CN109031141A - A kind of prediction technique of lithium ion battery analysis lithium - Google Patents
A kind of prediction technique of lithium ion battery analysis lithium Download PDFInfo
- Publication number
- CN109031141A CN109031141A CN201810768985.0A CN201810768985A CN109031141A CN 109031141 A CN109031141 A CN 109031141A CN 201810768985 A CN201810768985 A CN 201810768985A CN 109031141 A CN109031141 A CN 109031141A
- Authority
- CN
- China
- Prior art keywords
- charge
- rate
- ion battery
- lithium ion
- temperature
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 58
- 229910001416 lithium ion Inorganic materials 0.000 title claims abstract description 58
- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 title claims abstract description 45
- 229910052744 lithium Inorganic materials 0.000 title claims abstract description 45
- 238000004458 analytical method Methods 0.000 title claims abstract description 34
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000012546 transfer Methods 0.000 claims abstract description 26
- 210000000952 spleen Anatomy 0.000 claims abstract description 8
- 210000002784 stomach Anatomy 0.000 claims abstract description 8
- 230000004913 activation Effects 0.000 claims description 10
- 238000012360 testing method Methods 0.000 description 10
- 230000005611 electricity Effects 0.000 description 6
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 4
- KMTRUDSVKNLOMY-UHFFFAOYSA-N Ethylene carbonate Chemical compound O=C1OCCO1 KMTRUDSVKNLOMY-UHFFFAOYSA-N 0.000 description 4
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- VAYTZRYEBVHVLE-UHFFFAOYSA-N 1,3-dioxol-2-one Chemical compound O=C1OC=CO1 VAYTZRYEBVHVLE-UHFFFAOYSA-N 0.000 description 2
- QGHDLJAZIIFENW-UHFFFAOYSA-N 4-[1,1,1,3,3,3-hexafluoro-2-(4-hydroxy-3-prop-2-enylphenyl)propan-2-yl]-2-prop-2-enylphenol Chemical group C1=C(CC=C)C(O)=CC=C1C(C(F)(F)F)(C(F)(F)F)C1=CC=C(O)C(CC=C)=C1 QGHDLJAZIIFENW-UHFFFAOYSA-N 0.000 description 2
- 229910001290 LiPF6 Inorganic materials 0.000 description 2
- 229910019142 PO4 Inorganic materials 0.000 description 2
- 239000000654 additive Substances 0.000 description 2
- 230000000996 additive effect Effects 0.000 description 2
- 239000010405 anode material Substances 0.000 description 2
- IEJIGPNLZYLLBP-UHFFFAOYSA-N dimethyl carbonate Chemical compound COC(=O)OC IEJIGPNLZYLLBP-UHFFFAOYSA-N 0.000 description 2
- 239000003792 electrolyte Substances 0.000 description 2
- 229910002804 graphite Inorganic materials 0.000 description 2
- 239000010439 graphite Substances 0.000 description 2
- 229910003002 lithium salt Inorganic materials 0.000 description 2
- 159000000002 lithium salts Chemical class 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 239000010452 phosphate Substances 0.000 description 2
- NBIIXXVUZAFLBC-UHFFFAOYSA-K phosphate Chemical compound [O-]P([O-])([O-])=O NBIIXXVUZAFLBC-UHFFFAOYSA-K 0.000 description 2
- 238000007747 plating Methods 0.000 description 2
- 238000013139 quantization Methods 0.000 description 2
- 239000002904 solvent Substances 0.000 description 2
- -1 acrylic ester Chemical class 0.000 description 1
- 229910021383 artificial graphite Inorganic materials 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 239000003575 carbonaceous material Substances 0.000 description 1
- BVKZGUZCCUSVTD-UHFFFAOYSA-N carbonic acid Chemical compound OC(O)=O BVKZGUZCCUSVTD-UHFFFAOYSA-N 0.000 description 1
- SIXOAUAWLZKQKX-UHFFFAOYSA-N carbonic acid;prop-1-ene Chemical compound CC=C.OC(O)=O SIXOAUAWLZKQKX-UHFFFAOYSA-N 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 210000001787 dendrite Anatomy 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000005087 graphitization Methods 0.000 description 1
- 238000004573 interface analysis Methods 0.000 description 1
- 239000007773 negative electrode material Substances 0.000 description 1
- 230000010287 polarization Effects 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
Landscapes
- Secondary Cells (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The present invention provides a kind of prediction techniques of lithium ion battery analysis lithium, comprising: S1) lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge are subjected to linear fit, obtain slope；S2 lithium ion battery charge transfer resistance and slope) are subjected to linear fit, simultaneously according to the relationship of charge transfer resistance and temperature T, the condition model of lithium ion battery charging current or rate of charge and temperature is obtained, the critical analysis lithium charging current or rate of charge of different temperatures are predicted according to condition model.Compared with prior art, the critical condition of present invention lithium ion battery analysis lithium at a temperature of Arrhenius formula can quantitatively prejudge varying environment in the way of modeling, does not have to dismantling battery core, time saving and energy saving, economizes on resources, realizes and quantify, accuracy is high.
