CN114839251A - Defect identification method, defect identification device, potential sensor, battery, medium and product - Google Patents
Defect identification method, defect identification device, potential sensor, battery, medium and product Download PDFInfo
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- CN114839251A CN114839251A CN202210269850.6A CN202210269850A CN114839251A CN 114839251 A CN114839251 A CN 114839251A CN 202210269850 A CN202210269850 A CN 202210269850A CN 114839251 A CN114839251 A CN 114839251A
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
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- 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
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- 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
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- Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02E60/10—Energy storage using batteries
Abstract
The application relates to a defect identification method, a defect identification device, a potential sensor, a battery, a medium and a product. The defect identification method is applied to a battery, the battery comprises a battery body and a potential sensor, the potential sensor comprises a reference electrode and a potential signal processing device, the reference electrode is implanted into the battery body, and the potential signal processing device is connected with the reference electrode and the positive electrode or the negative electrode of the battery, and the method comprises the following steps: the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time length; the measuring voltage is the corresponding voltage of a reference electrode and a measured working electrode in the battery body; and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether defects exist in the battery body. By adopting the method, the defects and faults under the service state of the battery can be identified on line.
Description
Technical Field
The application relates to the technical field of sensors, in particular to a defect identification method, a defect identification device, a potential sensor, a battery, a medium and a product.
Background
At present, lithium ion batteries are more and more widely applied, defects and faults are inevitable in the production and use processes of the lithium ion batteries, and further potential safety hazards are caused, so that the lithium ion batteries are very important for detecting the defects and the faults of the batteries.
In the related art, when defect identification is performed on a battery, a machine vision technology is mostly adopted to perform identification processing on an obtained image of a shallow surface of the battery, whether the shallow surface of the battery has defects and faults is determined according to an identification result, and the method is limited to scene detection before the battery leaves or after the battery is retired, and cannot perform safety monitoring in a service state of the battery.
That is, when the battery is in service and has a defect or a fault, online identification of the battery cannot be realized by using the above technology.
Disclosure of Invention
In view of the above, it is necessary to provide a defect identification method, a device, a potential sensor, a battery, a storage medium, and a product, which can identify internal defects and failures of a battery, in view of the above technical problems.
In a first aspect, the present application provides a defect identification method, which is applied to a battery, the battery includes a battery body and a potential sensor, the potential sensor includes a reference electrode and a potential signal processing device, the reference electrode is embedded in the battery body, the potential signal processing device is connected with the reference electrode and a positive electrode or a negative electrode of the battery, and the method includes:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In one embodiment, the voltage threshold range includes an upper voltage threshold and a lower voltage threshold, and the determining whether the battery body has a defect by performing a difference analysis according to each measured voltage and a preset voltage threshold range includes:
matching each measured voltage with an upper limit voltage threshold and a lower limit voltage threshold, and determining a matching result;
and determining whether the inside of the battery body has defects according to the matching result.
In one embodiment, determining whether there is a defect inside the battery body according to the matching result includes:
if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body;
and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that the defect exists in the battery body.
In one embodiment, the voltage threshold range includes a mean square error voltage threshold, and the determining whether the inside of the battery body has defects according to the difference analysis performed on each measured voltage and the preset voltage threshold range includes:
calculating the mean square error of each measured voltage, and determining the mean square error voltage;
comparing the mean square error voltage with a mean square error voltage threshold value to determine a comparison result;
and determining whether the inside of the battery body has defects according to the comparison result.
In one embodiment, determining whether there is a defect inside the battery body according to the comparison result includes:
calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold;
and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
In one embodiment, determining whether there is a defect inside the battery body according to the determination result includes:
if the absolute value of the difference is not greater than the threshold value of the difference, determining that no defect exists in the battery body;
and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body.
In a second aspect, the application also provides a defect identification device. The above-mentioned device includes:
the voltage acquisition module is used for acquiring each measurement voltage corresponding to the reference electrode within a preset time length; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the defect identification module is used for performing difference analysis according to the measured voltages and a preset voltage threshold range to determine whether defects exist in the battery body.
In a third aspect, the present application also provides a potentiometric sensor. The potential sensor comprises a reference electrode and a potential signal processing device which are connected with each other, the potential signal processing device comprises a memory and a processor, the memory stores a computer program, and the processor realizes the following steps when executing the computer program:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time length; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In a fourth aspect, the present application further provides a battery. The battery comprises a battery body, the potential sensor of the third aspect, and the reference electrode is implanted in the battery body and connected to the positive electrode or the negative electrode of the battery.
