Detection method of lithium deposition in negative electrode of low-temperature fast-charging lithium battery based on AC impedance spectroscopy

Abstract

The present invention relates to a method for detecting lithium deposition at a negative electrode of a low-temperature fast-charge lithium battery based on an alternating current impedance spectrum, and belongs to the technical field of lithium batteries. The method comprises the following steps: superimposing signals at different frequency points to form a fast-sweep multi-sinusoidal synthesis signal, inputting the signal into a programmable power supply to generate an excitation current, using a Hall sensor to implement excitation current signal transmission, and measuring the transmitted current signal and battery terminal voltage through a data acquisition card; using the excitation current generated by the multi-sinusoidal synthesis signal to charge the battery, measuring the battery voltage and current signals, intercepting finite-length voltage and current signals through a window function to perform fast Fourier transform, and obtaining the battery alternating current impedance spectrum during the battery charging process; coupling a battery model of the alternating current impedance characteristics; and using a model-driven or data-driven method to establish a mapping relationship between the alternating current impedance spectrum and the severity of lithium deposition, and judging the severity of lithium deposition by analyzing the change trend of the alternating current impedance spectrum, thereby realizing lithium deposition detection.

Description

Technical Field

[0001] The present invention belongs to the technical field of lithium batteries, and in particular relates to a method for detecting lithium deposition at a negative electrode of a low-temperature fast-charging lithium battery based on an alternating current impedance spectrum. Background Art

[0002] Lithium-ion batteries are secondary batteries that work by converting chemical energy between the positive and negative electrodes. During normal charging, lithium ions are released from the anode and embedded in the cathode graphite material through the diaphragm; however, during high-rate or low-temperature charging, the lithium insertion potential of graphite is close to the deposition potential of metallic lithium (Li x C 6 , 0.5≤x≤1, the lithium insertion potential of graphite is about 0.08V), and the lithium ions are not able to embed into the graphite negative electrode in time and deposit on the graphite surface to form dendrite-like metallic lithium. The deposited metallic lithium reacts with the electrolyte to consume active lithium, causing battery power and capacity loss; at the same time, lithium dendrites may pierce the diaphragm, triggering a short circuit in the battery and causing safety problems.

[0003] At present, there are three types of traditional lithium deposition detection methods. 1. In-situ material characterization method is a physical observation method based on in-situ material characterization of surface chemistry and non-in-situ material characterization based on surface morphology. Before using the in-situ material characterization method for lithium deposition diagnosis, the battery needs to be subjected to special test treatment. The negative electrode plates of the battery are disassembled in the glove box and cleaned with dimethyl carbonate solution to destroy the battery structure. This destructive detection process of the battery makes it difficult to apply this method in the actual online detection of the battery energy storage system. 2. Acoustic detection method is a non-destructive lithium deposition detection method that uses ultrasonic waves to transmit lithium batteries charged at different rates at low temperature and detect whether the endpoint of the acoustic wave flight time is offset to determine whether lithium deposition occurs. However, this non-destructive detection method is also affected by the coupling interference of electrothermal factors such as charging rate-ambient temperature-battery state of charge during the test process, and the acoustic detection system is expensive and the test conditions are demanding. It is difficult to promote and popularize in the complex environment of new energy vehicle battery energy storage systems and wind-light grid energy storage. 3. The electrochemical detection method requires the battery to stand for several hours to eliminate the influence of electrochemical polarization inside the battery. Therefore, the detection and analysis time is long and it is not easy to promote commercial application. Summary of the invention

[0004] The purpose of the present invention is to provide a method for detecting lithium deposition at the negative electrode of a low-temperature fast-charged lithium battery based on AC impedance spectroscopy, which is used to solve the technical problems existing in the above-mentioned prior art, and to detect the lithium deposition problem of a low-temperature, high-rate fast-charged lithium-ion power battery using the battery AC impedance spectrum information during the charging process. The method collects the characteristic change trend of the real part of the battery AC impedance when lithium deposition occurs within a certain frequency range, establishes a fast calculation method for the battery AC impedance spectrum, eliminates the interference of electrothermal factors on impedance collection, and achieves efficient, fast and non-destructive lithium deposition detection.

[0005] To achieve the above object, the technical solution of the present invention is:

[0006] The method for detecting lithium deposition at the negative electrode of a low-temperature fast-charging lithium battery based on AC impedance spectroscopy comprises the following steps:

[0007] S1. Superimpose signals at different frequency points to form a fast-sweep multi-sine synthetic signal, input it into a programmable power supply to generate an excitation current, use a Hall sensor to achieve excitation current signal transmission, and measure the transmitted current signal and battery terminal voltage through a data acquisition card;

[0008] S2, using the excitation current generated by the multi-sine synthesis signal to charge the battery, measuring the battery voltage and current signals, intercepting the finite length voltage and current signals through a window function to perform fast Fourier transform, and obtaining the battery AC impedance spectrum during the battery charging process;

[0009] S3. According to the Butler-Volmer equation, a battery model that integrates the time-frequency domain electrothermal factor coupling AC impedance characteristics of the battery electrical equivalent circuit model and the thermal equivalent circuit model is established to eliminate the influence of the electrothermal factor on the AC impedance during the charging process;

[0010] S4. Use a model-driven or data-driven approach to establish a mapping relationship between the AC impedance spectrum and the severity of lithium deposition. By analyzing the change trend of the AC impedance spectrum, the severity of lithium deposition can be determined, thereby achieving lithium deposition detection.