Description
Technical field
The invention belongs to technical field of lithium ion more particularly to a kind of prediction techniques of lithium ion battery analysis lithium.
Background technique
Lithium ion battery lithium ion battery is as new green energy, in recent years by common concern, current business lithium from
Sub- cell negative electrode material is mainly based on graphitic carbon material, and when the charging of big multiplying power or low temperature are charged, inside battery polarization increases,
Cathode overpotential is larger, and the lithium ion in battery is precipitated on Carbon anode surface, seriously forms Li dendrite, pierces through diaphragm, causes just
Cathode short circuit, security performance are had a greatly reduced quality, and judge that the critical condition of battery core generation analysis lithium can design reasonable charging temperature in advance
Degree and multiplying power guarantee that lithium ion battery works normally.
Currently, judge lithium ion battery whether analyse lithium most common method be by battery different multiplying and at a temperature of fill
Then electricity disassembles battery, naked eyes judge that subjectivity provides analysis lithium state and severity.Such method can only qualitatively judge, and consume
Take a large amount of manpower and material resources, there are also certain security risks in battery dismantling process.
Summary of the invention
In view of this, the technical problem to be solved in the present invention is that providing a kind of prediction technique of lithium ion battery analysis lithium.
The present invention provides a kind of prediction techniques of lithium ion battery analysis lithium, comprising:
S1 lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge) are subjected to linear fit, obtained
To slope；
S2 lithium ion battery charge transfer resistance and slope) are subjected to linear fit, at the same according to charge transfer resistance with
The relationship of temperature T obtains the condition model of lithium ion battery charging current or rate of charge and temperature, is predicted according to condition model
The critical analysis lithium charging current or rate of charge of different temperatures.
Preferably, the step S1) in the obtained equation of linear fit be U=kX+b, U is current potential, and k is slope, and b is to cut
Away from X is charging current or rate of charge.
Preferably, the step S1) specifically:
At the same temperature, it is charged using different rate of charge or charging current to lithium ion battery, record anode electricity
Anode potential and charging current or rate of charge are carried out linear fit, obtain slope by position and charge transfer resistance.
Preferably, the temperature is 10 DEG C~60 DEG C.
Preferably, the rate of charge is 0.1~5C.
Preferably, the step S2) in lithium ion battery charge transfer resistance and slope be subjected to linear fit, the side of obtaining
Journey is that k=α * Rct+ β, α, β are constant, and Rct is charge transfer resistance.
Preferably, the charge transfer resistance and the relationship of temperature T meet equation:A, B is
Constant, Ea are activation energy, and R is mol gas constant, and T is absolute temperature, and K is rate constant.
Preferably, the condition model of the lithium ion battery charging current or rate of charge and temperature are as follows:
X be charging current or rate of charge,Ea is activation energy, and R is mole gas
Body constant, T are absolute temperature,A, c is fitting coefficient, and U current potential, b is Linear Quasi in step S1)
The intercept of conjunction.
