CN112433157A - Online monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery - Google Patents
Online monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery Download PDFInfo
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- CN112433157A CN112433157A CN202011182915.0A CN202011182915A CN112433157A CN 112433157 A CN112433157 A CN 112433157A CN 202011182915 A CN202011182915 A CN 202011182915A CN 112433157 A CN112433157 A CN 112433157A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 54
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 title claims abstract description 17
- 229910052744 lithium Inorganic materials 0.000 title claims abstract description 17
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 13
- 238000012512 characterization method Methods 0.000 claims abstract description 11
- 238000005070 sampling Methods 0.000 claims abstract description 11
- 238000000034 method Methods 0.000 claims abstract description 9
- 239000000178 monomer Substances 0.000 claims abstract description 8
- 238000004891 communication Methods 0.000 claims abstract description 4
- 230000026676 system process Effects 0.000 claims abstract description 4
- 238000010606 normalization Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 5
- 239000000463 material Substances 0.000 abstract description 4
- 210000004027 cell Anatomy 0.000 description 14
- 238000010586 diagram Methods 0.000 description 4
- 238000004146 energy storage Methods 0.000 description 4
- 239000011244 liquid electrolyte Substances 0.000 description 3
- 230000032683 aging Effects 0.000 description 2
- 238000002485 combustion reaction Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000002269 spontaneous effect Effects 0.000 description 2
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000008602 contraction Effects 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 210000001787 dendrite Anatomy 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 229910001416 lithium ion Inorganic materials 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000005486 organic electrolyte Substances 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 238000007789 sealing Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
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Classifications
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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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/40—Investigating fluid-tightness of structures by using electric means, e.g. by observing electric discharges
-
- 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
- G01R31/50—Testing of electric apparatus, lines, cables or components for short-circuits, continuity, leakage current or incorrect line connections
- G01R31/52—Testing for short-circuits, leakage current or ground faults
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4228—Leak testing of cells or batteries
-
- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
- H01M10/4285—Testing apparatus
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
The invention relates to an online monitoring and distinguishing system for internal short circuit and leakage faults of a power lithium battery. The invention comprises a battery sampling module and a monitoring system, wherein the monitoring system comprises an algorithm for judging short-circuit faults and leakage faults in a battery by using real-time state data of each battery cell in a battery pack; the battery sampling module collects real-time state data of each monomer battery cell in the battery pack in real time and uploads the real-time state data to the monitoring system through the communication bus; the monitoring system processes the collected real-time state data, and comprises a method for extracting fault characterization quantities based on a statistic rule of consistency of cell voltages in the battery pack and an algorithm for online monitoring and distinguishing internal short circuit faults and leakage faults of the battery through the characterization quantities. The monitoring system can monitor the single fault of the battery in real time, does not need to disassemble and detect the single battery, can greatly save manpower and material resources, has higher real-time performance, and can realize early discovery, early control and early solution of the fault.
Description
Technical Field
The invention relates to an online monitoring and distinguishing system for internal short circuit and leakage faults of a power lithium battery, belongs to the technical field of safety of energy storage systems of power electronics and the power lithium battery, and particularly relates to a new energy automobile and large-scale power energy storage.
Background
The short circuit in the battery is one of the main reasons of the self-ignition accident of the battery. The phenomenon that the anode and the cathode of a battery monomer are in direct contact due to the failure of a diaphragm is avoided. The causes of short circuits in power cells are mainly classified into three types, the first is internal short circuits due to external abuse, such as deformation and tearing of a separator due to mechanical abuse, such as squeezing, puncturing, etc., dendrite penetration due to electrical abuse, such as overcharge, overdischarge, etc., and contraction and folding of the separator due to high temperature caused by thermal abuse. The second is that the battery defects are caused by the problems of metal impurities contained in the material, dust in the environment, burrs generated during die cutting and the like in the manufacturing process of the battery. The third is that the battery is charged at low temperature too frequently in the application process or the charging circuit is too large, so that lithium is separated from the surface of the negative electrode, and an internal short circuit phenomenon is caused. The second and third cases produce internal short circuits that are initially relatively mild and do not immediately trigger thermal runaway.
In addition, leakage and overheating caused by battery aging are also important factors causing battery thermal runaway and spontaneous combustion. Conventional liquid organic electrolytes organic liquid electrolytes are used in almost all commercial batteries due to their advantage of high conductivity in lithium ions. The liquid electrolyte always has the risk of leakage, and the leakage can be caused by poor sealing effect, aging, overcharge, internal pressure increase, physical damage and the like; the flammability of the liquid electrolyte causes potential safety hazards, which may cause safety accidents such as external short circuits.