In a fifth aspect, the present application further provides a computer readable storage medium having a computer program stored thereon, the computer program when executed by a processor implementing the steps of:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In a sixth aspect, the present application further provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, performs the steps of:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
According to the defect identification method, the defect identification device, the potential sensor, the battery, the storage medium and the product, the battery body is connected with the potential sensor, the potential sensor comprises the reference electrode and the potential signal processing device, the reference electrode is implanted into the battery body, the potential signal processing device is connected with the reference electrode and the positive electrode or the negative electrode of the battery, then each measurement voltage corresponding to the reference electrode within the preset time is obtained through the potential signal processing device, and the measurement voltage and the preset voltage threshold range are subjected to difference analysis to judge whether defects exist in the battery body. In the method, the reference electrode is directly implanted into the battery, and the potential signal processing device is connected with the reference electrode and the anode or the cathode of the battery, so that the absolute voltage corresponding to the anode or the cathode in the battery can be obtained, but not the relative potential difference between the anode and the cathode, and the defect and the fault in the battery can be accurately judged by performing difference analysis on the voltage threshold range of the anode or the cathode of the defect-free battery. In addition, because the reference electrode is connected with the potential signal processing device and implanted into the battery, namely, the battery can be always kept connected with the potential sensor, the online identification of defects and faults of the battery in a service state can be realized, namely whether the defects and faults exist in the service state of the battery can be judged.
Drawings
FIG. 1 is a schematic diagram of the structure of a battery in one embodiment;
FIG. 2 is a schematic flow chart illustrating defect diagnosis in one embodiment;
FIG. 3 is a schematic diagram of a potential signal processing device;
FIG. 4 is a negative-reference resting potential obtained by a potential sensor monitoring a cell according to one embodiment;
FIG. 5 is a positive-negative potential curve obtained by a potential sensor monitoring a full cell over time in one embodiment;
FIG. 6 is a positive-negative potential curve obtained by a potential sensor monitoring a full cell over time in one embodiment;
FIG. 7 is a flowchart illustrating a defect identification method according to one embodiment;
FIG. 8 is a positive and negative cycling curve for a battery with internal defects as measured by the prior art;
fig. 9 is a graph of cell capacity and coulombic efficiency for a cell with internal defects measured using the prior art;
FIG. 10 is a negative electrode-reference potential curve of a battery with internal defects measured by a potential sensor according to one embodiment;
FIG. 11 is a positive-negative cycling curve for a battery implanted with an external defect, as measured by the prior art;
FIG. 12 is a graph of cell capacity and coulombic efficiency of a cell implanted with an external defect measured using the prior art;
FIG. 13 is a negative-reference potential curve of a cell implanted with an external defect as measured by a potential sensor in one embodiment;
FIG. 14 is a flowchart illustrating a defect identification method according to another embodiment;
FIG. 15 is a flowchart illustrating a defect identification method according to another embodiment;
FIG. 16 is a diagram illustrating a structure of a defect detecting apparatus according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
At present, lithium ion batteries are widely applied, internal defects such as impurities, foreign matters, folded corners, material falling and the like are easily generated in the production process of the batteries, external defects such as extrusion, needling and the like are possibly generated in the use process of the batteries, the phenomena of thermal runaway and the like of the batteries caused by local heat generation or internal short circuit are generated due to uneven lithium ion deposition of positive and negative electrodes of the batteries, and the defects bring serious potential safety hazards to the use of the batteries, so the health state and the safety state of the batteries are particularly important in the production or use process.
However, when the existing battery management system monitors the running safety state of the power battery or the energy storage battery, only the relative measurement between the positive working electrode and the negative working electrode can be realized, so that even if the battery introduces defects such as impurities in the production process, the battery management system cannot monitor that the internal defects exist in the battery. In addition, the reference electrode is a common battery analysis and detection means, which is necessary for recognizing the change of the positive electrode and the negative electrode potential and further realizing the early warning and monitoring of the battery safety condition.
In another prior art, when defect recognition is performed on a battery, machine vision technology is mostly used to perform recognition processing on an obtained image of the outer surface of the battery, and whether defects and faults occur on the outer surface or a shallow surface of the battery is determined according to the recognition result. However, when a defect or a fault occurs inside the battery, the technology cannot identify the defect or the fault inside the battery, and cannot perform online monitoring on the battery in a service state.
In summary, the above-mentioned technologies cannot identify whether a defect exists inside the battery, and the defect identification method, apparatus, potential sensor, battery, storage medium and computer program product provided by the present application can solve the above-mentioned technical problems, implement diagnosis of the internal defect of the battery, and implement diagnosis of the defect in the service state of the battery.
The defect identification method provided by the embodiment of the application can be applied to a battery capable of identifying battery defects caused by damage scenes inside and outside the battery. Referring to fig. 1, the battery may include a battery body, and a potential sensor including a reference electrode implanted inside the battery body and a potential signal processing device connected to the reference electrode and a positive electrode or a negative electrode of the battery. In the case of defect detection, the reference electrode can be connected to the positive or negative electrode of the battery, i.e. the reference electrode can be connected to the negative or positive electrode of the battery body via a respective tab. It should be noted that the content in fig. 1 is only an example, and does not affect the essential content of the technical solution of the present application.