The present invention provides a kind of prediction techniques of lithium ion battery analysis lithium, comprising: S1) by lithium ion battery charging process
Middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge carry out linear fit, obtain slope；S2 lithium ion battery charge) is shifted into electricity
Resistance carries out linear fit with slope, while according to the relationship of charge transfer resistance and temperature T, obtaining lithium ion battery charging current
Or the condition model of rate of charge and temperature, the critical analysis lithium charging current or charging times of different temperatures are predicted according to condition model
Rate.Compared with prior art, the present invention can quantitatively prejudge varying environment temperature by Arrhenius formula in the way of modeling
The critical condition for spending lower lithium ion battery analysis lithium, does not have to dismantling battery core, time saving and energy saving, economizes on resources, realizes quantization, accuracy
It is high.
Detailed description of the invention
Fig. 1 is the graph of relation of critical analysis lithium electric current and temperature in the embodiment of the present invention 1；
Fig. 2 is rate of charge when being 0.3C, the photo at battery core interface；
Fig. 3 is rate of charge when being 0.4C, the photo at battery core interface；
Fig. 4 is the graph of relation of critical analysis lithium electric current and temperature in the embodiment of the present invention 2；
When Fig. 5 is that rate of charge is 1C in the embodiment of the present invention 2, the photo at battery core interface；
When Fig. 6 is that rate of charge is 0.6C in the embodiment of the present invention 2, the photo at battery core interface.
Specific embodiment
Below in conjunction with the embodiment of the present invention, technical scheme in the embodiment of the invention is clearly and completely described,
Obviously, described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based in the present invention
Embodiment, every other embodiment obtained by those of ordinary skill in the art without making creative efforts, all
Belong to the scope of protection of the invention.
The present invention provides a kind of prediction techniques of lithium ion battery analysis lithium, comprising: S1) by lithium ion battery charging process
Middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge carry out linear fit, obtain slope；S2 lithium ion battery charge) is shifted into electricity
Resistance carries out linear fit with slope, while according to the relationship of charge transfer resistance and temperature T, obtaining lithium ion battery charging current
Or the condition model of rate of charge and temperature, the critical analysis lithium charging current or charging times of different temperatures are predicted according to condition model
Rate.
It is commercially available that the present invention, which is not particularly limited the source of all raw materials,.
Lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge are subjected to linear fit, obtained tiltedly
Rate；This is preferably a step specifically at the same temperature in the present invention, using different rate of charge or charging current to lithium
Ion battery charging, records anode potential and charge transfer resistance, and anode potential and charging current or rate of charge are carried out line
Property fitting；Being fitted obtained equation is preferably U=kX+b, and U is current potential, and k is slope, and b is intercept, and X is charging current or charging
Multiplying power；The temperature is preferably 10 DEG C~60 DEG C；The lithium ion battery is lithium ion battery well known to those skilled in the art
, special limitation is had no, preferably to plate lithium electrode as reference electrode in the present invention；When lithium ion battery changes locating temperature
When degree condition, 30~240min, more preferably 60~200min are preferably first stood, is further preferably 100~180min, most preferably
120~140min, then charged using different rate of charge；To ensure that each charge condition is the same, preferably first put
After electricity, then different rate of charge is used to charge；The electric discharge is preferably carried out using 1C electric current；The preferred electric discharge of electric discharge
To low cutoff voltage；The rate of charge is preferably 0.1~5C；The charging preferably charges to upper limit blanking voltage；Every time
After charging, preferably 1~10min of standing, more preferably 4~8min of standing further preferably stand 5~6min, record anode potential,
Then it after being discharged, then is charged next time；The electric discharge is preferably carried out using 1C electric current.
The charge transfer resistance of record and slope are subjected to linear fit, obtain slope and electric charge transfer electricity under corresponding temperature
The relationship of resistance, the equation are preferred are as follows: k=α * Rct+ β, α, β are constant, and Rct is charge transfer resistance.
