A lithium battery detection device and method

Abstract

The application relates to the technical field of lithium battery detection, in particular to a lithium battery detection device and method, which comprises the following steps: acquiring voltage data, excitation current data, cell center temperature and a Nyquist diagram of a lithium battery to be detected; judging whether the lithium battery to be detected has a lithium precipitation condition according to the number of minimum points in the Nyquist diagram; if the lithium battery to be detected does not have the lithium precipitation condition, it is determined that the lithium battery to be detected can continue to be used; if the lithium battery to be detected has the lithium precipitation condition, an impedance abnormality coefficient of the lithium battery to be detected is acquired according to the impedance characteristics in the Nyquist diagram of the lithium battery to be detected, and a battery lithium precipitation factor of the lithium battery to be detected is acquired in combination with the change characteristics of the cell center temperature of the lithium battery to be detected and the fluctuation degree of the phase difference between the voltage data and the excitation current data, so as to judge whether the lithium battery to be detected can continue to be used. The application improves the accuracy of lithium precipitation condition evaluation of the lithium battery by analyzing the impedance abnormality characteristics and the temperature abnormality characteristics of the lithium battery to be detected.

Description

Technical Field

[0001] This application relates to the field of lithium battery testing technology, specifically to a lithium battery testing device and method. Background Technology

[0002] With the increasing demand for lithium batteries in electric vehicles, energy storage systems, and portable electronic devices, the performance stability and safety of lithium batteries have become a focus of industry development. While lithium batteries offer the advantage of high energy density, their chemical reactivity makes them prone to fire and explosion under conditions of thermal runaway, overcharging, and short circuits. The core function of lithium battery testing equipment is to accurately measure and evaluate various performance parameters of the battery, ensuring stable performance in practical applications and extending its lifespan through rigorous testing.

[0003] Lithium plating is a phenomenon where lithium ions, deintercalated from the positive electrode, fail to reintercalate into the negative electrode during lithium-ion battery charging due to abnormal conditions, resulting in their deposition on the negative electrode surface. Traditional methods for detecting lithium plating in lithium batteries, using electrochemical impedance spectroscopy (EIS), can analyze the impedance characteristics of the battery at different frequencies, thus providing a layered analysis of the battery's internal state. However, EIS is highly temperature-sensitive; uneven temperature distribution within the lithium battery can easily cause impedance data drift, disrupting the lithium plating characteristics shown in the Nyquist plot. Existing methods often assess the severity of lithium plating solely based on the impedance characteristics in the Nyquist plot, neglecting the impact of uneven temperature distribution on the impedance data. This leads to misjudgments of the lithium plating status and severely limits the accuracy of lithium battery performance testing and lifespan assessment. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a lithium battery testing device and method, the specific technical solution of which is as follows: In a first aspect, embodiments of this application provide a lithium battery testing method, which includes the following steps: Real-time acquisition of voltage data, excitation current data, cell center temperature, and cell edge temperature of the lithium battery under test throughout the entire testing process, and acquisition of the Nyquist plot of the lithium battery under test; Based on the number of minimum points in the Nyquist plot of the lithium battery under test, it is determined whether the lithium battery under test has lithium plating. If there is no lithium plating, it is determined that the lithium battery under test can continue to be used. If there is lithium plating, the impedance anomaly coefficient of the lithium battery under test is obtained based on the impedance magnitude, frequency range, and negative phase angle shift of the second capacitive arc in the Nyquist plot of the lithium battery under test, as well as the upward trend strength and instability of the curve after the last minimum point in the Nyquist plot. Based on the changing trend and dispersion of the cell center temperature of the lithium battery under test, the changing trend of the difference between the cell center temperature and the cell edge temperature, the degree of difference between the cell center temperature and the voltage data, and the fluctuation degree of the phase difference between the voltage data and the excitation current data in the preset low-to-medium frequency band, the temperature impedance interference value of the lithium battery under test is obtained. Combined with the impedance anomaly coefficient of the lithium battery under test, the lithium plating factor of the lithium battery under test is obtained, thereby determining whether the lithium battery under test can continue to be used.