Internal short circuit and leakage faults are the main causes of spontaneous combustion of the battery and are researched and valued by various scholars. Particularly, in the application of new energy vehicles and large-scale electric power energy storage, the two faults are quickly and effectively monitored on line, and the battery safety is directly related. On one hand, the current monitoring scheme in the industry does not consider the random error in the battery pack, and does not have a simple, convenient and easy characteristic quantity extraction method to filter out the influence caused by the random error, so that misjudgment can be caused, and the monitoring accuracy is not high. On the other hand, in the current online monitoring scheme, a method for clearly distinguishing an internal short circuit fault from a leakage fault does not exist, the detected fault problem cannot be subjected to symptomatic medicine administration, and the best fault control means is adopted.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the invention provides an on-line monitoring and distinguishing system for internal short circuit and leakage faults of a power lithium battery, which monitors the performance indexes of the battery in real time, quickly determines a fault single body and the fault type of the fault single body, and greatly improves the running safety of a large power battery energy storage system.
The technical scheme of the invention is as follows: the online monitoring and distinguishing system for the internal short circuit and the leakage fault of the power lithium battery comprises a battery sampling module and a monitoring system, wherein the monitoring system comprises an algorithm for judging the internal short circuit fault and the leakage fault of the battery by utilizing real-time state data of each battery cell in a battery pack;
the battery sampling module is used for acquiring real-time state data of each single battery cell in the battery pack in real time and then uploading the real-time state data to the monitoring system through the communication bus;
the monitoring system processes the collected real-time state data, and comprises a method for extracting fault characterization quantities based on a statistic rule of consistency of voltage of single cells of the battery pack, and an algorithm for online monitoring and distinguishing internal short circuit faults and leakage faults of the battery through the characterization quantities.
As a further aspect of the present invention, each real-time status data comprises: battery pack current, voltage of each single battery cell, total voltage of the battery pack and temperature of the battery pack.
As a further scheme of the invention, the battery sampling module uploads the summary information of each real-time state data to the monitoring system, and the monitoring system is communicated with the early warning system.
As a further scheme of the invention, the algorithm for monitoring and distinguishing the internal short circuit fault and the leakage fault of the battery on line through the characterization quantity comprises the following steps:
step one, obtaining real-time state data of each battery cell monomer from BMS data stream;
processing the real-time state data to obtain a mean value and a standard deviation of the characteristic quantity and then obtain an extreme value normalization result of the characteristic quantity;
and step three, judging whether a single battery cell is in a fault state or not by utilizing the characteristic quantity, and distinguishing an internal short circuit state from a leakage state.
As a further scheme of the invention, in the algorithm of the short-circuit fault and the leakage fault, the short circuit in each battery cell of the battery pack is represented by that the characteristic quantity P + is less than 6 or does not exceed 10 cycles, the value is more than 6, and P-is 100 continuous cycles and is less than-6; the leakage of the battery pack core becomes characterized in that the characteristic quantity P +100 cycles is more than 6, and the value of P-is more than-6 or no more than 10 cycles is less than-6.
As a further scheme of the present invention, the monitoring system is implemented in a form of an embedded control panel, a local background or cloud computing in practical application.
The invention has the beneficial effects that:
1. the method is simple and feasible, and can distinguish the internal short-circuit fault and the leakage fault of the battery pack battery cell monomer.
2. The novel system for monitoring, distinguishing and early warning the short circuit and the leakage fault in the battery on line has practical application significance, is convenient to add into almost all power battery management modules, and reduces the calculation difficulty of on-line real-time detection;
3. the monitoring system can monitor the single fault of the battery in real time, does not need to disassemble and detect the single battery, can greatly save manpower and material resources, has higher real-time performance, and achieves early discovery, early control and early solution of the fault.
Drawings
FIG. 1 is a block diagram of an online monitoring and distinguishing system for internal short circuit and leakage faults of a power lithium battery;
FIG. 2 is a flow chart of a method for online monitoring and distinguishing between short circuit and leakage faults in a battery;
FIG. 3 is a real-time waveform of the voltage of 8 cells in an example experiment;
FIG. 4 is P+(X) a real-time data plot;
FIG. 5 is P-(X) real-time data curve diagram.
Detailed Description
The invention is further described with reference to the following figures and specific examples.
Example 1: as shown in fig. 1-5, the on-line monitoring and distinguishing system for internal short circuit and leakage fault of a power lithium battery includes a battery sampling module and a monitoring system, wherein the monitoring system includes an algorithm for determining the internal short circuit fault and leakage fault of the battery by using real-time status data of each battery cell in a battery pack;
the invention can be applied to various scenes, in this example, a battery pack consisting of 8 batteries, as shown in fig. 1, voltage data of 8 batteries are detected by a battery sampling module; then uploading the monitoring system through a communication bus;
the monitoring system processes the collected voltage data, and comprises a method for extracting fault characterization quantities based on a statistic rule of consistency of cell voltages in the battery pack and an algorithm for online monitoring and distinguishing internal short circuit faults and leakage faults of the battery through the characterization quantities.
As a further scheme of the invention, the algorithm for monitoring and distinguishing the internal short circuit fault and the leakage fault of the battery on line through the characterization quantity comprises the following steps:
step one, obtaining real-time state data of each battery cell monomer from BMS data stream;
processing the real-time state data to obtain a mean value and a standard deviation of the characteristic quantity and then obtain an extreme value normalization result of the characteristic quantity;
and step three, judging whether a single battery cell is in a fault state or not by utilizing the characteristic quantity, and distinguishing an internal short circuit state from a leakage state.