Simultaneously according to the relationship of charge transfer resistance and temperature T, i.e. Arrhenius equation, establish charge transfer resistance and
The equation of temperature T is preferred are as follows:Also it can be written asA, B is normal
Number, Ea is activation energy, and R is mol gas constant, and T is absolute temperature, and K is rate constant.
According to the linear fit equation of anode potential and charging current or rate of charge, the line of charge transfer resistance and slope
The relationship of property fit equation and charge transfer resistance and temperature T, obtains lithium ion battery charging current or rate of charge and temperature
Condition model, preferably are as follows:
X be charging current or rate of charge,Ea is activation energy, and R is mole gas
Body constant, T are absolute temperature,A, c is fitting coefficient, and U current potential, b is Linear Quasi in step S1)
The intercept of conjunction；A is preferablyC is preferably equal with the β in slope linear fit equation with lithium ion battery charge transfer resistance.
It can be according to the critical analysis lithium charging current or rate of charge of obtained condition model prediction different temperatures.
Present invention lithium ion at a temperature of Arrhenius formula can quantitatively prejudge varying environment in the way of modeling
Battery analyses the critical condition of lithium, does not have to dismantling battery core, time saving and energy saving, economizes on resources, and realizes that quantization, accuracy are high.
In order to further illustrate the present invention, with reference to embodiments to a kind of lithium ion battery analysis lithium provided by the invention
Prediction technique is described in detail.
Reagent used in following embodiment is commercially available.
Embodiment 1
Battery uses ternary material: NCM523；Anode material: (gram volume plays 340mAh/g, degree of graphitization to graphite AK01
94%)；Electrolyte with the lithium hexafluoro phosphate (LiPF6) of concentration 1.0M be lithium salts, using vinylene carbonate as additive, with carbonic acid
The mixture of acrylic ester (PC), ethylene carbonate (EC) and dimethyl carbonate (DMC) is made for solvent；Lithium ion battery is measured to exist
Different multiplying charge when rated condition under anode to lithium current potential Ux。
Embodiment is specifically described as follows:
Battery core is embedded to copper wire in preparatory phase, handles after battery core activation copper wire plating lithium and reference electrode is made；Subsequent battery core
Merging high-low temperature chamber simultaneously accesses charge and discharge cabinet, completes to test by process, collects data.
Specific testing process is as follows:
1) adjustment environment temperature is T (T is the setting of experiment demand)；
2) 120min is stood；
3) nominal 1C current discharge is to low cutoff voltage；
4) 5min is stood；
5) upper limit blanking voltage is charged to；
6) 5min is stood.
Record same temperature, under different multiplying, the corresponding current potential U of anodex。
Lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current are subjected to linear fit, obtain fit equation U=
KI+b, U are current potential, and k is slope, and b is intercept, and I is electric current.
Test data and linear fit data are shown in Table 1.
1 test data of table and linear fit data
Linear fit is carried out according to the charge transfer resistance of test and slope k obtained above, it is oblique to obtain corresponding temperature
The linear fit equation of rate k and Rct: k=0.8474*Rct+8.9234.
Based on lithium ion battery principle, the equation of Rct Yu temperature T: LnRct=7120.1 (1/T) -21.059 are established.
Based on above-mentioned steps, the equation of critical charging current and temperature is established, obtains lithium ion battery different temperatures analysis lithium
Critical condition model of fit:
I0For charging current or rate of charge,Ea is activation energy, and R is mole gas
Body constant, T are absolute temperature,A, c is fitting coefficient, U current potential, b0It is linear in step S1)
The intercept of fitting, U0Lithium current potential, U are analysed for lithium ion battery0With b0For definite value.
It brings the data in table 1 into model of fit, it is as shown in Figure 1 to obtain matched curve.
According to model, predict that critical analysis lithium multiplying power is 0.3C when 0 DEG C (273.15K).