[0005] Preferably, the specific process for determining whether the lithium battery under test has lithium plating is as follows: obtain all minimum points in the Nyquist plot of the lithium battery under test except for the starting endpoint; if there is only one minimum point, it is determined that the lithium battery under test does not have lithium plating; if there are two minimum points, it is determined that the lithium battery under test has lithium plating.

[0006] Preferably, the method for obtaining the impedance anomaly coefficient of the lithium battery under test is as follows: The first and second minimum points in the Nyquist plot of the lithium battery under test are taken as the start and end points of the second capacitive arc in the Nyquist plot; the impedance amplification factor of the lithium battery under test is obtained according to the impedance magnitude and frequency range of the second capacitive arc in the Nyquist plot. Calculate the angles between all data points and the origin in the Nyquist plot of the lithium battery under test, from the starting point of the second capacitive reactance arc to the maximum value of its ordinate. Calculate the sequence of all angles from left to right according to the corresponding data points as the capacitive reactance phase angle sequence of the lithium battery under test. Calculate the sum of all difference values ​​in the capacitive reactance phase angle sequence of the lithium battery under test. The sequence of ordinates of all data points after the last minimum point in the Nyquist plot of the lithium battery under test is denoted as the diffusion impedance sequence of the lithium battery under test; the variance of all difference values ​​of the diffusion impedance sequence of the lithium battery under test is calculated; and the Z-value statistic of the diffusion impedance sequence of the lithium battery under test is obtained. The normalized value of the product of the impedance amplification factor, sum, variance, and Z-value statistics is denoted as the impedance anomaly coefficient of the lithium battery under test.

[0007] Preferably, the method for obtaining the impedance amplification factor of the lithium battery under test is as follows: obtain the maximum value of the vertical coordinate within the second capacitive arc in the Nyquist plot of the lithium battery under test, and calculate the absolute difference between the horizontal coordinates corresponding to the start and end points of the second capacitive arc. The product of the maximum value of the vertical coordinate and the absolute difference is recorded as the impedance amplification factor of the lithium battery under test.

[0008] Preferably, the formula for calculating the temperature impedance interference value of the lithium battery under test is as follows: In the formula, The temperature impedance interference value of the lithium battery under test; This is the sum of the differences between the trend terms of each data point in the cell center temperature sequence of the lithium battery under test; is an exponential function with the natural constant e as the base; k is the variance of the cell center temperature sequence of the lithium battery under test; Let be the slope of the fitted straight line of the local temperature difference of the lithium battery under test at all sampling times during the entire test process; dW distance is the DTW distance between the cell center temperature sequence and voltage sequence of the lithium battery under test; b is the phase offset factor of the lithium battery under test; norm() is the normalization function; Among them, the cell center temperature sequence and voltage sequence of the lithium battery under test refer to the sequence composed of the cell center temperature and voltage data of the lithium battery under test arranged in chronological order throughout the entire test process.

[0009] Preferably, the local temperature difference of the lithium battery under test at each sampling time refers to the difference between the temperature at the center of the cell and the temperature at the edge of the cell at each sampling time.

[0010] Preferably, the method for obtaining the phase shift factor of the lithium battery under test is as follows: obtaining the phase frequency data of the voltage data and excitation current data of the lithium battery under test throughout the entire test process; calculating the absolute difference between the phase of the voltage data and the excitation current data at each frequency in the preset low-frequency band, and recording the variance of all absolute differences as the phase shift factor of the lithium battery under test.

[0011] Preferably, the lithium plating factor of the lithium battery under test refers to the product of the impedance anomaly coefficient and the temperature impedance interference value of the lithium battery under test.

[0012] Preferably, the specific process for determining whether the lithium battery under test can continue to be used is as follows: when the lithium plating factor of the lithium battery under test is less than the preset lithium plating threshold, it is determined that the lithium battery under test can continue to be used; otherwise, it is determined that the lithium battery under test can no longer be used.

[0013] Secondly, embodiments of this application also provide a lithium battery testing device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described lithium battery testing methods.

