Lithium ion battery charging and discharging process dynamic change characterization method based on harmonic excitation online impedance test

Abstract

The invention discloses a lithium ion battery charging and discharging process dynamic change characterization method based on a harmonic excitation online impedance test, and is suitable for dynamic monitoring of a lithium ion battery in an operation process. The lithium ion battery to be tested is connected with a charging and discharging device, and the charging and discharging device is used for carrying out constant-current charging and discharging on the battery; acquiring time sequence data of current and voltage, respectively performing time-frequency domain analysis on the acquired current and voltage data, and calculating to obtain impedance data in a specific frequency range; purifying the impedance data; time relaxation distribution peak information of different processes is extracted through relaxation time distribution; time relaxation distribution peak value information in the whole charging and discharging process is repeatedly collected, and the change trend of the peak value information along with the change of the charge state in the whole charging and discharging process is formed; and dynamic change monitoring is realized by observing changes. The method can be used for detecting the dynamic change of the lithium ion battery in the charging and discharging process, and has very high accuracy and timeliness.

Description

Technical Field

[0001] The present invention belongs to the research field of lithium-ion batteries, and in particular relates to a method for characterizing kinetic changes in the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing. Background Art

[0002] Lithium-ion batteries play an important role in modern society. They are almost everywhere, from smartphones to electric vehicles to large-scale energy storage systems. It is very necessary to study the dynamic changes of lithium-ion batteries during operation because it directly affects the performance, life and safety of batteries. Kinetic changes refer to key processes such as electrochemical reaction rate, ion diffusion and transmission inside the battery during charging and discharging. The kinetics of such electrochemical processes as a whole determine the reaction speed and energy utilization efficiency of the battery, and also affect the core performance of the battery, such as fast charging capability and stability for long-term use. If these processes do not match, it may lead to a decrease in battery capacity, or even overheating or safety hazards. In addition, in actual operation, batteries need to cope with complex working environments, such as frequent charging and discharging, high-rate use, and temperature fluctuations, which will change the kinetic behavior inside the battery, thereby affecting the battery's user experience and life. Therefore, in-depth research on the real-time kinetic changes of lithium-ion batteries under different working conditions can help optimize battery design and use strategies, such as controlling the temperature range, adjusting the charging and discharging strategy, and selecting suitable electrolytes and materials, thereby improving the overall performance of the battery, extending its service life, and ensuring its safety. This is particularly critical for high-demand fields such as electric vehicles. However, current research methods for lithium-ion battery kinetics cannot meet the requirements for real-time detection of the kinetic changes in lithium-ion batteries during operation. Summary of the invention

[0003] In order to monitor the dynamic change law of the battery operation process, the present invention proposes a method for characterizing the dynamic change of the lithium ion battery charging and discharging process based on harmonic excitation online impedance testing, which is used to study the online dynamic change of the lithium ion battery.

[0004] The present invention is achieved through the following technical solutions:

[0005] A method for characterizing kinetic changes in the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing, the method comprising:

[0006] S1: Connect the lithium-ion battery to be tested to the charging device, and use DC current to charge and discharge the battery at a constant current. Record the current intensity as I DC , and intermittently superimposing a detection signal on the DC current signal;

[0007] S2: collecting time series information of current and voltage during the application of the detection signal;

[0008] S3: The collected time series information of current and voltage is converted into the complex form in the frequency domain by the time-frequency domain transformation method. The complex form of impedance is obtained by dividing the complex number of voltage by the complex number of current, and then the real part and imaginary part of impedance are extracted respectively.