0 DEG C of temperature of control, successively charges under the conditions of under 0.3C and 0.4C multiplying power, and then dismantling is full by hand in safe house
Charge core and observing interface analysis lithium situation, judges critical analysis lithium multiplying power；When wherein Fig. 2 is rate of charge 0.3C, battery core interface
Photo, no analysis lithium phenomenon, Fig. 3 is rate of charge when being 0.4C, the photo at battery core interface, there is slight analysis lithium；By Fig. 2 and figure
0 DEG C of critical analysis lithium multiplying power of 3 deducibility this lithium ion battery is that 0.3C is consistent with model of fit prediction result.
Embodiment 2
Battery uses ternary material: NCM523；Anode material: (gram volume plays 350mAh/g, graphite to artificial graphite SF01
Change degree 96.5%)；Electrolyte with the lithium hexafluoro phosphate (LiPF6) of concentration 1.0M be lithium salts, using vinylene carbonate as additive,
It is made by solvent of the mixture of propene carbonate (PC), ethylene carbonate (EC) and dimethyl carbonate (DMC)；Measure lithium ion
Battery different multiplying charge when rated condition under anode to lithium current potential Ux。
Embodiment is specifically described as follows:
Battery core is embedded to copper wire in preparatory phase, handles after battery core activation copper wire plating lithium and reference electrode is made；Subsequent battery core
Merging high-low temperature chamber simultaneously accesses charge and discharge cabinet, completes to test by process, collects data.
Record same temperature, under different multiplying, the corresponding current potential U of anodex。
Lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current are subjected to linear fit, obtain fit equation U=
KI+b, U are current potential, and k is slope, and b is intercept, and I is electric current.
Test data and linear fit data are shown in Table 2.
2 test data of table and linear fit data
Linear fit is carried out according to the charge transfer resistance of test and slope k obtained above, it is oblique to obtain corresponding temperature
The linear fit equation of rate k and Rct: k=0.6987*Rct+7.4753.
Based on lithium ion battery principle, the equation of Rct Yu temperature T: LnRct=6440.6* (1/T) -18.678 are established.
Based on above-mentioned steps, the equation of critical charging current and temperature is established, obtains lithium ion battery different temperatures analysis lithium
Critical condition model of fit:
I0For charging current or rate of charge,Ea is activation energy, and R is mole gas
Body constant, T are absolute temperature,A, c is fitting coefficient, U current potential, b0It is linear in step S1)
The intercept of fitting, U0Lithium current potential, U are analysed for lithium ion battery0With b0For definite value.
It brings the data in table 2 into model of fit, it is as shown in Figure 4 to obtain matched curve.
Analysis lithium test at 10 DEG C of verifying, Fig. 5 is rate of charge when being 1C, the photo at battery core interface, there is slight analysis lithium；
Fig. 6 is rate of charge when being 0.6C, and battery core interface is good.Therefore critical analysis lithium multiplying power is between 0.6C and 1C, with fitting mould
Type prediction result is consistent.
Claims (8)
1. a kind of prediction technique of lithium ion battery analysis lithium characterized by comprising
S1 lithium ion battery charging process middle-jiao yang, function of the spleen and stomach electrode potential and charging current or rate of charge) are subjected to linear fit, obtained tiltedly
Rate；
S2 lithium ion battery charge transfer resistance and slope) are subjected to linear fit, while according to charge transfer resistance and temperature T
Relationship, obtain the condition model of lithium ion battery charging current or rate of charge and temperature, predicted according to condition model different
The critical analysis lithium charging current or rate of charge of temperature.
2. prediction technique according to claim 1, which is characterized in that the step S1) in the obtained equation of linear fit
It is current potential for U=kX+b, U, k is slope, and b is intercept, and X is charging current or rate of charge.
3. prediction technique according to claim 1, which is characterized in that the step S1) specifically:
At the same temperature, using different rate of charge or charging current to lithium ion battery charge, record anode potential with
Anode potential and charging current or rate of charge are carried out linear fit, obtain slope by charge transfer resistance.
4. prediction technique according to claim 3, which is characterized in that the temperature is 10 DEG C~60 DEG C.