In addition, the battery can be a vehicle-mounted battery, an energy battery, a consumer battery and the like, and the battery can detect the absolute voltage of the battery electrode in real time during the whole service period of the battery due to the potential sensor, so as to detect whether the battery has defects, thereby ensuring the use safety of the battery and avoiding the occurrence of potential safety hazards.
The following description is made of the process for preparing the reference electrode:
the reference electrode is composed of a conductive and insulating double-sided substrate and a sensitive material, the reference electrode substrate is a flexible insulating substrate, and the preparation process comprises the steps of firstly coating a conductive coating on one side of the flexible insulating substrate, and then coating the sensitive material load on the conductive coating to obtain the reference electrode.
Specifically, the reference electrode flexible insulating substrate can be various battery diaphragms such as polyethylene, polypropylene, polyethylene polypropylene composite diaphragms, Polyimide (PI) diaphragms, aramid diaphragms, ceramic diaphragms, Polyester (PET) non-woven fabrics and other base membranes and composite diaphragms, and can also be other polymer films and composite membranes such as PI films, PET films, polyurethane and the like; also includes inorganic films such as glass fiber and organic-inorganic composite films.
The conductive coating can be a metal material, such as copper, aluminum, and the like, and can also be nanoparticles, such as gold nanoparticles, silver nanoparticles, and the like. The coating mode of the conductive coating comprises methods such as photoetching, ultrafast laser processing, microelectronic printing, magnetron sputtering and the like. The conductive coating pattern is realized by adopting a micro-nano processing technology, and the coating area and the coating shape on the insulating substrate can be any, for example, the coating area and the coating shape can occupy the whole area or part area of one side of the insulating substrate, and also can be any geometric pattern, such as ring, rectangle, square, honeycomb, circle and the like. The conductive layer is coated on one side of the insulating substrate in part of area, so that the blocking effect of lithium ions in the battery can be reduced, the conductivity of the battery is higher, and the service life of the reference electrode is longer. The realization of the random area and the pattern of the conductive coating can adopt a laser process to etch away the edge conductive material, commonly known as a subtractive process, can also transfer a metal coating needing to be designed and processed onto a film substrate by methods such as transfer printing, and can also carry out coating by presetting a patterned template.
Before the sensitive material load is coated on the conductive layer, if the flexible insulating substrate is a non-porous substrate, the substrate needs to be subjected to micropore treatment in advance, the micropore treatment mode comprises drilling, hole grinding, ultrasonic punching, laser direct punching, a laser cutting method, femtosecond laser, single-pulse laser punching, multi-pulse laser punching and the like, and the hole structure comprises a barrel-shaped hole, a conical hole, a straight-through hole and the like. If the flexible insulating substrate is a porous substrate, micropore treatment is not needed, the flexible insulating substrate is directly adopted to prepare the reference electrode, and if a lithium battery diaphragm material is adopted, punching treatment can also not be carried out.
In addition, the sensitive material may include active materials, conductive agents, binders, dispersants, defoaming agents, and other components, wherein the active materials include, but are not limited to, lithium titanate, titanium dioxide, metallic lithium, lithium iron phosphate, lithium vanadium phosphate, and other positive and negative electrode materials, and other electrode materials capable of providing a stable potential; the conductive agent includes but is not limited to conductive carbon black, Super P, C60, single-arm carbon nanotube, multi-arm carbon nanotube, Ketjen black, graphene, Mxene and other conductive additives or a mixture of several components; binders include, but are not limited to, high molecular weight polymers or copolymers such as polyvinylidene fluoride, polyvinylidene fluoride-hexafluoropropylene copolymers, polyacrylic acid, polyacrylates, polyacrylic acid copolymers, sodium carboxymethylcellulose; defoaming agents and dispersants, including various types of water-soluble and organic additives.
The application of the flexible film substrate and the micro-nano processing technology of the conductive pattern endow the film material with the function of conducting and transmitting potential signals, and the flexibility of the flexible film substrate can also enhance the mechanical integrity of the potential sensor; the thin film laser drilling technology can enable the electrolyte and lithium ions to be efficiently transmitted when the thin film material is implanted between the positive electrode and the negative electrode of the battery, and the barrier effect on the battery is reduced; the active material load can ensure that a stable potential is provided in a battery environment to serve as a reference of the positive electrode potential or the negative electrode potential, and the binder can ensure the adhesive strength of the active material and the film substrate and improve the electrochemical stability and the mechanical adhesion of a surface interface.