[0014] This application has at least the following beneficial effects: This application addresses the problem that traditional electrochemical impedance spectroscopy for detecting lithium plating characteristics in lithium batteries fails to consider the impact of uneven temperature distribution on impedance data in the Nyquist plot, leading to misjudgments of lithium plating status. By analyzing the impedance change characteristics and trends in the Nyquist plot of a lithium battery exhibiting lithium plating, an impedance anomaly coefficient is constructed, enabling accurate assessment of the degree of impedance anomaly caused by lithium plating. Furthermore, by analyzing the temperature change characteristics of the cell center, the differences between the cell center temperature and cell edge temperature and voltage data, and the phase difference fluctuation between voltage and excitation current data, a temperature impedance interference value is constructed, accurately assessing the degree of temperature anomaly caused by lithium plating throughout the testing process. Finally, a lithium plating factor is constructed, allowing for precise assessment of the severity of lithium plating, thus improving the accuracy of lithium plating status assessment and consequently, the accuracy of lithium battery life assessment. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a lithium battery testing method provided in one embodiment of this application; Figure 2 This is a flowchart illustrating the steps for determining whether a lithium battery under test can continue to be used, as provided in one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a lithium battery testing device and method proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the lithium battery testing equipment and method provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a lithium battery testing method according to an embodiment of this application. The method includes the following steps: Step 1: Real-time acquisition of voltage data, excitation current data, cell center temperature, and cell edge temperature of the lithium battery under test throughout the entire testing process, and acquisition of the Nyquist plot of the lithium battery under test.

[0021] The lithium battery testing scenario in this application is set as the battery charging and discharging process, and the charging process from 10% to 80% of the lithium battery's state of charge (SOC) is recorded as a test process. Throughout the test, a sinusoidal current signal with a fixed peak value and continuously changing frequency is input to the lithium battery under test as the excitation current signal. In this embodiment, the sweep frequency range of the sinusoidal current signal is set to 0.1Hz-10kHz, and the sweep direction is from high frequency to low frequency. During the test, the voltage signal and excitation current signal at both ends of the lithium battery under test are collected in real time by voltage and current sensors, with the sampling frequency set to FkHz (F is 20 in this embodiment). Based on the voltage and excitation current data at each sampling moment, and combined with the complex form of Ohm's law, the complex impedance at each sampling moment is calculated. The real and imaginary parts of the complex impedance of the lithium battery under test at all sampling moments throughout the entire test process are plotted on the complex plane to obtain the Nyquist plot of the lithium battery under test throughout the entire test process. Temperature sensors were deployed at the center and edge of the lithium-ion battery cell under test to acquire the center and edge temperatures of the cell in real time. The sampling frequency was also set to FkHz. Since the Nyquist plotting technique is well-known, the specific acquisition process will not be described in detail.

[0022] To avoid the impact of inconsistent dimensions on subsequent analysis, this application normalizes the voltage data, excitation current data, cell center temperature, and cell edge temperature obtained throughout the testing process. The normalization methods include, but are not limited to, the maximum-minimum normalization method and the Z-score normalization method. In this embodiment, the maximum-minimum normalization method is used for normalization.

[0023] Thus, the voltage data, excitation current data, cell center temperature, cell edge temperature, and Nyquist plot of the lithium battery under test were obtained throughout the entire testing process.

[0024] Step 2: Determine whether lithium plating exists in the lithium battery under test based on the number of minimum points in the Nyquist plot. If lithium plating does not exist, the lithium battery under test can continue to be used. If lithium plating exists, obtain the impedance anomaly coefficient of the lithium battery under test based on the impedance magnitude, frequency range, and negative phase angle shift of the second capacitive arc in the Nyquist plot, as well as the upward trend strength and instability of the curve after the last minimum point in the Nyquist plot.

[0025] In the process of detecting lithium plating in lithium batteries using EIS (electrochemical impedance spectroscopy), existing methods assess the impedance characteristics of the lithium battery under test based on its Nyquist plot, thereby evaluating the presence and severity of lithium plating. However, lithium plating causes internal temperature changes, leading to inaccuracies in the impedance characteristics of the Nyquist plot. Existing methods do not consider the influence of temperature on lithium plating detection, resulting in misjudgments and affecting the accuracy of the detection. Therefore, a more in-depth analysis of the temperature characteristics and Nyquist plot of the lithium battery under test is needed.

