Lithium ion battery lithium precipitation detection method and system based on pressure characteristic parameters

Abstract

The invention discloses a lithium ion battery lithium precipitation detection method and system based on pressure characteristic parameters, and the method comprises the steps: carrying out the charging of a battery at different rates to a preset state of charge, carrying out the two-step testing of constant current / dynamic working condition-small current discharging, and recording a pressure curve and a pressure variation in the charging and discharging process of the battery; a lithium de-intercalation reference interpolation function is defined, and pressure changes corresponding to lithium de-intercalation, lithium deposition / stripping and thermal expansion are de-coupled in combination with a thermal expansion source; extracting a pressure characteristic parameter RLSF reflecting the lithium stripping amount; determining a lithium precipitation threshold value by using fuzzy c-means clustering; and judging the lithium precipitation state according to the comparison between the RLSF and a threshold value. According to the invention, rapid detection of lithium precipitation of the lithium ion battery can be realized, and the lithium precipitation boundary current of the battery at different temperatures can be obtained.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of lithium-ion power battery fault diagnosis, and particularly relates to a lithium precipitation detection method and system for lithium-ion batteries based on pressure characteristic parameters. BACKGROUND

[0002] In recent years, lithium-ion batteries are considered as an effective way to reduce environmental pollution and energy consumption. However, low-temperature charging or high-rate charging of the battery can increase the risk of lithium precipitation of the battery, and also cause accelerated capacity degradation of the battery. Lithium dendrites formed by lithium metal generated during the battery cycle process can even cause internal short circuit due to the lithium dendrites piercing the separator, which can greatly affect the cycle life and safety state of the battery. In-situ rapid detection of lithium precipitation of lithium-ion batteries is one of the key technologies for safe and efficient operation of lithium-ion batteries. How to realize rapid detection of lithium precipitation of lithium-ion batteries is a very important technical problem.

[0003] With the gradual increase of the capacity and size of power batteries, the sensitivity of the existing lithium precipitation detection methods based on impedance and voltage signals gradually decreases. In addition, the evolution of the lithium precipitation boundary and the quantitative evaluation of the lithium precipitation amount during the aging process of lithium-ion batteries still pose great challenges to rapid detection and evaluation of lithium precipitation. There is a lack of research on in-situ lithium precipitation detection technology of large-capacity lithium iron phosphate batteries under complex working conditions, especially the research on in-situ lithium precipitation diagnosis using expansion force signals to extract features. SUMMARY

[0004] In view of the deficiencies in the prior art, the application provides a lithium precipitation detection method for lithium-ion batteries based on pressure characteristic parameters, which comprises the following steps: charging the battery at different rates to a preset state of charge, and then performing two-step testing of constant current / dynamic working condition-small current discharge, recording the pressure curve and pressure change amount of the battery during charging and discharging; defining a deintercalated lithium reference interpolation function, and decoupling the pressure changes corresponding to deintercalated lithium, lithium deposition / stripping and thermal expansion based on the thermal expansion principle; extracting a pressure characteristic parameter RLSF reflecting the amount of lithium stripping; determining a lithium precipitation threshold value by using fuzzy c-means clustering; determining the lithium precipitation state according to the comparison between RLSF and the threshold value.

[0005] Further, the different rates of charging are 1 / 5C-1.5C, and the preset state of charge is 60%-99% SOC.

[0006] Further, the pressure calculation formula corresponding to thermal expansion is: ; wherein is the thermal expansion coefficient of the battery, and is 0.054 KN / ℃; is the temperature change of the battery during the charging and discharging process.

[0007] Further, the calculation formula of the pressure characteristic parameter RLSF is: ; wherein, is the current lithium stripping pressure at the current rate; is the lithium stripping pressure at the 0.25C rate; is the total expansion force change of the battery when charging at the current rate; is the total expansion force change of the battery when charging at the 0.25C rate.

[0008] Further, the determination of the lithium precipitation threshold value by the fuzzy c-means clustering specifically includes: clustering the battery pressure characteristic parameters into lithium precipitation clusters and non-lithium precipitation clusters by the fuzzy c-means clustering method, taking the RLSF corresponding to the minimum charging rate of the lithium precipitation cluster as the upper limit of the threshold value, taking the RLSF corresponding to the maximum charging rate of the non-lithium precipitation cluster as the lower limit of the threshold value, and taking the average value of the upper and lower limits as the lithium precipitation threshold value.

[0009] Further, the determination of the lithium precipitation state according to the comparison between RLSF and the threshold value specifically includes: when charging to the SOC range, if RLSF exceeds the threshold value, it is determined that the battery precipitates lithium; otherwise, it is determined that the battery does not precipitate lithium.

