent, the detection is performed to see whether the detection is problematic.
FIG. 2 is a second order RC equivalent model diagram, and the implementation process is specifically described below:
Analysis of the equivalent circuit of the battery, as shown in the circuit of fig. 6, C AB is the capacitance between the two poles, and since it is much larger than the electric double layer capacitance C d, C AB is generally ignored in the research process; r Ω represents the resistance of the lithium battery electrolyte solution, and is a pure ohmic resistance; r SEI and C SEI represent the resistance and capacitance of the SEI film, respectively; c d is an electric double layer capacitor at the electrode interface; z f is the faraday impedance of the electrode, faraday impedance Z f is composed of charge transfer resistor R ct and diffusion impedance Z d, which is negligible in EIS analysis Z d. Calculating the equivalent impedance of the battery of fig. 6 may result in:
for ease of understanding, we take the impedance during charge conduction alone to calculate, where the impedance is:
the method comprises the following steps:
From the above formula:
as known from kirchhoff's law, the mathematical expression of the model is:
the model parameter identification problem is the problem of solving R 0,R1,R2,C1,C2 parameter values in the model according to current and voltage data acquired in an experiment, and can start from an ideal second-order RC circuit model to realize identification of the internal resistance of the lithium battery.
In the charge and discharge process of the battery ohmic internal resistance, the change of the SOC is basically kept unchanged, so that the value of the ohmic internal resistance R 0 can be identified according to the change curve of the battery voltage and the current at the part affected by the battery non-polarization parameter. In an ideal second-order RC model of the battery, the peak value of the open-circuit voltage of the battery can be regarded as a fixed value E m, and in the process of constant-current discharge of the battery, the electric quantity expression of a dynamic circuit is as follows:
Further, in the battery cycle process step, a certain period of rest time is set after the charge and discharge are finished, and the terminal voltage of the battery is rapidly reduced by a certain value at the moment of the rest after the charge is finished, so that the reason for the reduction is mainly considered to be the voltage drop on the ohmic internal resistance, and the formula (3) is the identification basis of the ohmic internal resistance R 0.
Knowing the time constant t=rc, t reflects the steady state speed of the battery after charging and discharging, and the resistor and the capacitor in the RC link are to be identified, t is required to be obtained first, and the real constant expression is combined to obtain:
Wherein U 1(0),U2 (0) is the initial voltage at two ends of the capacitor at the moment of ending each charging; t is the polarization effect response time.
And calibrating the SOC-U OC, wherein the internal parameters of the lithium battery change at any time, and the identification of RC parameters under different SOCs requires corresponding open-circuit voltage values. To obtain the relationship between SOC and U OC, a pulse discharge experiment was performed on the battery: when the battery is fully charged, the battery is discharged by a 5A current pulse, and after 5% SOC is discharged, the discharge is stopped, and the battery is kept in an equilibrium state. And (3) after the battery stands still, measuring a terminal voltage value, namely a U OC value corresponding to the current SOC.
Firstly, carrying out parameter identification on the charging-standing direction, wherein in the standing time period, the current input is 0, the current input can be regarded as response when RC link zero input is carried out, and the terminal voltage can be expressed as:
R 1、R2、C1、C2 parameter identification in charging-standing stage
According to equation (5), U1 (0) Put and put - Static state -5,U2(0) Discharge of electric power - Standing still -5,τ1 Put and put - Static state -5,τ2 Put and put - Static state -5 can be obtained by fitting a voltage change curve of the battery after discharging and standing for 5 s.
According to equation (5), U1 (0) Put and put - Static state -10,U2(0) Discharge of electric power - Standing still -10,τ1 Put and put - Static state -10,τ2 Put and put - Static state -10 can be obtained by fitting a voltage change curve of 10s after charging the battery.
According to equation (5), U1 (0) Put and put - Static state -50,U2(0) Discharge of electric power - Standing still -50,τ1 Put and put - Static state -50,τ2 Put and put - Static state -50 can be obtained by fitting a voltage change curve of the battery after charging and standing for 50 s.
When the battery is discharged and stood for a period of time, the internal polarization effect is basically disappeared, and the polarization voltage is considered to be 0, so that the discharge phase of 100% -80% SOC at intervals of 5% SOC is regarded as zero-state response of RC link. The voltage at two ends of the polarized internal resistance is as follows:
The cell polarization voltage at the moment of the end of discharge is basically unchanged, and thus the following can be obtained:
Wherein t k is the loading time for 5% SOC discharge, and R 1、R2 when the obtained U 1(0) Put and put - Static state ,U2(0) Put and put - Static state ,τ1 Put and put - Static state ,τ2 Put and put - Static state is substituted into formula (7) and discharge-standing for 5s, 10s and 50s can be obtained;
And then C 1 and C 2 are obtained according to the time constant expression, and RC link identification parameters in the standing for 5s, 10s and 50s are as follows under the discharging-standing direction.
The total internal resistance R is calculated according to the formula under the conditions of 80-100% SOC and respectively corresponding to the conditions of standing for 5s, 10s and 50s, and is plotted as shown in figure 4. Further, obvious outlier data points are found, and the performance of a battery in the container is proved to be obviously degraded.