[0009]

[0010] Among them, U(t) is the time series data of voltage, is the frequency domain complex form of voltage, I(t) is the time series data of current, is the frequency domain complex form of the current, is the impedance data;

[0011] S4: Purify the acquired impedance data to extract impedance information within the target frequency range;

[0012] S5: Perform time relaxation distribution analysis on the purified impedance data, and obtain the impedance DRT peak information within the target frequency range through deconvolution calculation;

[0013] S6: repeatedly collect DRT peak information during the entire charge and discharge process to form a change trend of the peak information as the state of charge changes during the entire charge and discharge process;

[0014] S7: Analyze the change of online impedance DRT peak information of lithium-ion batteries at different charge states as the charge state changes, so as to obtain the dynamic change law of lithium-ion batteries during the charging and discharging process.

[0015] Further, in S1, the current intensity I DC 0.1C-2C, the detection interval is 2%-10% SOC, preferably, the current intensity I DC is 0.1C and the detection interval is 10% SOC.

[0016] Furthermore, in S1, the detection signal has a frequency range of 0.1-1 Hz and an amplitude of 10%I DC A square wave signal is applied for a total of 2 cycles, and the frequency range is preferably 0.1 Hz.

[0017] Furthermore, in S2, the sampling frequency f s At least 20 times the highest frequency to be detected, f s ≥20f max .

[0018] Furthermore, in S3, the time-frequency domain transformation method is one of fast Fourier transform, continuous wavelet transform or s transform.

[0019] Furthermore, in S4, the data purification is specifically as follows: converting the harmonic frequency data into a logarithmic format, then evenly selecting 10 frequency points in every 10 times the frequency range, and recording the real and imaginary parts of the impedance at the selected frequency, and then extracting the impedance data within the target frequency range by rounding up.

[0020] Furthermore, in S5, deconvolution operation is performed through DRT tools, and the DRT peak information includes time constant, peak height, peak area, normalized time constant, and normalized peak area.

[0021] Furthermore, in S7, the peak information includes DRT peak time constant, peak height, peak area, etc.

[0022] The beneficial effects of the present invention compared to the prior art are:

[0023] 1. Compared with traditional kinetic characterization methods such as cyclic voltammetry and constant current intermittent titration, the present invention starts from the perspective of online impedance and can simultaneously analyze the kinetic changes of multiple electrochemical processes. It has the advantages of rich information, high sensitivity and strong resolution.

[0024] 2. The present invention does not require a specific charging and discharging process, does not need to modify the battery structure, disassemble and destroy the battery, add additional sensors or use expensive instruments for testing, reduces the complexity of operation, avoids damage to the battery itself, reduces the detection cost, has significant cost advantages and operability, facilitates dynamic detection during the actual operation of the battery, and enhances the timeliness of dynamic detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 The present invention is a schematic diagram of the implementation process of the method.

[0026] Figure 2 This is the Nyquist diagram of the online impedance test under different charge states in the graphite / / lithium half-cell overdischarge lithium deposition experiment in Example 1 of the present invention.

[0027] Figure 3 This is a DRT diagram of the online impedance test results based on square wave excitation during the over-discharge lithium deposition process of the graphite / / lithium half-cell in Example 1 of the present invention.

[0028] Figure 4 This is a graph showing the variation of DRT peak height with SOC during the over-discharge lithium deposition process of a graphite / / lithium half-cell in Example 1 of the present invention based on square wave excitation.

[0029] Figure 5 This is a graph showing the change in SOC of the DRT normalized peak area during the over-discharge lithium deposition process of the graphite / / lithium half-cell in Example 1 of the present invention based on square wave excitation in the online impedance test.

[0030] Figure 6 This is a DRT diagram of the online impedance test based on square wave excitation during the high-rate discharge relaxation process of the graphite / / lithium half-cell of Example 2 of the present invention.

[0031] Figure 7 This is a graph showing the variation of the DRT time constant with the relaxation time during the high rate discharge relaxation process of the graphite / / lithium half-cell of Example 2 of the present invention in the online impedance test based on square wave excitation.