[0011] Furthermore, in step S1, the Hall sensor is used to implement the excitation current signal transmission as follows:

[0012] When the programmable power supply generates an excitation current flowing through the Hall sensor, the magnetic field generated on the wire is gathered by the magnetic ring and induced to the Hall device. The generated signal output is used to drive the power tube and turn it on, thereby obtaining a compensation current.

[0013] The compensation current then generates a magnetic field through a multi-turn winding, and the magnetic field is exactly opposite to the magnetic field generated by the excitation current, thereby compensating the original magnetic field and gradually reducing the output of the Hall device;

[0014] When the magnetic field generated by multiplying the excitation current by the number of turns is equal, the compensation current no longer increases. At this time, the Hall sensor plays the role of indicating zero magnetic flux. At this time, the excitation current is tested by the compensation current.

[0015] When the excitation current changes, the balance is destroyed and the Hall sensor outputs a signal, that is, the above process is repeated to regain balance. Any change in the excitation current will destroy this balance, thereby realizing the transmission of the excitation current signal.

[0016] Further, step S2 is specifically as follows:

[0017] Using multi-sinusoidal signals, input to the programmable power supply;

[0018] The programmable power supply charges the battery, and the data acquisition card is used to collect the voltage and current signals of the battery;

[0019] The finite-length voltage and current signals are intercepted by using the window function, and the voltage function and the current function are obtained by performing fast Fourier transform respectively.

[0020] The ratio of the voltage function to the current function is the AC impedance spectrum of the battery.

[0021] Furthermore, step S3 is specifically as follows:

[0022] The current and state of charge are used as inputs of the electrical equivalent circuit model, and the electrical equivalent circuit model outputs voltage and heat generation power;

[0023] The heat generation power and the ambient temperature are used as inputs of the thermal equivalent circuit model, which outputs the actual battery temperature and acts on the battery AC impedance spectrum;

[0024] The actual temperature of the battery is applied to the AC impedance spectrum and then inputted back into the electrical equivalent circuit model;

[0025] The electrical equivalent circuit model and the thermal equivalent circuit model are coupled through the Butler-Volmer equation to form a battery model with electric and thermal factors coupled with AC impedance characteristics in the time-frequency domain.

[0026] Further, step S4 is specifically as follows:

[0027] Use scanning electron microscopy or solid-state nuclear magnetic resonance in-situ material characterization to extract lithium deposition severity maps at each stage of lithium deposition appearance, lithium deposition initiation, and lithium deposition aggravation;

[0028] Based on the above-mentioned method for obtaining the AC impedance spectrum, the impedance characteristic change trends of the AC impedance spectrum showing a downward trend, the AC impedance spectrum starting to decline, and the AC impedance spectrum decreasing trend aggravating are obtained respectively;

[0029] Use model-driven or data-driven machine learning algorithms to deeply explore the mapping relationship between the severity of lithium deposition and the characteristic trend of AC impedance spectroscopy;

[0030] According to the impedance characteristic change trend, the lithium deposition severity map is reversely compared to realize lithium deposition detection.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] One of the beneficial effects of the present scheme is that the present invention breaks the traditional destructive or extremely time-consuming lithium deposition detection method. The present invention uses the sweeping frequency method of multi-sinusoidal synthetic signals to quickly obtain the AC impedance spectrum information during the charging process, and establishes a mapping relationship between the characteristic change trend of the AC impedance spectrum and the severity of lithium deposition, thereby realizing efficient, rapid and non-destructive lithium deposition detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the overall process of a specific implementation method of the present invention.

[0034] Figure 2 The figure is a schematic diagram of the excitation current transmission process of a specific implementation mode of the present invention.

[0035] Figure 3 The figure is a schematic diagram of the AC impedance spectrum acquisition process according to a specific implementation mode of the present invention.

[0036] Figure 4 It is a schematic diagram of a battery model of time-frequency domain electrothermal factors coupled with AC impedance characteristics in a specific implementation mode of the present invention.

[0037] Figure 5 The figure is a schematic diagram of the detection process and discrimination basis of a specific implementation mode of the present invention. DETAILED DESCRIPTION

[0038] Below in conjunction with the appended Figure 1 -Attached Figure 5 , the technical solutions in the embodiments of the present invention are clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] At present, there are great limitations in the selection of locations for energy storage access to the grid.