[0010] Further, in the two-step test of the constant current / dynamic working condition-small current discharging, the constant current discharging current is 0.05C-0.5C, and the dynamic working condition discharging follows a preset current curve.

[0011] Further, the deintercalation lithium reference interpolation function takes the pressure curve at the 0.25C charging rate as the reference, and defines the reference interpolation function as: ; wherein, is the SOC or DoD of the battery, is the pressure change caused by the deintercalation lithium reaction of the battery at the SOC value.

[0012] Further, the method further includes lithium precipitation detection at different temperatures, compensating the influence of temperature on pressure by the thermal expansion coefficient, and determining the lithium precipitation boundary current at each temperature.

[0013] In another aspect, the present application also provides a lithium ion battery lithium precipitation detection system, which comprises: a charging and discharging test module for performing different rate charging and two-step discharging tests; a pressure acquisition module for recording the pressure curve during the charging and discharging process; A data processing module for pressure decoupling, RLSF calculation and fuzzy c-means clustering; A lithium precipitation determination module for determining the lithium precipitation state according to a threshold value; The system uses the method of any one of claims 1-9 for lithium precipitation detection.

[0014] The present application has the following technical effects: 1. High sensitivity: using pressure signal decoupling technology, separating the pressure characteristics related to lithium precipitation, overcoming the limitations of voltage and impedance signals.

[0015] 2. Quantitative evaluation: through RLSF parameters and threshold values, quantitative representation of lithium precipitation amount and accurate determination of lithium precipitation boundary current are realized.

[0016] 3. Strong adaptability: suitable for lithium precipitation detection at different temperatures (compensated by thermal expansion coefficient), different rates (1 / 5C-1.5C) and different working conditions (constant current / dynamic).

[0017] 4. Fast detection: two-step discharge test process can complete lithium precipitation diagnosis in a short time, meeting the needs of engineering applications. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is the lithium ion battery lithium precipitation detection flowchart based on the pressure characteristic parameters of the present application; Figure 2 is the pressure decoupling result of the discharge process of the present application; Figure 3 is the lithium ion battery lithium precipitation detection result based on the pressure characteristic parameters of the present application. DETAILED DESCRIPTION

[0019] The present application will be described in detail below with reference to the accompanying drawings.

[0020] Example 1: The method embodiment of the present application specifically includes the following steps: Step one: perform a charging experiment at different rates on the battery to make the battery reach a preset state of charge, perform a two-step discharge test of constant current / dynamic working condition-small current discharge on the battery, and record the pressure curve and pressure change of the battery during charging and discharging; Step two: define a deintercalation lithium reference interpolation function, and decouple the corresponding pressure changes of battery deintercalation lithium, lithium deposition (peeling), and thermal expansion in combination with thermal expansion theory; Step three: define a pressure characteristic parameter reflecting the amount of lithium peeling of the battery, and extract the pressure characteristic parameter according to the pressure decoupling result; Step four: using fuzzy c-means clustering method to cluster the battery pressure characteristic parameters into "lithium precipitation cluster" and "non-lithium precipitation cluster", setting the pressure characteristic parameter corresponding to the minimum charging rate in the "lithium precipitation cluster" as the maximum value of the lithium precipitation pressure characteristic parameter threshold range, and setting the pressure characteristic parameter corresponding to the maximum charging rate in the "non-lithium precipitation cluster" as the minimum value of the lithium precipitation pressure characteristic parameter threshold range. The average value of the maximum and minimum values of the pressure characteristic parameter threshold range is determined as the pressure characteristic parameter threshold value of the battery without lithium precipitation.

[0021] Step five: determining the lithium precipitation condition of the battery in the charging current charging process according to the battery pressure characteristic parameter threshold value: If the battery pressure characteristic parameter exceeds the threshold value when the charging current is charged to a certain state of charge range, it is determined that the battery has lithium precipitation at the charging rate; If the battery pressure characteristic parameter does not exceed the threshold value when the charging current is charged to a certain state of charge range, it is determined that the battery does not have lithium precipitation at the charging rate; Example 2: Three batteries were used to verify the correctness of the application at different temperatures and different rates. The experimental equipment used: three clamping plate constant displacement devices, Fujian Xingyun charge and discharge test equipment, Bell high and low temperature box BTT-544C, Jinke multi-channel temperature acquisition equipment. The detailed detection process is shown in the figure. This embodiment does not limit the application. Figure 1

[0022] Step one, charging experiment of the battery at different rates to make the battery reach a preset state of charge, recording the pressure curve and pressure change of the battery during charging and discharging.

[0023] The preset current is determined by the charging rate of the battery, and the charging rate can be any value in the range of 1 / 5C-1.5C. The preset state of charge is 60%-99% SOC (State of Charge, SOC). Preferably, the preset state of charge is 95% SOC.