5. prediction technique according to claim 3, which is characterized in that the rate of charge is 0.1~5C.
6. prediction technique according to claim 1, which is characterized in that the step S2) in by lithium ion battery charge turn
It moves resistance and slope carries out linear fit, obtaining equation as k=α * Rct+ β, α, β is constant, and Rct is charge transfer resistance.
7. prediction technique according to claim 1, which is characterized in that the relation character of the charge transfer resistance and temperature T
Close equation:A, B is constant, and Ea is activation energy, and R is mol gas constant, and T is absolute temperature, K
For rate constant.
8. prediction technique according to claim 1, which is characterized in that the lithium ion battery charging current or rate of charge
With the condition model of temperature are as follows:
X be charging current or rate of charge,Ea is activation energy, and R is that moles of gas is normal
Number, T is absolute temperature,A, c is fitting coefficient, and U current potential, b is linear fit in step S1)
Intercept.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810768985.0A CN109031141B (en) | 2018-07-13 | 2018-07-13 | Lithium ion battery lithium analysis prediction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810768985.0A CN109031141B (en) | 2018-07-13 | 2018-07-13 | Lithium ion battery lithium analysis prediction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109031141A true CN109031141A (en) | 2018-12-18 |
| CN109031141B CN109031141B (en) | 2021-06-04 |
Family
ID=64642099
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810768985.0A Active CN109031141B (en) | 2018-07-13 | 2018-07-13 | Lithium ion battery lithium analysis prediction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109031141B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109633454A (en) * | 2019-01-13 | 2019-04-16 | 浙江大学 | A method of realizing lithium ion battery equivalent temperature On-line Estimation |
| CN109872002A (en) * | 2019-03-04 | 2019-06-11 | 汤依伟 | Prediction technique, device and the electronic equipment of lithium metal deposition |
| CN109946622A (en) * | 2019-03-04 | 2019-06-28 | 汤依伟 | A kind of the lithium deposition prediction technique and device of lithium ion battery |
| CN110556601A (en) * | 2019-08-29 | 2019-12-10 | 龙能科技(宁夏)有限责任公司 | Low-temperature charging process for ternary power battery |
| CN111371143A (en) * | 2020-03-24 | 2020-07-03 | 北京经纬恒润科技有限公司 | Charging and discharging system |
| CN112345945A (en) * | 2020-10-27 | 2021-02-09 | 同济大学 | Battery temperature estimation method during charging |
| CN112394289A (en) * | 2020-10-27 | 2021-02-23 | 同济大学 | Lithium analysis detection method during charging of lithium ion battery |
| CN112710957A (en) * | 2020-12-26 | 2021-04-27 | 清华大学 | Method and device for detecting lithium precipitation during battery charging and computer equipment |
| CN113125974A (en) * | 2021-04-22 | 2021-07-16 | 远景动力技术(江苏)有限公司 | Method and device for detecting lithium separation of battery |
| CN113193249A (en) * | 2021-04-27 | 2021-07-30 | 广州小鹏汽车科技有限公司 | Method and device for determining lithium analysis threshold value and electric automobile |
| CN114221049A (en) * | 2021-11-19 | 2022-03-22 | 东莞维科电池有限公司 | Method for judging lithium precipitation of battery cell |
| WO2023070335A1 (en) * | 2021-10-26 | 2023-05-04 | 东莞新能源科技有限公司 | Method for detecting lithium plating of electrochemical apparatus, and system and electrochemical apparatus |
| CN116577680A (en) * | 2023-07-13 | 2023-08-11 | 无锡大派电子有限公司 | Lithium battery lithium precipitation detection method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006345634A (en) * | 2005-06-08 | 2006-12-21 | Fuji Heavy Ind Ltd | Control device for storage device |
