CN106248702A - In influence factor's detection method in a kind of lithium ion battery self discharge - Google Patents
In influence factor's detection method in a kind of lithium ion battery self discharge Download PDFInfo
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- CN106248702A CN106248702A CN201610812405.4A CN201610812405A CN106248702A CN 106248702 A CN106248702 A CN 106248702A CN 201610812405 A CN201610812405 A CN 201610812405A CN 106248702 A CN106248702 A CN 106248702A
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- lithium ion
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- self discharge
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
- G01N23/02—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material
- G01N23/04—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by transmitting the radiation through the material and forming images of the material
Abstract
The invention discloses a kind of lithium ion battery self discharge interior in influence factor's detection method, the method includes that first measuring system with X-ray tomography is obtained from the three-dimensional tomographic image of the underproof lithium ion battery parts that discharge, then image procossing is passed through, both positive and negative polarity pole plate is extracted from battery component tomographic map, lug, barrier film, the tomographic map of electrolyte, then the density of component on tomographic map is analyzed, shape, the physical parameters such as position, compared by the physical parameter of lithium ion battery satisfactory with self discharge in data base, and then find out inside lithium ion cell and affect the key factor of self discharge.The present invention is based on the digital X-ray tomography art towards material attenuation quotient, it is achieved that in real-time, the Non-Destructive Testing of influence factor in lithium ion battery self discharge, has important practical significance in self-discharge of battery detection field technical merit for promoting China.
Description
Technical field
The present invention relates to self-discharge of battery detection technique field, affecting in particularly relating to a kind of lithium ion battery self discharge
Factor detection method.
Background technology
Self discharge is to be caused by the intrinsic factor of battery, and is affected by extrinsic factor.Generally self-discharge of battery performance
Determined by the positive and negative electrode constituting battery, lug, barrier film and electrolyte property, and by manufacturing process and the shadow of production requirement
Ring.And self discharge size is not changeless in battery life, also with the degree of aging of battery, SOC and battery residing for
The factors such as the temperature of environment have relation, and severe discharge and recharge system and working condition also can constitute impact to the self discharge of battery.
With regard to the impact on self-discharge of battery of the intrinsic factor of battery, mainly include positive and negative electrode, lug, barrier film, electrolyte
Deng, and for different model and the battery of various processes, they are different to the influence degree of self-discharge of battery.Real at battery
In the production process on border, the battery serious to self discharge, it is to be appreciated that specifically which or several factor are to its self discharge shadow
The degree of sound is bigger, in order to find out the principal element affecting self-discharge of battery.
Owing to self discharge occurs at inside battery, existing measuring method can not be deep into inside battery and directly carry out it
Measure, be difficult to find out the main inherent influence factor of the serious battery of self discharge in a conventional way.Based on this, the present invention is special
In influence factor's detection method in a kind of lithium ion battery self discharge that profit proposes, in impact in lithium ion battery self discharge
The detection of factor, has important practical significance in self-discharge of battery detection field technical merit for promoting China.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, it is provided that in a kind of lithium ion battery self discharge affect because of
Element detection method.Measure system with X-ray tomography and be obtained from the three-dimension layer of the underproof lithium ion battery parts that discharge
Analysis image, extracts the tomographic map of both positive and negative polarity pole plate, lug, barrier film, electrolyte from battery component tomographic map, and then
Find out inside lithium ion cell and affect self discharge principal element, solve lithium ion battery self discharge influnecing factor and be difficult to reality
Time, a Non-Destructive Testing difficult problem.
For achieving the above object, the present invention is by the following technical solutions:
In influence factor's detection method in a kind of lithium ion battery self discharge, comprise the steps:
(1) measure system with X-ray tomography and be obtained from the three-dimensional tomographic map of the underproof lithium ion battery parts that discharge
Picture；
(2) by image procossing, from battery component tomographic map, both positive and negative polarity pole plate, lug, barrier film, electrolyte are extracted
Tomographic map；
(3) physical parameter of component on tomographic map is then analyzed, including density, shape, position；
(4) compared by the physical parameter of lithium ion battery satisfactory with self discharge in data base, and then find out lithium
The key factor of ion battery internal influence self discharge.
Further, described step (1) is derived from the three-dimensional tomographic map of the underproof lithium ion battery parts that discharge
Picture method particularly includes: utilize photon stream and the atomic interaction in lithium ion battery structure of the X-ray that x-ray source launches,
Photosignal in scanning process is made record continuously by photodetector, data collecting system by gather information conveyance to count
Calculation machine, is rebuild by computer picture, obtains the three-dimensional tomographic image of self discharge underproof lithium ion battery parts.
Further, in described step (2), image procossing includes background in tomographic map and separates, target scale becomes
Change, the Image semantic classification of sub-pix interpolation and the extraction of multi-mode target characteristic image and measurement.