[0024] For example, the battery can be charged at a current of 1C to make the battery reach 95% SOC (i.e. state of charge).

[0025] Step two, define the deintercalation lithium reference interpolation function, and decouple the corresponding pressure change of the battery deintercalation, lithium deposition (peeling), thermal expansion.

[0026] For example, taking the pressure curve corresponding to 0.25C as the reference, the reference interpolation function is defined as For the SOC or DoD (Depth of Discharge) of the battery, ​The pressure change caused by the battery's lithium extraction reaction at a specific SOC value. Based on this, the change curves of each charging rate during the charging and discharging process can be calculated, and the calculation method is as follows: ; The battery thermal expansion force is calculated by the battery's thermal expansion coefficient and temperature change, and the calculation method is as follows: ; Wherein is the thermal expansion coefficient of the battery, is the temperature change of the battery during charging and discharging. The thermal expansion coefficient of the experimental sample is tested at 100% SOC, and the value is about 0.054 KN / ℃. Therefore, the pressure during the lithium deposition or lithium stripping process during the charging and discharging process can be calculated by the following formula: ; ; The decoupling of the pressure of each chemical reaction in the battery charging and discharging process can be realized by the above steps, and the decoupling result is shown in Figure 2 .

[0027] Step three, define the pressure characteristic parameter reflecting the amount of lithium stripping of the battery, and extract the pressure characteristic parameter according to the pressure decoupling result.

[0028] When lithium deposition occurs in the battery, the internal active material particle structure expands, causing the external pressure of the battery to rapidly increase, and after lithium stripping, the active particles rapidly shrink, causing the external pressure of the battery to rapidly decrease. However, the amount of pressure change or the rate of change of the battery is not only caused by lithium deposition, but also affected by temperature, gas production, side reactions, etc. At the same time, the original value of the pressure is affected by the battery specifications, initial pre-warning force, capacity, etc., and its change range is large. Therefore, in order to better reflect the pressure of lithium stripping of the battery and its proportion in the abnormal increase of the battery pressure, the present application introduces a new pressure characteristic parameter RLSF (Ratio of expansion force of lithium stripping, RLSF ), defined as: the ratio of the pressure difference of lithium stripping reaction at the current rate and the reference rate to the pressure difference during charging, as shown in the following formula: ; The physical meaning of this feature can be explained as: the proportion of the pressure change of lithium stripping reaction in the abnormal pressure increase of the battery. The extracted pressure characteristic parameters are shown in Table 1.

[0029] Table 1 Pressure characteristic parameters under two discharge conditions RLSF and clustering results ​;

[0030] Step four: using fuzzy c-means clustering method to cluster the battery pressure characteristic parameters into "lithium precipitation cluster" (marked as "Y") and "non-lithium precipitation cluster" (marked as "N"), setting the pressure characteristic parameter corresponding to the minimum charging rate in the "lithium precipitation cluster" as the maximum value of the lithium precipitation pressure characteristic parameter threshold range, and setting the pressure characteristic parameter corresponding to the maximum charging rate in the "non-lithium precipitation cluster" as the minimum value of the lithium precipitation pressure characteristic parameter threshold range. The average value of the maximum and minimum values of the pressure characteristic parameter threshold range is determined as the pressure characteristic parameter threshold value when the battery does not precipitate lithium.

[0031] As shown in Table 1, in the two discharge conditions, the clustering results of 0.25C and 0.5C are all attributed to the non-lithium precipitation cluster, and the remaining charging rates are attributed to the lithium precipitation cluster. Therefore, it can be determined that the lithium precipitation critical current of the battery in the environment is between 0.5C and 0.75C, and it is inferred that the lithium precipitation critical value of parameter RLSF in the constant current discharge condition is between 66.6% and 85.8%, and the lithium precipitation critical value of parameter RLSF in the FUDS discharge condition is between 58.8% and 89.7%. In order to improve the accuracy and reduce the false positive rate of lithium precipitation detection, the average value of the maximum value 66.6% of the lower limit and the minimum value 85.8% of the upper limit of the critical range of parameter RLSF is selected as the threshold value of parameter RLSF .

[0032] Step five, according to the battery pressure characteristic parameter threshold, determine the lithium precipitation situation of the battery in the charging current charging process: if the battery pressure characteristic parameter exceeds the threshold value when the charging current is charged to a certain state of charge range, it is determined that the battery exists lithium precipitation at the charging rate; if the battery pressure characteristic parameter does not exceed the threshold value when the charging current is charged to a certain state of charge range, it is determined that the battery does not exist lithium precipitation at the charging rate.