The reference electrode can be prepared by the above technology, and then, as shown in fig. 2, the prepared reference electrode can be connected with a potential signal processing device to obtain a potential sensor, and the potential sensor is inserted/implanted into the battery body and connected with the positive electrode or the negative electrode inside the battery body, so as to collect the voltage change between the positive electrode or the negative electrode inside the battery body and the reference electrode, and transmit the voltage change to the potential signal processing device for processing (i.e. data collection and transmission).
Further, the schematic diagram of the internal structure of the above-mentioned electric potential sensor is shown in fig. 3, and the electric potential sensor includes an electric potential signal processing device and a reference electrode connected to each other, where the electric potential signal processing device includes a microprocessor, an electric potential acquisition module, a wireless transmission module, and a battery charging module.
Specifically, the potential acquisition module may be connected to a reference electrode, and the reference electrode is connected to the positive electrode or the negative electrode of the battery body, and is configured to acquire a voltage corresponding to the positive electrode or the negative electrode in the battery body within a preset time.
The microprocessor can be connected with the potential acquisition module and used for acquiring the voltage corresponding to the anode or the cathode of the battery body within the preset time measured by the potential acquisition module, and the microprocessor can comprise an analog signal converter and used for converting the acquired voltage into a digital signal and analyzing and processing the digital signal.
Wireless transmission module can link to each other with microprocessor for voltage transmission to the terminal after processing microprocessor, the terminal includes server, computer, cell-phone, high in the clouds etc. and this wireless transmission module carries out wired or wireless mode's communication with outside terminal, and wherein wired mode can adopt the USB mode to realize, and wireless mode can adopt other modes such as near-range wireless communication transmission (NFC), removal cellular network, bluetooth, WIFI to realize.
And the battery charging module is used for supplying power to each module in the potential signal processing device, and can also be used for supplying power to the battery body and supplying power to other batteries.
In summary, the reference electrode and the potential signal processing device can be implanted into the battery body after being prepared into the potential sensor, so that the potential change of the positive electrode or the negative electrode in the battery body can be accurately monitored, and the voltage measured by the reference electrode can be rapidly processed and transmitted, so that the rapid diagnosis of the defects of the battery under the static condition can be realized, and the diagnosis of the defects of the battery in the dynamic (i.e. operation) process can also be realized.
In addition, after the potential sensor prepared by the reference electrode and the potential signal processing device is implanted into the battery body, the performance of the battery is not adversely affected, and specific effects can be seen in fig. 4-6, fig. 4 is that when the reference electrode is connected with the negative electrode of the battery, the potential signal processing device detects the potential of the negative electrode when the battery is not in operation, and because the battery is not in operation, the detected value is theoretically a voltage value with small fluctuation, the potential detected by the sensor when the negative electrode is still in operation should also be a voltage value with small fluctuation, and the test result in fig. 4 is also a voltage value with small fluctuation, so that the operation state of the implanted potential sensor can be proved to be good. Fig. 5 is a negative potential curve of a potential sensor during long-term monitoring of a defect-free battery at a current density cycle of 0.33C, fig. 6 is a potential curve of a potential sensor during long-term monitoring of a defect-free full battery at a current density cycle of 0.33C, and the data of fig. 5 and 6 have small fluctuation results, which can also show that the battery performance and the performance of an implanted potential sensor are constant.
In one embodiment, as shown in fig. 7, a defect identification method is provided, which is exemplified by the method applied to the battery in fig. 1, and the method may include the following steps:
s102, the potential signal processing device acquires each measurement voltage corresponding to the reference electrode in a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body.
In this step, the preset time period may be set according to actual conditions, and may be, for example, 1 hour, 5 hours, 10 hours, or the like, and may also be a full life cycle time period when the battery is running. The voltage measurement refers to a voltage difference between a measured working electrode inside the battery body and a reference electrode or a counter electrode when the battery is powered on, and the measured working electrode may be a negative electrode of the battery or a positive electrode of the battery, that is, a voltage between the positive electrode and the reference electrode or a voltage between the negative electrode and the reference electrode may be measured, and certainly, a voltage change between the positive electrode and the negative electrode is also included.
Specifically, when the potential sensor is implanted into the battery body, a reference electrode in the potential sensor is mainly implanted into the battery body, the potential signal processing device is connected with the reference electrode and the anode or the cathode of the battery, and the voltage at the electrode at each moment within a preset time can be measured and obtained through the reference electrode, so that the measured voltage at a plurality of moments can be obtained.
And S104, the potential signal processing device performs difference analysis according to the measured voltages and a preset voltage threshold range to determine whether the interior of the battery body has defects.
The preset voltage threshold range may be obtained by performing voltage measurement on a plurality of non-defective batteries to obtain a calibration curve under normal conditions, and performing mean value processing, median value processing, mean square error processing, and the like on the measured voltage values of the plurality of batteries. The voltage threshold range may include two limits, may include only one limit, or may have another form, such as a threshold range formed by a charge/discharge curve shape. The defect of the battery body may be any defect which is different from the battery in the normal state, that is, any defect which affects the battery health state or the charge state and the like, such as the condition of lithium ion deposition of the negative electrode which is different from the normal battery, and the like, and may be in other forms.