Further, described step (3) specifically includes: to the geometry of battery each several part tomographic map obtained, color, sky
Between feature be analyzed extracting, and by related algorithm, target characteristic is carried out precision raising, it is simple to identification, and then is chromatographed
The physical parameter of component in image, including density, shape, position.
Further, in (4), the process of setting up of data base is: the morphologic method of applied mathematics, in conjunction with to production process
In battery component component and the analysis of impurity composition form, concentration, temperature and self discharge and associated batteries charge and discharge electrical
Can experimental result, system and study quantitatively come from various processes under the conditions of there are the various batteries zero of self-discharge characteristics
Parts chromatography image information, and then obtain the battery component chromatography configuration image of meso-scale in production process, this figure
Battery component and impurity thereof as being demonstrated by motion, heat and electrochemical reaction process chromatograph configuration and physics thereof
Chemical characteristic.As guide, set up in production process battery component and impurity thereof in time, the physical model of spatial variations
And mathematical model, design the battery component towards self discharge and chromatograph configuration credit analysis, the transformation rule of identification and algorithm,
Establishment has the morphological data storehouse of battery component many-valued chromatography configuration and performance characteristic.
Further, described tomography measurement system includes that x-ray source, lithium ion battery, photodetector, sample are swept
Retouch mechanical system and aid system, data collecting system.
Compared with prior art, the present invention has the effect that
The method uses chromatography structural imagesization to measure, and overcomes existing lithium ion battery self discharge influnecing factor detection method
Deficiency, such as: Chinese scholars uses ultramicroscope microcell, surface analysis art, X-ray diffraction art, infrared spectrum and little angle are swashed
The core material microscopic pattern of self discharge is analyzed by the methods such as light scattering with structure, but it has the destruction of sample preparation, sight
Examine narrow range, representative difference and bidimensional etc., it is impossible to being deep into inside battery directly measures it, is difficult to find out self discharge
The main inherent influence factor of serious battery.The method X-ray chromatography configuration image by lithium ion battery, discloses
The mechanism that positive and negative electrode pole plate, lug, barrier film and the electrolyte property etc. of lithium ion battery interact with its self discharge, analyzes
Density that battery chromatography image sets is divided, shape, the physical parameter such as position, with the relation between self-discharge of battery, solve lithium-ion electric
Pond self discharge influnecing factor is difficult in real time, a non-destructive prediction difficult problem.
Accompanying drawing explanation
Fig. 1 is battery longitudinal section tomographic map.
Fig. 2 is battery longitudinal section target tomographic map after pretreatment.
Fig. 3 is the GTG before the target image pretreatment of battery longitudinal section and pixel distribution.
Fig. 4 is the battery longitudinal section pretreated GTG of target image and pixel distribution.
Fig. 5 is that the battery after under a certain GTG interval extracting pretreated battery longitudinal section target image is vertical to be cut
Region feature image.
Fig. 6 is that the battery after under another GTG interval extracting pretreated battery longitudinal section target image is vertical to be cut
Region feature image.
Fig. 7 is that the battery after under another GTG interval extracting pretreated battery longitudinal section target image is vertical to be cut
Region feature image.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is purged, complete
Describe, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiment wholely.
The ferric phosphate lithium ion battery that the present embodiment selects, relatively big through detection self discharge, self-discharge rate has exceeded row
Industry standard.In the case of not destroying battery, based on X-ray chromatography configuration image it is detected, with find lithium from
Sub-inside battery affects the principal element of self discharge.Tomography is measured system and is included x-ray source, lithium ion battery, light electrical resistivity survey
Survey device, Sample Scan mechanical system and aid system, data collecting system.
In influence factor's detection method in a kind of lithium ion battery self discharge, comprise the steps:
(1) measure system with X-ray tomography and be obtained from the three-dimensional tomographic map of the underproof lithium ion battery parts that discharge
Picture.The present embodiment chooses the longitudinal section plane of battery ad-hoc location, carries out CT scan experiment, it is thus achieved that battery longitudinal section tomographic map
Picture, as shown in Figure 1.
(2) by image procossing, from battery component tomographic map, both positive and negative polarity pole plate, lug, barrier film, electrolysis are extracted
The tomographic map of liquid.The information that the present embodiment is useful in order to obtain inside battery, enters the longitudinal section tomographic map of tested battery
The pretreatment such as the segmentation of row image, scale conversion and sub-pix interpolation, it is thus achieved that its pretreated battery longitudinal section target tomographic map
Picture, shown in Fig. 2.