Specifically, the obtained 8 pieces of battery data X are subjected to1、X2、X3···X8Calculating the acquired real-time data in real time, and removing two extreme values Xmax、XminAnd then, calculating the average value of the whole to obtain:
further determining the overall standard deviation
Then, normalization processing is carried out on the parameters through a statistical method to obtain dimensionless parameters, so that further judgment can be conveniently carried out. The normalized dimensionless parameter can be calculated as follows:
obtaining the characteristic parameter P of the battery pack+(X) and P-After (X), according to the flow of fig. 2, it is determined whether the value is outside the threshold, and if so, the continuous time of the value outside the threshold is further observed, so as to avoid erroneous determination caused by data fluctuation. And finally, judging the type of the fault according to different indexes of the internal short circuit and the battery leakage.
FIG. 3 is a real-time waveform of 8 batteries during the experiment, showing that the output voltage of the single battery No. 1 gradually decreases along with the progress of the charging and discharging process, and the difference between the output voltage and other normal batteries is larger and larger, and further observing P+(X) and P-The real-time data of (X) are shown in fig. 4 and 5.
By observing the P-curve schematic diagram, when the value of P-is less than-6 and lasts for 100 sampling periods, the value is 14959s in the diagram, the mean value difference between the fault battery and the normal battery at the moment is about 0.019V, and conversely, when the value of P + is smaller, the internal short circuit fault of the battery can be identified before the voltage of the battery is greatly changed.
As a further scheme of the present invention, the monitoring system is implemented in a form of an embedded control panel, a local background or cloud computing in practical application.
According to the invention, the information such as the voltage of each monomer of the lithium battery pack is collected in real time through the battery sampling module and is uploaded to the monitoring system, and then the statistical rule normalization processing is carried out on the information to obtain the characteristic quantity, so that the non-fault voltage statistical deviation in the battery pack is filtered, and the fault monitoring accuracy is improved.
The two faults are distinguished according to different characteristic quantity changes of the internal short circuit and the leakage: if the specific voltage normalization characteristic quantity is detected to be higher than the threshold value for a long time (time is set manually), the battery can be judged to have a leakage fault, and if the specific voltage normalization parameter is lower than the threshold value for a long time, the battery is determined to have an internal short circuit fault. This monitoring system can real time monitoring battery's free fault, need not dismantle the detection to battery monomer, and the material resources of using manpower sparingly that can be very big have higher real-time, accomplish that the trouble is early to discover, early control, early solution.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes and modifications can be made within the knowledge of those skilled in the art without departing from the spirit of the present invention.
Claims (6)
1. The online monitoring and distinguishing system for the internal short circuit and the leakage fault of the power lithium battery is characterized in that: the monitoring system comprises an algorithm for judging short-circuit faults and leakage faults in the battery by using real-time state data of each battery cell in the battery pack;
the battery sampling module is used for acquiring real-time state data of each single battery cell in the battery pack in real time and then uploading the real-time state data to the monitoring system through the communication bus;
the monitoring system processes the collected real-time state data, and comprises a method for extracting fault characterization quantities based on a statistic rule of consistency of voltage of single cells of the battery pack, and an algorithm for online monitoring and distinguishing internal short circuit faults and leakage faults of the battery through the characterization quantities.
2. The on-line monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery as claimed in claim 1, wherein: each real-time status data includes: battery pack current, voltage of each single battery cell, total voltage of the battery pack and temperature of the battery pack.
3. The on-line monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery as claimed in claim 1, wherein: and the battery sampling module uploads the summary information of each real-time state data to a monitoring system, and the monitoring system is communicated with the early warning system.
4. The on-line monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery as claimed in claim 1, wherein: the algorithm for online monitoring and distinguishing the internal short circuit fault and the leakage fault of the battery through the characterization quantity comprises the following steps:
step one, obtaining real-time state data of each battery cell monomer from BMS data stream;
processing the real-time state data to obtain a mean value and a standard deviation of the characteristic quantity and then obtain an extreme value normalization result of the characteristic quantity;
and step three, judging whether a single battery cell is in a fault state or not by utilizing the characteristic quantity, and distinguishing an internal short circuit state from a leakage state.
5. The on-line monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery as claimed in claim 1, wherein: in the algorithm of the short-circuit fault and the leakage fault, the short circuit in each battery cell of the battery pack is represented by a characteristic quantity P + less than 6 or not more than 10 cycles, the value is more than 6, and P-is continuously 100 cycles and is less than-6; the leakage of the battery pack core becomes characterized in that the characteristic quantity P +100 cycles is more than 6, and the value of P-is more than-6 or no more than 10 cycles is less than-6.
6. The on-line monitoring and distinguishing system for internal short circuit and leakage fault of power lithium battery as claimed in claim 1, wherein: in practical application, the monitoring system is realized in the form of embedded control panel, local background or cloud computing.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113484780A (en) * | 2021-06-02 | 2021-10-08 | 苏州领湃新能源科技有限公司 | Method for testing short-circuit resistance in soft package battery |
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