Specifically, after the measured voltages and the voltage threshold ranges at each time are obtained, difference analysis may be performed on each measured voltage and the voltage threshold range, and whether a defect exists in the battery is determined according to a comparison result of each measured voltage, for example, if the comparison result of each measured voltage indicates that most of the measured voltages exceed the voltage threshold range, it is determined that the defect exists in the battery. The measured voltage at each time may be compared with a voltage threshold range after being processed, and whether a defect exists in the battery may be determined according to the comparison result, for example, if the result after each measured voltage processing exceeds the voltage threshold range, the defect exists in the battery. Of course, the preset voltage threshold range may be obtained through a calibration curve of a normal operating condition, or may be obtained in other manners. The method for performing difference analysis on each measured voltage and a preset voltage threshold range can comprise processing methods of extracting characteristic parameters from linear fitting/nonlinear fitting curves such as charge-discharge cut-off voltage threshold comparison, root mean square error analysis, natural logarithm comparison, covariance inspection, absolute value comparison, piecewise linear interpolation, Hermite interpolation, cubic spline interpolation, least square fitting, fast Fourier transform and the like.
For example, for the same battery with internal defects, a graph of a curve of voltage and time obtained when the battery is subjected to internal defect identification by using the prior art (the positive electrode and the negative electrode of the battery are connected to external workstations) is shown in fig. 8, and a graph of a relation of discharge capacity/coulomb efficiency and cycle number obtained in the charging and discharging processes of the battery is shown in fig. 9. When the method of the embodiment of the application is adopted to identify the defects of the battery, the obtained curve relation graph of the voltage and the time is shown in fig. 10. In general, when a defect occurs in the battery, the voltage and time curve, the discharge capacity/coulombic efficiency curve, and the cycle number curve fluctuate or become abnormal. However, as can be seen from fig. 8-10, the curves in fig. 8 and 9 have no fluctuation in the prior art, i.e., they cannot identify the defects existing inside the battery, while the curves obtained by the method of the embodiment of the present application have fluctuation, i.e., the defects existing inside the battery can be identified.
Of course, the method in the embodiment of the present application may also detect the existence of defects when the battery has defects caused by external damage, and the implementation process and principle are the same as the implementation principle and process of internal defects, which are not described herein again.
Illustratively, for the same defect-free battery, an external defect (e.g., a crushed battery) is implanted at some point during operation of the battery, and the battery is subject to the external defect. When the external defect identification is performed on the battery by adopting the prior art (the positive electrode and the negative electrode of the battery are connected with an external workstation), the obtained curve relation graph of voltage and time is shown in fig. 11, and meanwhile, the obtained relation graph of discharge capacity/coulombic efficiency and cycle number in the charging and discharging process of the battery is shown in fig. 12. When the method of the embodiment of the application is adopted to identify the defects of the battery, the obtained curve relation graph of the voltage and the time is shown in fig. 13. In general, when a defect occurs outside a battery, the voltage and time curve, the discharge capacity/coulombic efficiency curve, and the cycle number curve thereof fluctuate or become abnormal. However, as can be seen from fig. 11-13, the curves in fig. 11 and 12 have no fluctuation in the prior art, i.e., they cannot identify the defect existing outside the battery, while the curves obtained by the method of the embodiment of the present application have fluctuation, i.e., the defect existing outside the battery can be identified.
In the defect identification method, the battery body is connected with the potential sensor, the potential sensor comprises a reference electrode and a potential signal processing device, the reference electrode is implanted into the battery body, the potential signal processing device is connected with the reference electrode and the anode or the cathode of the battery, then, each measurement voltage corresponding to the reference electrode within a preset time is obtained through the potential signal processing device, and the measurement voltage and a preset voltage threshold range are subjected to difference analysis to judge whether defects exist in the battery body. In the method, the reference electrode is directly implanted into the battery, and the potential signal processing device is connected with the reference electrode and the anode or the cathode of the battery, so that the voltage corresponding to the anode or the cathode in the battery can be obtained instead of the relative potential difference between the anode and the cathode, and the defect and the fault in the battery can be accurately judged by performing difference analysis on the voltage threshold range of the defect-free battery or the anode or the cathode under normal working conditions. In addition, the reference electrode is connected with the potential signal processing device and implanted into the battery, namely, the battery can be always connected with the potential sensor, so that the online identification of defects and faults of the battery in a service state can be realized, namely, whether the defects and faults exist in the service state of the battery can be judged.
In the above embodiments, it is mentioned that whether a defect exists in the battery body is determined according to each measured voltage, a preset voltage threshold range, a charging/discharging curve shape, and the like, and two possible embodiments are described below to describe a specific determination process for determining whether a defect exists in the battery body.