[0026] Specifically, in the process of testing lithium batteries using the EIS electrochemical impedance spectroscopy, when the lithium battery under test does not have lithium plating, only one capacitive arc, namely the first capacitive arc, exists in its Nyquist plot. When the lithium battery under test has lithium plating, a second capacitive arc appears in its Nyquist plot. The more severe the lithium plating, the more the deposited lithium metal layer increases the interfacial kinetic resistance and the effective surface area of ​​the electrode, resulting in a more significant increase in charge transfer impedance. That is, the impedance of the second capacitive arc in the Nyquist plot is larger, the frequency range it occupies is wider, and the negative phase angle shift is more severe (since the vertical axis of the Nyquist plot is a negative imaginary part, a severe negative phase angle shift is manifested as a larger angle between the phase angle and the origin). At the same time, lithium plating in lithium batteries hinders the transport and diffusion of lithium ions inside the electrode, resulting in a stronger upward trend in impedance in the low-frequency range and more unstable impedance fluctuations in the low-frequency range.

[0027] Based on the above analysis, an extreme value detection algorithm is used to obtain all minimum points in the Nyquist plot of the lithium battery under test, excluding the starting endpoint. If only one minimum point exists, the capacitive arc characteristic in the Nyquist plot conforms to the characteristics of a normal lithium battery, indicating that the lithium battery under test does not exhibit lithium plating and can therefore be used. If two minimum points exist, the lithium battery under test is determined to exhibit lithium plating, and the severity of the lithium plating needs to be further assessed to determine whether the battery can continue to be used. It should be noted that regardless of whether the lithium battery under test exhibits lithium plating, its Nyquist plot must contain at least one minimum point and at most two minimum points, excluding the maximum or minimum value at the starting endpoint.

[0028] When the lithium battery under test is in a lithium plating state, the first and second minimum points in its Nyquist plot are taken as the start and end points of the second capacitive arc in the Nyquist plot, respectively. The maximum value of the vertical axis within the second capacitive arc is obtained, and the absolute difference between the horizontal axis corresponding to the start and end points of the second capacitive arc is calculated. The product between the maximum value of the vertical axis and the absolute difference is recorded as the impedance amplification factor of the lithium battery under test, which is used to characterize the degree of increase in charge transfer impedance of the lithium battery under test throughout the entire test process. The larger the value, the greater the degree of increase in charge transfer impedance of the lithium battery under test throughout the entire test process.

[0029] The angles between all data points and the origin in the Nyquist plot of the lithium battery under test, from the starting point of the second capacitive reactance arc to the maximum value of its ordinate, are counted. The sequence of all angles arranged from left to right according to their corresponding data points is taken as the capacitive reactance phase angle sequence of the lithium battery under test.

[0030] The sequence of ordinates of all data points after the last minimum point in the Nyquist plot of the lithium battery under test is denoted as the diffusion impedance sequence of the lithium battery under test. Using the obtained diffusion impedance sequence as input, the Mann-Kendall trend test algorithm is used to obtain the Z-value statistic of the diffusion impedance sequence. A larger Z-value statistic indicates a stronger upward trend in low-frequency impedance caused by lithium plating in the lithium battery under test. The Mann-Kendall trend test algorithm is a well-known technique, and its specific process will not be elaborated further.

[0031] As a preferred embodiment, the impedance anomaly coefficient of the lithium battery under test is obtained based on the impedance magnitude, frequency range, and negative phase angle shift of the second capacitive arc in the Nyquist plot of the lithium battery under test, as well as the upward trend strength and instability of the curve after the last minimum point in the Nyquist plot. This coefficient is used to characterize the degree of impedance anomaly caused by lithium plating during the test.

[0032] In this embodiment, the impedance anomaly coefficient of the lithium battery under test is denoted as... Its specific expression is: In the formula, The impedance anomaly coefficient of the lithium battery under test; The impedance increase factor of the lithium battery under test; This is the sum of all the difference values ​​of the phase angle sequence of the capacitive reactance of the lithium battery under test; denoted as the variance of all difference values ​​in the diffusion impedance sequence of the lithium battery under test; Let Z be the Z-statistic of the diffusion impedance sequence of the lithium battery under test; norm() is the normalization function, which makes Z = Z / N. The value range is between (0,1), and the tanh function is used for normalization in this embodiment.