And (3) focusing on the battery with problems in the EIS detection in the last step, and judging whether the parameters identified by the second-order RC model are consistent with the rest of batteries in a healthy state.
The method for combining the second-order RC parameter identification-EIS impedance test-ultrasonic detection technology is carried out in order to screen out the energy storage lithium batteries with inconsistent impedance performance.
The EIS spectrum of the cell at 50% soc is shown in fig. 5; EIS impedance maps of the energy storage lithium battery under different SOCs are shown in FIG. 6;
If the appearance of the battery does not generate obvious bulge gas production phenomenon, if the energy storage power station is allowed to stop, detecting the distribution condition of electrolyte of the battery by utilizing an ultrasonic technology within 30min, so that the method is used for enhancing and analyzing the fault reason of the battery;
And further detecting the battery screened by the second-order RC parameter identification, and firstly, observing the appearance of the battery with problems to see whether obvious external faults such as bulges occur. If so, the battery is directly replaced without further detection, and if no obvious appearance damage exists and the power station is allowed to stop, the battery is required to be further detected-ultrasonic detection.
Sticking the lugs of the single batteries by using an insulating adhesive tape, putting the single batteries into silicone oil, and fixing the single batteries between ultrasonic probes;
Setting the moving frequency and the moving position of the ultrasonic probe and setting the frame rate of an image at the upper machine position;
based on the ultrasonic transmission principle, the electrolyte infiltration condition inside the battery is scanned from the lower part to the upper part of the battery frame by frame, and the part with uneven distribution of the electrolyte is analyzed or gas production occurs, so that the fault cause of the battery is enhanced and analyzed, and the service life early warning of the battery is realized.
Fig. 8-9 reflect two state electrolyte distribution diagrams of the energy storage battery, the wetting state of fig. 8 is good, and the defects of the electrolyte distribution of fig. 9 are due to the defects of the structure of the battery.
Before the battery fails, the battery core is replaced to realize the life early warning of the energy storage lithium battery.
The present disclosure may be a system, method, and/or computer program product. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for causing a processor to implement aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
The computer program instructions for performing the operations of the present disclosure may be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as SMALLTALK, C ++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those skilled in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. The performance degradation and life early warning method for the energy storage lithium battery is characterized by comprising the following steps of:
S1, circularly selecting voltage pins of a battery management system BMS of a battery module according to set circulation times for each cluster of power stations of the energy storage power station to be repeatedly led out, and manufacturing an EIS test terminal;
s2, performing EIS off-line test on the selected battery module from low frequency to high frequency in different SOC intervals of the battery;
S3, judging whether the impedance performance of the battery is consistent according to the test result, if so, replacing the inner core of the battery is not needed; if not, entering S4;
s4, standing the battery with inconsistent battery impedance, and when the voltage of the battery drops to a preset platform voltage, establishing a second-order RC equivalent circuit model of the battery of the energy storage power station, and obtaining the internal resistance of the battery by using the second-order RC equivalent circuit model;
s5, judging whether the internal resistance characteristics of the batteries are consistent, if so, judging that the battery inner core does not need to be replaced, and if not, entering S6;
s6: screening all batteries of the energy storage power station, selecting the battery with the internal resistance value of 0.1% at the front, detecting the electrolyte solution infiltration condition of the screened battery, and analyzing the failure reason of the battery;
And S7, selecting out the battery exceeding the detection standard according to the fault analysis result to replace the battery inner core in advance, so as to realize the life early warning of the energy storage lithium battery.
2. The performance degradation and life early warning method for an energy storage lithium battery according to claim 1, wherein the method comprises the following steps:
The step S2 specifically comprises the following steps:
Before EIS test, charging the battery to a specified SOC and standing; the BMS outputs an alternating current excitation signal to the battery, acquires an alternating voltage response signal, obtains complex impedance after processing, and outputs battery EIS data after sweep frequency measurement is completed; the test was repeated and impedance spectrum data were recorded for battery SOC in the 80% -100% range, every 5% SOC.
3. The performance degradation and life early warning method for an energy storage lithium battery according to claim 2, wherein the method comprises the following steps:
in the EIS test process, the method further comprises:
And carrying out Fourier decomposition on the measured data to calculate an impedance value, and simultaneously observing the temperature, open circuit voltage and impedance spectrum data of the battery through the BMS, and recording the data.
4. The energy storage lithium battery performance degradation and life early warning method according to claim 3, wherein the method comprises the following steps:
Charging the battery to a specified SOC and standing before performing EIS testing on the battery specifically includes:
Constant-current charging is carried out on the battery; constant voltage charging is carried out when the voltage of the battery reaches the rated voltage, and charging is stopped when the current reaches the charging cut-off current; then constant-current discharge is carried out on the battery, and when the battery reaches the discharge cut-off voltage, the discharge is stopped, so that the battery is a cycle failure;
and charging the energy storage lithium battery with fixed capacity to 80-100% of the interval through charge and discharge circulation, and performing EIS test every 5% of SOC in the interval, wherein the initial time of the EIS test is a time point of 10min after the charging of every 5% of SOC is finished, wherein the battery is required to be subjected to test after being subjected to standing for 2H at the end point of the interval, and the scanning frequency ranges from lkHz to 100mHz.