(3) physical parameter of component on tomographic map is then analyzed, including density, shape, position.Specifically, to acquisition
The geometry of battery each several part tomographic map, color, space characteristics be analyzed extracting, and by related algorithm to target characteristic
Carry out precision raising, it is simple to identify, and then obtain the physical parameter of component in tomographic map, including density, shape, position.
In the present embodiment, extracting battery longitudinal section tomographic map GTG before and after pretreatment and pixel distribution, Fig. 3 is pre-
GTG before treatment and pixel distribution, Fig. 4 is pretreated GTG and pixel distribution；Before pretreatment in comparison diagram 3, Fig. 4
After the GTG of target image and pixel map understand, target image information after pretreatment is at gray-scale distribution and pixel count
Strengthen in amount.According to the corresponding relation between grey decision-making and material density, i.e. grey decision-making the lowest tie substance density more
High, it is known that it is interval that pretreated tomographic map high-density matter is distributed in the broader gray scale of scope.
On the basis of pretreated target image, according to multiple random variables mutual information principle, according to different
GTG is interval, the target image of enhanced battery A is carried out image characteristics extraction, obtains its characteristic image such as Fig. 5 successively extremely
Shown in Fig. 7.
Wherein, in Fig. 5, the feature 1 of battery is mainly distributed on the right side of battery longitudinal section, also has a small amount of point in left side simultaneously
Cloth；In Fig. 6, the feature 2 of battery is mainly distributed on the left area of battery longitudinal section and battery right-hand part except the district of lug position
Territory；In Fig. 7, the feature 3 of battery is mainly distributed on the zone line of battery longitudinal section, and has and be distributed in left side edge on a small quantity.
(4) compared by the physical parameter of lithium ion battery satisfactory with self discharge in data base, and then look for
Go out inside lithium ion cell and affect the key factor of self discharge.The present embodiment is by the lithium ion qualified with self discharge in data base
Battery characteristics distribution compares, and in Fig. 6, the feature 2 of battery is mainly distributed it can be deduced that this kind of phenomenon is owing to pole plate occurs corruption
Erosion, positive and negative electrode material occurs dissolving to come off from polar board surface, so that the feature 2 of battery is mainly distributed on both sides.
Specifically, in described (4), the process of setting up of data base is: the morphologic method of applied mathematics, in conjunction with to production
During battery component component and the analysis of impurity composition form, concentration, temperature and self discharge and associated batteries charge and discharge
Electrical property experiment result, system and study quantitatively come from various processes under the conditions of there are the various electricity of self-discharge characteristics
Pond parts tomographic map information, and then obtain the battery component chromatography configuration image of meso-scale in production process,
This image appearance battery component in motion, heat and electrochemical reaction process and impurity chromatography configuration thereof and
Physicochemical characteristics.As guide, set up in production process battery component and impurity thereof in time, the physics of spatial variations
Model and mathematical model, design towards self discharge battery component chromatograph configuration credit analysis, identify transformation rule and
Algorithm, establishment has the morphological data storehouse of battery component many-valued chromatography configuration and performance characteristic.
In sum, by the analysis to battery A longitudinal section tomographic map, in conjunction with the qualified lithium of self discharge in data base from
Sub-battery chromatography image characteristic parameters, finds out the corrosion that main inside influence factor is pole plate that battery A self discharge is serious.
It should be noted that the announcement of book and elaboration according to the above description, those skilled in the art in the invention also may be used
So that above-mentioned embodiment is changed and revises.Therefore, the invention is not limited in disclosed and described above being embodied as
Mode, some equivalent modifications and change to the present invention should also be as in the scope of the claims of the present invention.Additionally, to the greatest extent
Pipe this specification employs some specific terms, but these terms are merely for convenience of description, the present invention is not constituted
Any restriction.
Claims (6)
1. in influence factor's detection method in a lithium ion battery self discharge, it is characterised in that comprise the steps:
(1) measure system with X-ray tomography and be obtained from the three-dimensional tomographic map of the underproof lithium ion battery parts that discharge
Picture；
(2) by image procossing, from battery component tomographic map, both positive and negative polarity pole plate, lug, barrier film, electrolyte are extracted
Tomographic map；
(3) physical parameter of component on tomographic map is then analyzed, including density, shape, position；
(4) compared by the physical parameter of lithium ion battery satisfactory with self discharge in data base, and then find out lithium
The key factor of ion battery internal influence self discharge.
In influence factor's detection method in a kind of lithium ion battery self discharge the most according to claim 1, it is characterised in that:
Described step (1) is derived from the three-dimensional tomographic image of the underproof lithium ion battery parts that discharge method particularly includes: utilize X
The photon stream of the X-ray that radiographic source is launched and the atomic interaction in lithium ion battery structure, photodetector is to scanned
Photosignal in journey makees record continuously, and the information conveyance of collection to computer, is passed through computer graphic by data collecting system
As rebuilding, obtain the three-dimensional tomographic image of self discharge underproof lithium ion battery parts.