[0033] The impedance anomaly coefficient reflects the increase in interfacial kinetic resistance caused by lithium plating during the test of the lithium battery under test, as well as the degree of obstruction to lithium ion diffusion. The larger the value, the greater the impedance anomaly caused by lithium plating, and the more severe the lithium plating condition of the lithium battery under test.

[0034] Step 3: Based on the changing trend and dispersion of the cell center temperature of the lithium battery under test, the changing trend of the difference between the cell center temperature and the cell edge temperature, the degree of difference between the cell center temperature and the voltage data, and combined with the fluctuation of the phase difference between the voltage data and the excitation current data in the preset low-to-medium frequency band, the temperature impedance interference value of the lithium battery under test is obtained. Combined with the impedance anomaly coefficient of the lithium battery under test, the lithium plating factor of the lithium battery under test is obtained, thereby determining whether the lithium battery under test can continue to be used.

[0035] Furthermore, in the process of detecting lithium plating in lithium batteries using electrochemical impedance spectroscopy, temperature changes directly alter the ionic conductivity, charge transfer resistance, and interfacial reaction kinetics of the cell materials (electrodes or electrolyte). If lithium plating is present in the lithium battery, it leads to an increase in internal temperature, which accelerates the charge transfer reaction rate at the electrode interface, thereby reducing the charge transfer resistance. If the severity of lithium plating in the tested lithium battery is analyzed solely based on the characteristics in the Nyquist plot, the impedance characteristics in the Nyquist plot may be inaccurate. Therefore, during the lithium plating test of the tested lithium battery, it is necessary to consider the internal temperature fluctuation characteristics to comprehensively assess the severity of lithium plating.

[0036] Specifically, during the entire testing process of the lithium battery under test, the more severe the lithium plating, the stronger the upward trend and fluctuation of the cell center temperature due to the difficulty in heat dissipation at the center of the lithium battery, and the more obvious the continuous increase in the gradient difference between the cell center temperature and the cell edge temperature. At the same time, since the EIS testing equipment in this application adopts constant current mode and outputs a stable sinusoidal current amplitude, when the high-temperature impedance of the lithium battery decreases, the current of the lithium battery remains unchanged, but the voltage decreases and drifts, which leads to a greater difference in the trend of change between the lithium battery voltage signal and the cell center temperature. In addition, the voltage drift of the lithium battery will cause the phase difference between the voltage signal and the excitation current signal to deviate from the normal phase difference, and the voltage drift usually occurs in the mid-to-low frequency range, so the fluctuation of the phase difference between the voltage signal and the excitation current signal in the mid-to-low frequency range is greater.

[0037] Based on the above analysis, the cell center temperatures of the lithium battery under test are arranged in chronological order throughout the entire testing process to obtain the cell center temperature sequence. This sequence is then used as input to a sequence decomposition algorithm (Seasonal and Trend decomposition using Loess, STL) to obtain the trend term for each data point in the cell center temperature sequence. The difference between the cell center temperature and the cell edge temperature at each sampling time during the entire testing process is recorded as the local temperature difference at each sampling time.

[0038] The voltage and excitation current data of the lithium battery under test throughout the entire testing process are converted to the frequency domain using Fast Fourier Transform (FFT) to obtain the phase frequency data of the voltage and excitation current data. The absolute difference between the phase of the voltage data and the excitation current data at each frequency within a preset low-to-mid frequency band (0.1Hz-1kHz in this embodiment) is calculated, and the variance of all absolute differences is recorded as the phase shift factor of the lithium battery under test. Since the STL algorithm and Fast Fourier Transform are well-known technologies, the specific acquisition process will not be described in detail.

[0039] As a preferred embodiment, the temperature impedance interference value of the lithium battery under test is obtained based on the changing trend and dispersion of the cell center temperature, the changing trend of the difference between the cell center temperature and the cell edge temperature, the degree of difference between the cell center temperature and the voltage data, and the fluctuation degree of the phase difference between the voltage data and the excitation current data in the preset low-frequency band. This value is used to characterize the degree of temperature anomaly of the lithium battery under test due to the lithium plating condition during the entire test process.