[0032] Figure 8 This is a graph showing the change in DRT normalized peak area versus relaxation time during high rate discharge relaxation of the graphite / / lithium half-cell of Example 2 of the present invention based on square wave excitation in an online impedance test. Specific implementation methods

[0034] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments, but is not limited thereto. Any modification or equivalent replacement of the technical solution of the present invention that does not depart from the spirit and scope of the technical solution of the present invention should be included in the protection scope of the present invention.

[0035] The main contents of the present invention include obtaining the impedance information of lithium-ion batteries during the charging and discharging process by applying an external square wave current signal excitation and combining the time-frequency domain analysis technology, obtaining the time relaxation distribution (DRT) peak information of the target frequency range by using the relaxation time distribution method after data comparison and purification, and characterizing the dynamic changes of lithium-ion batteries during the charging and discharging process by recording the DRT peak information change rules of the battery under different working environments and different charge states. Then, this method is used to characterize the changes in the dynamic process inside the battery when the lithium precipitation reaction occurs.

[0036] Embodiment 1:

[0037] Graphite / / Characterization of online kinetic changes during overdischarge of lithium half-cell. It includes the following steps:

[0038] S1: Connect the activated graphite / / lithium half-cell to the charging device and discharge it from a state of charge of 30% SOC at a current of 0.1C. The discharge process is the process of lithium insertion into the graphite layer, and the final discharge depth is -30% SOC. During the discharge process, the frequency is 0.1Hz and the amplitude is 10%I for every 1h of discharge. DC A square wave signal is applied for a total of 2 cycles.

[0039] S2: Collect the time series information of current and voltage, and obtain a total of 7 sets of square wave current and square wave voltage data.

[0040] S3: The collected current and voltage time series information is converted into complex form in the frequency domain through Fourier transform, and the frequency, current complex number and voltage complex number under each harmonic are extracted. The complex form of impedance is obtained by dividing the voltage complex number by the current complex number, and the real part and imaginary part of the impedance are extracted respectively. The Nyquist diagram of the line impedance under different charge states is shown in Figure 2 shown.

[0041] S4: Convert the harmonic frequency data into logarithmic format, then evenly select 10 frequency points in every 10 times frequency range, and record the real and imaginary parts of the impedance at the selected frequency, and then extract the impedance data within 0.1-500Hz by rounding up.

[0042] S5: Perform DRT analysis on the purified impedance data, and perform deconvolution calculations using DRT tools to obtain impedance time relaxation distribution diagrams in the range of 0.1-500Hz. The DRT diagrams of online impedance under different charge states are shown in the figure below: Figure 3 shown.

[0043] S6: Analyze the peak information of the online impedance DRT graph of graphite / / lithium single cells at different charge states. The peak height change and normalized peak area graph are as follows: Figure 4 , Figure 5 As shown in the figure, it can be seen that Peak 2, that is, the charge transfer reaction of the graphite electrode, turns after -20% SOC, representing the starting point of the growth of lithium dendrites.

[0044] Embodiment 2:

[0045] In-line kinetic characterization of graphite / / lithium half-cell during high-rate discharge relaxation. The following steps are involved:

[0046] S1: Connect the graphite / / lithium half-cell to the charging and discharging device, fully charge it at a rate of 0.1C, and then discharge it at a constant current of 3C for 10 minutes. Apply a square wave voltage signal with a frequency of 1Hz and an amplitude of 25mV online at 3, 5, 10, 20, 50, 80, and 120 minutes after the discharge, for a total of 2 cycles.

[0047] S2: Collect the time series information of current and voltage, and obtain a total of 7 sets of square wave current and square wave voltage data.

[0048] S3: Decompose the collected square wave time series information of current and voltage into a series of harmonic components of different frequencies in the frequency domain through Fourier transform, and extract the voltage harmonic components and current harmonic components at different frequencies. Divide the voltage harmonic components by the current harmonic components at the same frequency to obtain the impedance at each frequency, and extract the real and imaginary parts of the impedance respectively.