| CN104471414A (en) * | 2012-05-24 | 2015-03-25 | 日立汽车系统株式会社 | Cell control device |
| CN105738815A (en) * | 2014-12-12 | 2016-07-06 | 国家电网公司 | Method for detecting state of health of lithium ion battery online |
| CN105870525A (en) * | 2016-06-20 | 2016-08-17 | 宁德新能源科技有限公司 | Battery charging method and device |
| CN106099230A (en) * | 2016-08-09 | 2016-11-09 | 清华大学 | A kind of lithium ion battery fast charge method preventing to analyse lithium |
| CN107367694A (en) * | 2017-07-31 | 2017-11-21 | 重庆金山医疗器械有限公司 | A kind of appraisal procedure and system of lithium battery service life |
-
2018
- 2018-07-13 CN CN201810768985.0A patent/CN109031141B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006345634A (en) * | 2005-06-08 | 2006-12-21 | Fuji Heavy Ind Ltd | Control device for storage device |
| CN104471414A (en) * | 2012-05-24 | 2015-03-25 | 日立汽车系统株式会社 | Cell control device |
| CN105738815A (en) * | 2014-12-12 | 2016-07-06 | 国家电网公司 | Method for detecting state of health of lithium ion battery online |
| CN105870525A (en) * | 2016-06-20 | 2016-08-17 | 宁德新能源科技有限公司 | Battery charging method and device |
| CN106099230A (en) * | 2016-08-09 | 2016-11-09 | 清华大学 | A kind of lithium ion battery fast charge method preventing to analyse lithium |
| CN107367694A (en) * | 2017-07-31 | 2017-11-21 | 重庆金山医疗器械有限公司 | A kind of appraisal procedure and system of lithium battery service life |
Non-Patent Citations (2)
| Title |
|---|
| 伊廷锋 等: ""线性关系在物理化学教学中的应用"", 《安徽工业大学学报（社会科学版）》 * |
| 吴正国 等: ""锂离子电池加速老化温度应力的滥用边界"", 《汽车安全与节能学报》 * |
Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109633454A (en) * | 2019-01-13 | 2019-04-16 | 浙江大学 | A method of realizing lithium ion battery equivalent temperature On-line Estimation |
| CN109633454B (en) * | 2019-01-13 | 2020-06-23 | 浙江大学 | Method for realizing on-line estimation of equivalent temperature of lithium ion battery |
| CN109872002A (en) * | 2019-03-04 | 2019-06-11 | 汤依伟 | Prediction technique, device and the electronic equipment of lithium metal deposition |
| CN109946622A (en) * | 2019-03-04 | 2019-06-28 | 汤依伟 | A kind of the lithium deposition prediction technique and device of lithium ion battery |
| CN110556601A (en) * | 2019-08-29 | 2019-12-10 | 龙能科技(宁夏)有限责任公司 | Low-temperature charging process for ternary power battery |
| CN111371143A (en) * | 2020-03-24 | 2020-07-03 | 北京经纬恒润科技有限公司 | Charging and discharging system |
| CN112345945B (en) * | 2020-10-27 | 2021-12-31 | 同济大学 | Battery temperature estimation method during charging |
| CN112394289A (en) * | 2020-10-27 | 2021-02-23 | 同济大学 | Lithium analysis detection method during charging of lithium ion battery |
| CN112394289B (en) * | 2020-10-27 | 2021-10-08 | 同济大学 | Lithium analysis detection method during charging of lithium ion battery |
| CN112345945A (en) * | 2020-10-27 | 2021-02-09 | 同济大学 | Battery temperature estimation method during charging |
| CN112710957A (en) * | 2020-12-26 | 2021-04-27 | 清华大学 | Method and device for detecting lithium precipitation during battery charging and computer equipment |
| CN112710957B (en) * | 2020-12-26 | 2022-09-09 | 清华大学 | Battery charging lithium-separation detection method and device and computer equipment |
| CN113125974A (en) * | 2021-04-22 | 2021-07-16 | 远景动力技术(江苏)有限公司 | Method and device for detecting lithium separation of battery |
| CN113193249A (en) * | 2021-04-27 | 2021-07-30 | 广州小鹏汽车科技有限公司 | Method and device for determining lithium analysis threshold value and electric automobile |
| WO2023070335A1 (en) * | 2021-10-26 | 2023-05-04 | 东莞新能源科技有限公司 | Method for detecting lithium plating of electrochemical apparatus, and system and electrochemical apparatus |
| CN114221049A (en) * | 2021-11-19 | 2022-03-22 | 东莞维科电池有限公司 | Method for judging lithium precipitation of battery cell |