[0040] In this embodiment, the temperature impedance interference value of the lithium battery under test is denoted as... Its specific expression is: In the formula, The temperature impedance interference value of the lithium battery under test; This is the sum of the differences between the trend terms of each data point in the cell center temperature sequence of the lithium battery under test; is an exponential function with the natural constant e as the base; k is the variance of the cell center temperature sequence of the lithium battery under test; Let be the slope of the fitted straight line of the local temperature difference of the lithium battery under test at all sampling times during the entire test process; denoted as DTW distance between the center temperature sequence and voltage sequence of the lithium battery cell under test; b is the phase shift factor of the lithium battery under test; norm() is the normalization function, which makes ... The value range is between [0,1]. In this embodiment, the tanh function is used for normalization.

[0041] The greater the severity of lithium plating inside the tested lithium battery, the greater the temperature fluctuation at the cell center due to heat accumulation, the stronger the upward trend of the cell center temperature, the greater the temperature difference between the cell center and the edge, the greater the difference between the cell center temperature and the voltage signal change trend, and the more obvious the phase difference shift between the voltage signal and the excitation current signal in the mid-to-low frequency band. Consequently, the calculated temperature impedance interference value is greater. The temperature impedance interference value reflects the degree of temperature anomaly caused by lithium plating during the entire test process; the larger the value, the greater the degree of temperature anomaly caused by lithium plating during the entire test process, and therefore the greater the severity of the lithium plating condition in the tested lithium battery.

[0042] Furthermore, as a preferred embodiment, the lithium plating factor of the lithium battery under test is obtained based on the impedance anomaly coefficient and temperature impedance interference value, which is used to characterize the severity of lithium plating in the lithium battery under test.

[0043] Specifically, in this embodiment, the product of the impedance anomaly coefficient of the lithium battery under test and the temperature impedance interference value is used as the lithium plating factor of the lithium battery under test. The larger the lithium plating factor, the greater the degree of temperature anomaly of the lithium battery under test, and the more severe the impedance anomaly caused by lithium plating, the greater the severity of the lithium plating condition of the lithium battery under test.

[0044] Furthermore, N lithium batteries exhibiting lithium plating are obtained from historical testing data. The lithium plating factor of all these batteries is then obtained using the steps described above. All lithium plating factors are used as input, and the Otsu's method is employed to obtain a segmentation threshold, which is then recorded as the preset lithium plating threshold. When the lithium plating factor of the tested lithium battery is less than the preset threshold, it indicates that the lithium plating condition and aging of the tested lithium battery are relatively mild, and the tested lithium battery is determined to be usable. When the lithium plating factor of the tested lithium battery is greater than or equal to the preset threshold, it indicates that the lithium plating condition and aging of the tested lithium battery are relatively severe, and the tested lithium battery is determined to be unusable. In this embodiment, N is set to 50, but the implementer can choose a value according to the actual situation. The flowchart for determining whether the tested lithium battery can continue to be used is shown below. Figure 2 As shown.

[0045] Based on the same inventive concept as the above method, this application embodiment also provides a lithium battery testing device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described lithium battery testing methods.

[0046] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0047] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0048] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for detecting lithium batteries, characterized in that, The method includes the following steps: Real-time acquisition of voltage data, excitation current data, cell center temperature, and cell edge temperature of the lithium battery under test throughout the entire testing process, and acquisition of the Nyquist plot of the lithium battery under test; Based on the number of minimum points in the Nyquist plot of the lithium battery under test, it is determined whether the lithium battery under test has lithium plating. If there is no lithium plating, it is determined that the lithium battery under test can continue to be used. If there is lithium plating, the impedance anomaly coefficient of the lithium battery under test is obtained based on the impedance magnitude, frequency range, and negative phase angle shift of the second capacitive arc in the Nyquist plot of the lithium battery under test, as well as the upward trend strength and instability of the curve after the last minimum point in the Nyquist plot. Based on the changing trend and dispersion of the cell center temperature of the lithium battery under test, the changing trend of the difference between the cell center temperature and the cell edge temperature, the degree of difference between the cell center temperature and the voltage data, and the fluctuation degree of the phase difference between the voltage data and the excitation current data in the preset low and medium frequency band, the temperature impedance interference value of the lithium battery under test is obtained. Combined with the impedance anomaly coefficient of the lithium battery under test, the lithium plating factor of the lithium battery under test is obtained, so as to determine whether the lithium battery under test can continue to be used. The lithium plating factor of the lithium battery under test refers to the product of the impedance anomaly coefficient and the temperature impedance interference value of the lithium battery under test.