5. The method for early warning of performance degradation and life of an energy storage lithium battery according to claim 4, wherein the method comprises the steps of:
In the step S4 of the above-mentioned method,
In the charge-discharge cycle, the battery is kept still after being fully charged, the voltage is reduced to the platform voltage at the moment, the battery which is reduced to the platform voltage within the preset time is selected, and the internal resistance characteristic of the battery is obtained by utilizing the RC equivalent circuit model at 5s, 10s and 50s after the voltage is reduced.
6. The method for early warning of performance degradation and life of an energy storage lithium battery according to claim 5, wherein the method comprises the steps of:
the obtaining the internal resistance characteristic of the battery by using the RC equivalent circuit model specifically comprises the following steps:
the internal resistance of the battery is equivalent to a series resistance element, a second-order RC equivalent circuit model is established based on the open circuit voltage at two ends of the battery, and the mathematical expression of the model is as follows:
Wherein Uocv is open circuit voltage, I is current, end voltage of Uo second-order RC equivalent circuit, R0 is ohmic internal resistance, R1 and R2 are polarized internal resistance, C1 and C2 are polarized capacitance, and U1 and U2 are voltages on R1 and R2 respectively; in the process of constant current discharge of the battery, the dynamic circuit electric quantity expression is as follows:
At the standing moment when the battery is charged, according to The method is characterized in that the method is an identification basis of ohmic internal resistance R0, wherein Em is peak voltage when charging to a certain SOC value, and Uo (0) is initial terminal voltage in a standing stage;
According to Obtaining a time constant tau, wherein U1 (0), U2 (0) is the initial voltage at two ends of the capacitor at the moment of ending each pulse; τ is the polarization effect response time;
In the 80% -100% constant current charging process, standing for 1min every 5% SOC, identifying parameter values when standing for 5s, 10s and 50s, and in a standing time period, the current input is 0, and can be regarded as response when RC link zero input is performed, wherein the terminal voltage can be expressed as:
The voltage at two ends of the polarized internal resistance is as follows:
The battery polarization voltage is basically unchanged at the moment of the end of charging, and can be obtained by the following steps:
Wherein tk is the loading time for 5% SOC charging, R1 and R2 when charging-standing for 5s, 10s and 50s can be obtained by substituting the obtained charging-static of UE (0), charging-static of U2 (0), charging-static of tau 1 and charging-static of tau 2; then C1 and C2 are obtained according to the time constant expression, and RC link identification parameters in standing for 5s, 10s and 50s are completed;
and calculating total internal resistance Rtotal=R0+R1+R2, and taking the battery with the maximum total internal resistance Rtotal as a standard for selecting one thousandth of batteries.
7. The energy storage lithium battery performance degradation and life early warning method according to claim 6, wherein the method comprises the following steps:
The step S6 specifically comprises the following steps:
Observing a second-order RC parameter to identify whether the screened battery with the resistance value being 0.1% in front of all batteries has external faults or not, and if no obvious appearance damage exists, further performing ultrasonic detection; based on the ultrasonic transmission principle, the electrolyte infiltration condition inside the battery is scanned, the electrolyte is analyzed to be unevenly distributed or the part where gas production occurs, and the fault reason of the battery is enhanced and analyzed.
8. The method for early warning of performance degradation and life of an energy storage lithium battery according to claim 7, wherein the method comprises the steps of:
the step S7 specifically comprises the following steps:
And (3) replacing the inner core of the battery with appearance faults and detecting that the gas yield and the lithium precipitation of the battery exceed the standards in ultrasonic detection according to the detection result of the step (S6).
9. The performance degradation and life early warning method for an energy storage lithium battery according to claim 1, wherein the method comprises the following steps:
The battery circulation environment needs to be controlled in the battery circulation process, and the influence of other factors on the experiment is reduced under the condition that the temperature is close to the room temperature.
10. A performance degradation and life early warning system for performance of an energy storage lithium battery according to the life early warning method of any one of claims 1 to 9, comprising an EIS test module, a data analysis module, a charge-discharge cycle module, a second-order RC model identification module, a fault test and identification module, characterized in that:
The EIS test module circularly selects a battery module in each cluster of power stations of the energy storage power station, repeatedly leads out voltage pins of a battery management system of the battery module, and performs EIS test on each cluster of batteries from low frequency to high frequency in different SOC intervals of the batteries;
The data analysis module is used for analyzing whether the impedance characteristic and the internal resistance characteristic of the battery are consistent or not and judging whether to continue testing or not;
The charge-discharge circulation module performs charge-discharge circulation on the battery to enable the battery to reach a specific SOC value and stand;
the second-order RC model identification module establishes a second-order RC model, and the internal resistance of the battery is identified by utilizing the RC model;
The fault test and identification module performs fault test on the appointed battery and determines the battery of which the inner core needs to be replaced according to the test result.
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