In another embodiment, another defect identification method is provided, and this embodiment relates to one possible implementation of how to determine whether a defect exists inside a battery. In this embodiment, the voltage threshold range may include an upper voltage threshold and a lower voltage threshold, and based on the foregoing embodiment, as shown in fig. 14, the foregoing S102 may include the following steps:
s202, matching the measured voltages with an upper limit voltage threshold value and a lower limit voltage threshold value, and determining a matching result.
Wherein, the upper limit voltage threshold may be an upper limit value of a voltage threshold range, and the lower limit voltage threshold may be a lower limit value of the voltage threshold range, and generally, the upper limit voltage threshold may be greater than the lower limit voltage threshold; both the upper and lower voltage thresholds may be positive or negative.
In this step, after the measured voltages at the respective times are obtained, the measured voltages may be compared with an upper limit voltage threshold and a lower limit voltage threshold, whether the measured voltages exceed a voltage range section formed by the upper limit voltage threshold and the lower limit voltage threshold may be determined, and determination results corresponding to the measured voltages, that is, matching results of the measured voltages may be obtained.
And S204, determining whether the interior of the battery body has defects according to the matching result.
In this step, after obtaining the respective corresponding determination results of each measured voltage, optionally, if each measured voltage is smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, it is determined that there is no defect inside the battery body; that is, all the measured voltages are within a voltage range section composed of the upper limit voltage threshold and the lower limit voltage threshold, that is, are close to the voltage of a non-defective cell, and thus it can be considered that no defect exists in the cell.
In addition, if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, it is determined that a defect exists in the battery body. That is, if one or more measured voltages exceed a voltage range section consisting of an upper voltage threshold and a lower voltage threshold, it is considered that a defect exists inside the battery.
In the embodiment, the voltage at each moment in the preset duration is matched with the upper limit voltage threshold and the lower limit voltage threshold, so that whether defects exist in the battery can be directly judged, and the comparison mode is simple, so that the defect identification efficiency can be improved; meanwhile, the difference analysis is carried out on the voltage at each moment and the voltage threshold range, so that a relatively accurate defect identification result can be obtained, and the accuracy of obtaining the defect identification result can be improved. Further, the measured voltages are within the voltage threshold range, the battery is considered to have no defects, and at least one measured voltage exceeds the voltage threshold range, the battery is considered to have defects, so that whether the battery has defects or not can be determined more quickly through a simple comparison process, and the defect identification efficiency can be further improved.
One possible implementation of identifying defects by using the upper voltage threshold and the lower voltage threshold is provided in the above embodiment, and another possible implementation is described below.
In another embodiment, another defect identification method is provided, and this embodiment relates to another possible implementation of how to determine whether a defect exists inside a battery. In this embodiment, the voltage threshold range may include a mean square error voltage threshold, and based on the above embodiment, as shown in fig. 15, the above S102 may include the following steps:
s302, calculating the mean square error of each measured voltage and determining the mean square error voltage.
In this step, before calculating the mean square error, it is necessary to obtain an average value of each measured voltage, calculate a difference between each measured voltage and the average value, and calculate a mean square error through each difference, and record the mean square error as a mean square error voltage.
S304, comparing the mean square error voltage with the mean square error voltage threshold value, and determining the comparison result.
The mean square error voltage threshold value can be a value obtained by averaging the upper limit voltage threshold value and the lower limit voltage threshold value, or a value obtained by performing voltage measurement on a plurality of flawless batteries and performing mean square error and averaging; of course, other determined values are also possible.
Specifically, after the mean square error voltage and the mean square error voltage threshold corresponding to each measured voltage are obtained, the mean square error voltage and the mean square error voltage threshold may be compared to obtain a comparison result.
And S306, determining whether the interior of the battery body has defects according to the comparison result.
In this step, when judging whether the inside of the battery has defects through the comparison result, optionally, the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold value can be calculated; and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
That is, after the mean square error voltage and the mean square error voltage threshold corresponding to each measured voltage are obtained, the mean square error voltage threshold may be subtracted from the mean square error voltage, an absolute value of the difference is obtained by taking an absolute value of the obtained difference, and the absolute value of the difference is compared with the difference threshold, optionally, if the absolute value of the difference is not greater than the difference threshold, it is determined that there is no defect inside the battery body; and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body. The difference threshold may be set according to actual conditions, and may be, for example, 0V, 0.01V, 0.05V, or may be calibrated by using a method of normalization (for example, using a battery nominal voltage ratio), dimensionless, or the like.