2. The lithium battery testing method as described in claim 1, characterized in that, The specific process for determining whether the lithium battery under test has lithium plating is as follows: obtain all minimum points in the Nyquist plot of the lithium battery under test except for the starting endpoint. If there is only one minimum point, it is determined that the lithium battery under test does not have lithium plating; if there are two minimum points, it is determined that the lithium battery under test has lithium plating.

3. The lithium battery testing method as described in claim 1, characterized in that, The method for obtaining the impedance anomaly coefficient of the lithium battery under test is as follows: The first and second minimum points in the Nyquist plot of the lithium battery under test are taken as the start and end points of the second capacitive arc in the Nyquist plot; the impedance amplification factor of the lithium battery under test is obtained according to the impedance magnitude and frequency range of the second capacitive arc in the Nyquist plot. Calculate the angles between all data points and the origin in the Nyquist plot of the lithium battery under test, from the starting point of the second capacitive reactance arc to the maximum value of its ordinate. Calculate the sequence of all angles from left to right according to the corresponding data points as the capacitive reactance phase angle sequence of the lithium battery under test. Calculate the sum of all difference values ​​in the capacitive reactance phase angle sequence of the lithium battery under test. The sequence of ordinates of all data points after the last minimum point in the Nyquist plot of the lithium battery under test is denoted as the diffusion impedance sequence of the lithium battery under test; the variance of all difference values ​​of the diffusion impedance sequence of the lithium battery under test is calculated. Obtain the Z-value statistics of the diffusion impedance sequence of the lithium battery under test; The normalized value of the product of the impedance amplification factor, sum, variance, and Z-value statistics is denoted as the impedance anomaly coefficient of the lithium battery under test.

4. The lithium battery testing method as described in claim 3, characterized in that, The method for obtaining the impedance amplification factor of the lithium battery under test is as follows: obtain the maximum value of the vertical coordinate within the second capacitive arc in the Nyquist plot of the lithium battery under test, and calculate the absolute difference between the horizontal coordinates corresponding to the start and end points of the second capacitive arc. The product of the maximum value of the vertical coordinate and the absolute difference is recorded as the impedance amplification factor of the lithium battery under test.

5. The lithium battery testing method as described in claim 1, characterized in that, The formula for calculating the temperature impedance interference value of the lithium battery under test is as follows: In the formula, The temperature impedance interference value of the lithium battery under test; is the sum of the differences between the trend terms of each data point in the cell center temperature sequence of the lithium battery under test; exp() is an exponential function with the natural constant e as the base; k is the variance of the cell center temperature sequence of the lithium battery under test; H is the slope of the fitted line of the local temperature difference at all sampling times of the lithium battery under test throughout the entire test process; D is the DTW distance between the cell center temperature sequence and the voltage sequence of the lithium battery under test; b is the phase offset factor of the lithium battery under test; norm() is the normalization function; Among them, the cell center temperature sequence and voltage sequence of the lithium battery under test refer to the sequence composed of the cell center temperature and voltage data of the lithium battery under test arranged in chronological order throughout the entire test process.

6. The lithium battery testing method as described in claim 5, characterized in that, The local temperature difference of the lithium battery under test at each sampling time refers to the difference between the temperature at the center of the cell and the temperature at the edge of the cell at each sampling time.

7. The lithium battery testing method as described in claim 5, characterized in that, The method for obtaining the phase shift factor of the lithium battery under test is as follows: obtain the phase frequency data of the voltage data and excitation current data of the lithium battery under test throughout the entire test process; calculate the absolute difference between the phase of the voltage data and the excitation current data at each frequency in the preset low-frequency band, and record the variance of all absolute differences as the phase shift factor of the lithium battery under test.

8. The lithium battery testing method as described in claim 1, characterized in that, The specific process for determining whether the lithium battery under test can continue to be used is as follows: when the lithium plating factor of the lithium battery under test is less than the preset lithium plating threshold, it is determined that the lithium battery under test can continue to be used; otherwise, it is determined that the lithium battery under test cannot continue to be used.

9. A lithium battery testing device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the lithium battery detection method as described in any one of claims 1-8.

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