In influence factor's detection method in a kind of lithium ion battery self discharge the most according to claim 1, it is characterised in that:
In described step (2) image procossing include background in tomographic map and separate, target scale conversion, the image of sub-pix interpolation
Pretreatment and the extraction of multi-mode target characteristic image and measurement.
In influence factor's detection method in a kind of lithium ion battery self discharge the most according to claim 1, it is characterised in that
Described step (3) specifically includes: be analyzed carrying to the geometry of battery each several part tomographic map obtained, color, space characteristics
Take, and by related algorithm, target characteristic is carried out precision raising, it is simple to identify, and then obtain the physical property of component in tomographic map
Parameter, including density, shape, position.
In influence factor's detection method in a kind of lithium ion battery self discharge the most according to claim 1, it is characterised in that:
In described step (4), the process of setting up of data base is: the morphologic method of applied mathematics, in conjunction with to the battery zero in production process
Parts component and the analysis of impurity composition form, concentration, temperature and self discharge thereof and associated batteries charge-discharge performance experimental result,
System and study quantitatively come from various processes under the conditions of there are the various battery component tomographic maps of self-discharge characteristics
As information, and then obtaining the battery component chromatography configuration image of meso-scale in production process, this image appearance exists
Battery component and impurity thereof in motion, heat and electrochemical reaction process chromatograph configuration and physicochemical characteristics thereof；
As guide, set up in production process battery component and impurity thereof in time, the physical model of spatial variations and mathematical modulo
Type, designs the battery component towards self discharge and chromatographs configuration credit analysis, the transformation rule of identification and algorithm, and establishment has
Battery component many-valued chromatography configuration and the morphological data storehouse of performance characteristic.
In influence factor's detection method in a kind of lithium ion battery self discharge the most according to claim 1, it is characterised in that:
Described tomography is measured system and is included x-ray source, lithium ion battery, photodetector, Sample Scan mechanical system and auxiliary
System, data collecting system.
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Cited By (7)
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| CN108008305A (en) * | 2017-10-31 | 2018-05-08 | 华南理工大学 | A kind of automobile-used lithium iron phosphate dynamic battery capacity attenuation detecting system |
| CN108387594A (en) * | 2018-02-09 | 2018-08-10 | 中国电力科学研究院有限公司 | A kind of method and system of non-destructive testing stack type lithium ion battery |
| CN109975345A (en) * | 2019-04-17 | 2019-07-05 | 合刃科技（深圳）有限公司 | Method for testing performance and detection system based on heat radiation |
| CN111458644A (en) * | 2020-05-12 | 2020-07-28 | 安徽优旦科技有限公司 | Discharge detection system of new energy battery |
| CN112285137A (en) * | 2020-10-16 | 2021-01-29 | 合肥国轩高科动力能源有限公司 | Lithium ion battery full life cycle lithium analysis distribution detection method |
| CN113222900A (en) * | 2021-04-16 | 2021-08-06 | 深圳市安仕新能源科技有限公司 | Pole lug polarity detection method and detection device, terminal equipment and storage medium |
| CN114578245A (en) * | 2022-05-06 | 2022-06-03 | 四川富临新能源科技有限公司 | Device and method for rapidly detecting self-discharge rate of lithium iron phosphate lithium ion battery |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108008305A (en) * | 2017-10-31 | 2018-05-08 | 华南理工大学 | A kind of automobile-used lithium iron phosphate dynamic battery capacity attenuation detecting system |
| CN108387594A (en) * | 2018-02-09 | 2018-08-10 | 中国电力科学研究院有限公司 | A kind of method and system of non-destructive testing stack type lithium ion battery |
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| CN111458644A (en) * | 2020-05-12 | 2020-07-28 | 安徽优旦科技有限公司 | Discharge detection system of new energy battery |
| CN112285137A (en) * | 2020-10-16 | 2021-01-29 | 合肥国轩高科动力能源有限公司 | Lithium ion battery full life cycle lithium analysis distribution detection method |
| CN113222900A (en) * | 2021-04-16 | 2021-08-06 | 深圳市安仕新能源科技有限公司 | Pole lug polarity detection method and detection device, terminal equipment and storage medium |
| CN114578245A (en) * | 2022-05-06 | 2022-06-03 | 四川富临新能源科技有限公司 | Device and method for rapidly detecting self-discharge rate of lithium iron phosphate lithium ion battery |
| CN114578245B (en) * | 2022-05-06 | 2022-07-08 | 四川富临新能源科技有限公司 | Device and method for rapidly detecting self-discharge rate of lithium iron phosphate lithium ion battery |
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