In the embodiment, the mean square error voltage of each calculated measurement voltage is compared with the mean square error voltage threshold, and whether the inside of the battery has defects is determined according to the comparison result, so that the comparison process is simple, and whether the inside of the battery has defects can be determined quickly and accurately. Further, the difference absolute value of the mean square error voltage and the mean square error voltage threshold is compared with the difference threshold to judge whether the interior of the battery has defects, so that whether the interior of the battery has defects can be accurately determined, the defect diagnosis accuracy can be further improved, and the diagnosis error is avoided.
In order to better explain the technical solution of the embodiment of the present application, the following describes the technical solution of the present application with reference to a specific embodiment, and on the basis of the above embodiment, the method may include the following steps:
s1, obtaining each measuring voltage corresponding to the reference electrode in a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body; s2 or S4 is performed.
S2, matching each measured voltage with the upper limit voltage threshold and the lower limit voltage threshold.
S3, if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body; and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that the defect exists in the battery body.
And S4, calculating the mean square error of each measured voltage and determining the mean square error voltage.
And S5, calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold.
And S6, judging whether the absolute value of the difference value is larger than a preset difference value threshold value.
S7, if the absolute value of the difference is not larger than the difference threshold, determining that no defect exists in the battery body; and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body.
The steps in the flowcharts according to the embodiments described above are sequentially displayed as indicated by arrows, but the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a defect identification device for realizing the defect identification method. The implementation scheme for solving the problem provided by the apparatus is similar to the implementation scheme described in the above method, so specific limitations in one or more embodiments of the defect recognition apparatus provided below can be referred to the limitations of the defect recognition method in the foregoing, and are not described herein again.
In one embodiment, as shown in fig. 16, there is provided a defect identifying apparatus including a voltage acquiring module 11 and a defect identifying module 12, wherein:
the voltage acquisition module 11 is configured to acquire each measurement voltage corresponding to the reference electrode within a preset duration; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body;
and the defect identification module 12 is configured to perform difference analysis according to each measured voltage and a preset voltage threshold range, and determine whether a defect exists in the battery body.
In another embodiment, the defect identifying module 12 includes: a first threshold matching unit and a first defect diagnosis unit.
Specifically, the first threshold matching unit is configured to match each measurement voltage with an upper limit voltage threshold and a lower limit voltage threshold, and determine a matching result;
and the first defect diagnosis unit is used for determining whether the inside of the battery body has defects according to the matching result.
Optionally, the first defect diagnosis unit includes a first threshold comparison subunit and a second threshold comparison subunit:
the first threshold comparison subunit is used for determining that no defect exists in the battery body under the condition that each measured voltage is smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold;
and the second threshold comparison subunit is used for determining that the defect exists in the battery body under the condition that at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold.
In another embodiment, the defect identifying module 12 may include: the device comprises a determining unit, a comparing unit and a second defect diagnosing unit.
Specifically, the calculation unit compares the mean square error voltage with a mean square error voltage threshold value to determine a comparison result;
the comparison unit is used for comparing the mean square error voltage with a mean square error voltage threshold value and determining a comparison result;
and the second defect diagnosis unit is used for determining whether the inside of the battery body has defects according to the comparison result.
Optionally, the second defect diagnosis unit includes a calculation subunit and a third threshold comparison subunit, where:
the calculating subunit is used for calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold;
and the third threshold comparison subunit is used for judging whether the absolute value of the difference is greater than a preset difference threshold and determining whether the inside of the battery body has defects according to the judgment result.
Optionally, the third threshold comparing subunit is specifically configured to determine that no defect exists in the battery body when the absolute value of the difference is not greater than the difference threshold; and determining that the defect exists in the battery body under the condition that the absolute value of the difference is larger than the threshold value of the difference.
The modules in the defect identifying device can be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a processor independent of the signal processing device in a hardware form, or can be stored in a memory of the signal processing device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, there is provided a potentiometric sensor comprising a reference electrode and potentiometric signal processing means connected to each other, the potentiometric signal processing means comprising a memory and a processor, the memory storing a computer program, the processor when executing the computer program implementing the steps of:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body; and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
matching each measured voltage with an upper limit voltage threshold and a lower limit voltage threshold, and determining a matching result; and determining whether the inside of the battery body has defects according to the matching result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body; and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that the defect exists in the battery body.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating the mean square error of each measured voltage, and determining the mean square error voltage; comparing the mean square error voltage with a mean square error voltage threshold value to determine a comparison result; and determining whether the inside of the battery body has defects according to the comparison result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold; and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
if the absolute value of the difference is not greater than the threshold value of the difference, determining that no defect exists in the battery body; and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, performs the steps of:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body; and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In one embodiment, the computer program when executed by the processor further performs the steps of:
matching the measured voltages with an upper limit voltage threshold and a lower limit voltage threshold to determine a matching result; and determining whether the inside of the battery body has defects according to the matching result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body; and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that the defect exists in the battery body.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating the mean square error of each measured voltage, and determining the mean square error voltage; comparing the mean square error voltage with a mean square error voltage threshold value to determine a comparison result; and determining whether the inside of the battery body has defects according to the comparison result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold; and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the absolute value of the difference is not greater than the threshold value of the difference, determining that no defect exists in the battery body; and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body.