[0033] Specifically, the battery can be charged by a current with a charging rate of 1.25C to make the battery reach 95% SOC, and then discharged by a current with a charging rate of 0.05C. The pressure of each part is obtained by decoupling the charging and discharging process, and the pressure characteristic parameter RLSF value is 93.1%, which exceeds the set pressure characteristic parameter threshold value 76.2%, indicating that the battery precipitates lithium when charged at 1.25C.

[0034] Further, in the constant current discharge condition, the pressure characteristic parameter RLSFAll exceed the threshold value, which indicates that the battery occurs lithium precipitation when the battery is charged at the four rates. RLSF All exceed the threshold value, which indicates that the battery occurs lithium precipitation when the battery is charged at the four rates. The detection results are shown in Figure 3

[0035] In summary, the present application creatively realizes the decoupling of the chemical reaction pressure in the battery charging and discharging process by defining the lithium deintercalation reference interpolation function, defines the pressure characteristic parameter that can reflect the reversible lithium precipitation degree of the battery, determines the threshold value of the lithium precipitation pressure characteristic parameter of the battery by clustering the characteristic parameters, and realizes the accurate identification of the battery lithium precipitation.

[0036] The above description is only the preferred embodiment of the present application, but the protection scope of the present application is not limited to this. Any skilled person in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims. The information disclosed in the background section of the present application is only intended to deepen the understanding of the overall background technology of the present application, and should not be regarded as acknowledging or implying in any form that the information constitutes the prior art known to those skilled in the art.​

Claims

1. A method for detecting lithium precipitation of a lithium ion battery based on a pressure characteristic parameter, characterized in that, The method comprises: Different rate charging is performed on the battery to a preset state of charge, and then two-step test of constant current / dynamic condition-small current discharge is performed, and the pressure curve and pressure change amount during the charging and discharging of the battery are recorded; A lithium extraction reference interpolation function is defined, and the pressure changes corresponding to lithium extraction, lithium deposition / peeling and thermal expansion are decoupled based on the thermal expansion principle; A pressure characteristic parameter RLSF reflecting the amount of lithium peeling is extracted; The lithium extraction threshold is determined by fuzzy c-means clustering; The lithium extraction state is determined according to the comparison between RLSF and the threshold.

2. The method of claim 1, wherein, The different rate charging is 1 / 5C-1.5C, and the preset state of charge is 60%-99% SOC.

3. The method of claim 1, wherein, The pressure calculation formula corresponding to thermal expansion is: ； wherein is the thermal expansion coefficient of the battery, which is 0.054 KN / ℃; is the temperature change of the battery during charging and discharging.

4. The method of claim 1, wherein, The calculation formula of the pressure characteristic parameter RLSF is: ； wherein, is the current rate lithium stripping pressure; is the 0.25C rate lithium stripping pressure; is the total cell swelling force change at current rate charge; is the total cell swelling force change at 0.25C rate charge.

5. The method of claim 1, wherein, The lithium extraction threshold is determined by fuzzy c-means clustering, specifically including: the battery pressure characteristic parameters are clustered into lithium extraction clusters and non-lithium extraction clusters by fuzzy c-means clustering method, the RLSF corresponding to the minimum charging rate of the lithium extraction cluster is taken as the upper limit of the threshold, the RLSF corresponding to the maximum charging rate of the non-lithium extraction cluster is taken as the lower limit of the threshold, and the average value of the upper and lower limits is taken as the lithium extraction threshold.

6. The method of claim 1, wherein, The lithium extraction state is determined according to the comparison between RLSF and the threshold, specifically including: when charging to the SOC range, if RLSF exceeds the threshold, it is determined that the battery extracts lithium; otherwise, it does not extract lithium.

7. The method of claim 1, wherein, In the two-step test of constant current / dynamic condition-small current discharge, the constant current discharge current is 0.05C-0.5C, and the dynamic condition discharge follows a preset current curve.

8. The method of claim 1, wherein, The lithium extraction reference interpolation function takes the pressure curve at a charging rate of 0.25C as a reference to define a reference interpolation function: ； wherein, is the SOC or DoD of the battery, is the change in pressure caused by the battery's delithiation reaction at the SOC value.

9. The method of claim 1, wherein, The method further comprises lithium extraction detection at different temperatures, compensation of the influence of temperature on pressure by a thermal expansion coefficient, and determination of the lithium extraction boundary current at each temperature.

10. A lithium ion battery lithium plating detection system, characterized in that, The system comprises: A charging and discharging test module for performing different rate charging and two-step discharge test; A pressure acquisition module for recording the pressure curve during the charging and discharging process; A data processing module for pressure decoupling, RLSF calculation and fuzzy c-means clustering; A lithium extraction determination module for determining the lithium extraction state according to the threshold; The system adopts the method of any one of claims 1-9 for lithium extraction detection.

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