[0049] S4: Convert the harmonic frequency data into logarithmic format, then evenly select 10 frequency points in every 10 times frequency range, and record the real and imaginary parts of the impedance at the selected frequency, and then extract the impedance data within 1-500Hz by rounding up.

[0050] S5: Perform DRT analysis on the purified impedance data, and use DRT tools to perform relaxation time distribution analysis to obtain the impedance time relaxation distribution diagram in the range of 1-500Hz. The DRT diagram of online impedance at different relaxation times is as follows: Figure 6 shown.

[0051] S6: Analyze the peak information of the online impedance DRT graph of graphite / / lithium single cells at different charge states. The time constant and normalized peak area change graph are as follows: Figure 7 , Figure 8 As shown. Peaks a and b represent the SEI film impedance and graphite electrode charge transfer impedance respectively. Figure 7 It can be seen that the time constants of peaks a, b, and c remain basically stable. Figure 8 It shows that peaks a, b, and c grow rapidly before 20 minutes and tend to be flat after 20 minutes, indicating that the dissolution or re-intercalation of lithium dendrites in the graphite / / lithium half-cell after 3C discharge mainly occurs within 20 minutes after the end of discharge.

Claims

1. A method for characterizing the dynamic changes of lithium-ion battery charging and discharging process based on harmonic excitation online impedance testing, characterized in that: The method is: S1: Connect the lithium-ion battery to be tested to the charging device, and use DC current to charge and discharge the battery at a constant current. Record the current intensity as I DC , and intermittently superimposing a detection signal on the DC current signal; S2: collecting time series information of current and voltage during the application of the detection signal; S3: The collected time series information of current and voltage is converted into the complex form in the frequency domain by the time-frequency domain transformation method. The complex form of impedance is obtained by dividing the complex number of voltage by the complex number of current, and then the real part and imaginary part of impedance are extracted respectively. Among them, U(t) is the time series data of voltage, is the frequency domain complex form of voltage, I(t) is the time series data of current, is the frequency domain complex form of the current, is the impedance data; S4: Purify the acquired impedance data to extract impedance information within the target frequency range; S5: Perform time relaxation distribution analysis on the purified impedance data, and obtain the impedance DRT peak information within the target frequency range through deconvolution calculation; S6: repeatedly collect DRT peak information during the entire charge and discharge process to form a change trend of the peak information as the state of charge changes during the entire charge and discharge process; S7: Analyze the change of online impedance DRT peak information of lithium-ion batteries at different charge states as the charge state changes, so as to obtain the dynamic change law of lithium-ion batteries during the charging and discharging process.

2. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1 is characterized in that: In S1, the current intensity I DC It is 0.1C-2C, and the detection interval is 2%-10% SOC.

3. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1 is characterized in that: In S1, the detection signal has a frequency range of 0.1-1 Hz and an amplitude of 10%I DC A square wave signal is applied for 2 cycles in total, and the frequency range is preferably 0.1 Hz.

4. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1 is characterized in that: In S2, the sampling frequency f s At least 20 times the highest frequency to be detected, f s ≥20f max .

5. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1, characterized in that: In S3, the time-frequency domain transformation method is one of fast Fourier transform, continuous wavelet transform or s transform.

6. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1, characterized in that: In S4, the data purification is specifically as follows: converting the harmonic frequency data into a logarithmic format, then evenly selecting 10 frequency points in every 10 times frequency range, and recording the real and imaginary parts of the impedance at the selected frequency, and then extracting the impedance data within the target frequency range by rounding up.

7. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1 is characterized in that: In S5, deconvolution operation is performed through DRT tools. The DRT peak information includes time constant, peak height, peak area, normalized time constant, and normalized peak area.

8. The method for characterizing the dynamic changes of the charging and discharging process of a lithium-ion battery based on harmonic excitation online impedance testing according to claim 1, characterized in that: In S7, the peak information includes DRT peak time constant, peak height, peak area, etc.

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