In one embodiment, a computer program product is provided, which computer program, when executed by a processor, performs the steps of:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time; the measured voltage is the corresponding voltage of the reference electrode and the measured working electrode in the battery body; and the potential signal processing device performs difference analysis according to each measured voltage and a preset voltage threshold range to determine whether the interior of the battery body has defects.
In one embodiment, the computer program when executed by the processor further performs the steps of:
matching each measured voltage with an upper limit voltage threshold and a lower limit voltage threshold, and determining a matching result; and determining whether the inside of the battery body has defects according to the matching result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body; and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that the defect exists in the battery body.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating the mean square error of each measured voltage, and determining the mean square error voltage; comparing the mean square error voltage with a mean square error voltage threshold value to determine a comparison result; and determining whether the inside of the battery body has defects according to the comparison result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold; and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
if the absolute value of the difference is not greater than the threshold value of the difference, determining that no defect exists in the battery body; and if the absolute value of the difference is larger than the threshold value of the difference, determining that the defect exists in the battery body.
It should be noted that the data referred to in the present application (including but not limited to data for analysis, stored data, presented data, etc.) are data authorized by the user or fully authorized by each party.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), Magnetic Random Access Memory (MRAM), Ferroelectric Random Access Memory (FRAM), Phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (11)
1. A defect identification method is applied to a battery, the battery comprises a battery body and a potential sensor, the potential sensor comprises a reference electrode and a potential signal processing device, the reference electrode is implanted in the battery body, the potential signal processing device is connected with the reference electrode and a positive electrode or a negative electrode of the battery, and the method comprises the following steps:
the potential signal processing device acquires each measurement voltage corresponding to the reference electrode within a preset time length; the measured voltage is the corresponding voltage of a reference electrode and a measured working electrode in the battery body;
and the potential signal processing device performs difference analysis according to the measured voltages and a preset voltage threshold range to determine whether defects exist in the battery body.
2. The method of claim 1, wherein the voltage threshold range comprises an upper voltage threshold and a lower voltage threshold, and the determining whether the defect exists in the battery body according to the difference analysis between each measured voltage and the preset voltage threshold range comprises:
matching each measured voltage with the upper limit voltage threshold and the lower limit voltage threshold to determine a matching result;
and determining whether the battery body has defects according to the matching result.
3. The method of claim 2, wherein determining whether a defect exists inside the battery body according to the matching result comprises:
if the measured voltages are smaller than the upper limit voltage threshold and larger than the lower limit voltage threshold, determining that no defect exists in the battery body;
and if at least one of the measured voltages is greater than the upper limit voltage threshold or less than the lower limit voltage threshold, determining that a defect exists in the battery body.
4. The method of claim 1, wherein the voltage threshold ranges comprise mean square error voltage thresholds, and wherein the step of performing a differential analysis based on each of the measured voltages and a predetermined voltage threshold range to determine whether a defect exists in the battery body comprises:
calculating the mean square error of each measured voltage, and determining the mean square error voltage;
comparing the mean square error voltage with the mean square error voltage threshold value to determine a comparison result;
and determining whether the inside of the battery body has defects according to the comparison result.
5. The method of claim 4, wherein the determining whether the defect exists in the battery body according to the comparison result comprises:
calculating the absolute value of the difference between the mean square error voltage and the mean square error voltage threshold;
and judging whether the absolute value of the difference value is larger than a preset difference value threshold value or not, and determining whether the inside of the battery body has defects or not according to a judgment result.
6. The method of claim 5, wherein the determining whether the defect exists in the battery body according to the determination result comprises:
if the absolute value of the difference is not larger than the threshold value of the difference, determining that no defect exists in the battery body;
and if the absolute value of the difference is larger than the threshold value of the difference, determining that the inside of the battery body has defects.
7. A defect identification apparatus, the apparatus comprising:
the voltage acquisition module is used for acquiring each measurement voltage corresponding to the reference electrode within a preset time length; the measured voltage is the corresponding voltage of a reference electrode and a measured working electrode in the battery body;
and the defect identification module is used for performing difference analysis according to the measured voltages and a preset voltage threshold range to determine whether defects exist in the battery body.
8. An electric potential sensor comprising a reference electrode and an electric potential signal processing means connected to each other, the electric potential signal processing means comprising a memory and a processor, the memory storing a computer program which when executed by the processor effects the steps of the method of any one of claims 1 to 6.
9. A battery comprising a battery body and the electric potential sensor of claim 8, wherein the reference electrode is implanted in the battery body and connected to the positive electrode or the negative electrode of the battery.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
11. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 6 when executed by a processor.
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