| CN114221049B (en) * | 2021-11-19 | 2023-08-25 | 东莞维科电池有限公司 | Judgment method for lithium precipitation of battery cell |
| CN116577680A (en) * | 2023-07-13 | 2023-08-11 | 无锡大派电子有限公司 | Lithium battery lithium precipitation detection method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109031141B (en) | 2021-06-04 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109031141A (en) | A kind of prediction technique of lithium ion battery analysis lithium | |
| Yang et al. | A coupled electrochemical-thermal-mechanical degradation modelling approach for lifetime assessment of lithium-ion batteries | |
| Wu et al. | Low‐temperature reversible capacity loss and aging mechanism in lithium‐ion batteries for different discharge profiles | |
| CN112444753B (en) | Impedance test method for lithium analysis detection of lithium ion battery | |
| CN106855610B (en) | Lithium titanate battery health state estimation method | |
| CN111426724B (en) | Method for testing safety performance of electrode material | |
| CN110190325B (en) | Four-electrode lithium-sulfur battery, preparation method thereof and electrode electrochemical characteristic monitoring method | |
| CN108987808A (en) | A kind of high-voltage lithium ion batteries nonaqueous electrolytic solution and lithium ion battery | |
| CN111438077A (en) | Method for rapidly screening and detecting echelon utilization performance of retired ternary soft package battery | |
| CN108931736A (en) | A kind of determination method of lithium ion battery analysis lithium critical condition | |
| CN111366863B (en) | Lithium ion battery service life acceleration pre-judging method based on low-temperature circulation | |
| Zhang et al. | Deciphering the Thermal Failure Mechanism of Anode‐Free Lithium Metal Pouch Batteries | |
| CN112881925B (en) | Method for testing quick charge performance of anode material | |
| CN106450450A (en) | Battery electrolyte and preparation method therefor, and lithium battery | |
| CN102520363A (en) | Low-temperature performance evaluation method for lithium ion battery | |
| Wang et al. | Lithium plating induced volume expansion overshoot of lithium-ion batteries: Experimental analysis and modeling | |
| CN110515004A (en) | A kind of lithium ion battery charge and discharge circulation life calculation method | |
| CN114019385B (en) | Lithium analysis detection method based on single-frequency impedance test | |
| Qian et al. | Revealing the Impact of High Current Overcharge/Overdischarge on the Thermal Safety of Degraded Li‐Ion Batteries | |
| CN202454676U (en) | Lithium ion battery adaptive formation equipment | |
| Cui et al. | Safety boundary analysis for lithium-ion batteries via overcharge-to-thermal runaway | |
| CN110274815B (en) | Analysis method for mechanical strength of internal structure of lithium ion battery | |
| You et al. | Investigation of lithium-ion battery nonlinear degradation by experiments and model-based simulation | |
| CN112635831A (en) | Non-aqueous electrolyte and lithium ion battery | |
| CN108630943B (en) | Preparation method of high-capacity mesophase graphite negative electrode material |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220118 Address after: 215500 room 808, No. 1, Southeast Avenue, Changshu high tech Industrial Development Zone, Changshu, Suzhou, Jiangsu Patentee after: Jiangsu Zenergy Battery Technologies Co.,ltd Address before: 211100 Lantian Road 249, Airport Economic Development Zone, Jiangning District, Nanjing City, Jiangsu Province Patentee before: JIANGSU TAFEL NEW ENERGY TECHNOLOGY Co.,Ltd. Patentee before: DONGGUAN TAFEL NEW ENERGY TECHNOLOGY Co.,Ltd. Patentee before: SHENZHEN TAFEL NEW ENERGY TECHNOLOGY Co.,Ltd. |