[0040] Example:

[0041] like Figure 1 As shown, a method for detecting lithium deposition at the negative electrode of a low-temperature fast-charging lithium battery based on AC impedance spectroscopy is provided, comprising the following steps:

[0042] S1. Superimpose signals at different frequency points to form a fast-sweep multi-sine synthetic signal, input it into a programmable power supply to generate an excitation current, use a Hall sensor to achieve excitation current signal transmission, and measure the transmitted current signal and battery terminal voltage through a data acquisition card;

[0043] Among them, signal superposition can be carried out in the following ways:

[0044] Use MATLAB software to read the sinusoidal signals at different frequency points and assign them to a certain vector respectively. The specific MATLAB superposition code is as follows:

[0045] yt=sin(2*pi*t)+sin(100*pi*t)+…; % Different time domain frequency signals are superimposed.

[0046] subplot(1,2,1); %Set the signal layout after superposition.

[0047] plot(t(1:N),yt(1:N)); %Draw the time domain curve y(t).

[0048] title('y(t)=sin(2*pi*t)+sin(100*pi*t)'+...);

[0049] Y=FFT(yt); % Use FFT transformation on y(t) to obtain the spectrum.

[0050] w=((2*pi*fs) / N)*n; %Frequency domain unit conversion to obtain the analog angular frequency w.

[0051] subplot(1,2,2); %Set the image layout.

[0052] plot(w(1:N / 2),(2 / N)*abs(Y(1:N / 2))); %Draw the amplitude-frequency curve. Here, (2 / N)*abs(Y(1:150)) is used to get the true amplitude value.

[0053] title('Amplitude-frequency curve of y(t)'); %Realize the superposition of multiple sinusoidal signals at different frequency points.

[0054] S2, using the excitation current generated by the multi-sine synthesis signal to charge the battery, measuring the battery voltage and current signals, intercepting the finite length voltage and current signals through a window function to perform fast Fourier transform, and obtaining the battery AC impedance spectrum during the battery charging process;

[0055] S3. According to the Butler-Volmer equation, a battery model that integrates the time-frequency domain electrothermal factor coupling AC impedance characteristics of the battery electrical equivalent circuit model and the thermal equivalent circuit model is established to eliminate the influence of the electrothermal factor on the AC impedance during the charging process;

[0056] S4. Use a model-driven or data-driven approach to establish a mapping relationship between the AC impedance spectrum and the severity of lithium deposition. By analyzing the change trend of the AC impedance spectrum, the severity of lithium deposition can be determined, thereby achieving lithium deposition detection.

[0057] When the above plan is implemented:

[0058] 1. Use multi-sinusoidal synthetic current to charge the battery, measure and collect battery voltage and current signals;

[0059] 2. Use the window function to intercept the finite-length voltage and current signals for fast Fourier transform and collect the battery impedance characteristics under different charging conditions;

[0060] 3. Construct in situ material characterization of lithium deposition severity;

[0061] 4. Establish the relationship between the battery charge transfer process, diffusion process, conduction process and the parameters of the battery equivalent circuit model, and realize the battery low-temperature fast charging lithium deposition equivalent circuit model;

[0062] 5. Use the battery low-temperature fast-charging lithium deposition equivalent circuit model to analyze the changes in battery impedance characteristics under different charging conditions;

[0063] 6. Analyze the influence of electrothermal factors (including temperature, current, state of charge, etc.) on the change of battery impedance characteristics;

[0064] 7. Establish a sample data set of impedance characteristic changes without the influence of electrothermal factors and characteristic parameters of lithium deposition severity under in-situ material characterization;

[0065] 8. Use machine learning algorithms to deeply mine sample data sets of characteristic parameters of lithium deposition severity, establish a mapping relationship between AC impedance spectrum and lithium deposition severity, and by analyzing the changing trend of AC impedance spectrum, the severity of lithium deposition can be determined, thereby achieving efficient, rapid and non-destructive lithium deposition detection.

[0066] like Figure 2 As shown, further, in step S1, the excitation current signal is transmitted by using the Hall sensor as follows:

[0067] When the programmable power supply generates an excitation current flowing through the Hall sensor, the magnetic field generated on the wire is gathered by the magnetic ring and induced to the Hall device. The generated signal output is used to drive the power tube and turn it on, thereby obtaining a compensation current.

[0068] The compensation current then generates a magnetic field through a multi-turn winding, and the magnetic field is exactly opposite to the magnetic field generated by the excitation current, thereby compensating the original magnetic field and gradually reducing the output of the Hall device;

[0069] When the magnetic field generated by multiplying the excitation current by the number of turns is equal, the compensation current no longer increases. At this time, the Hall sensor plays the role of indicating zero magnetic flux. At this time, the excitation current is tested by the compensation current.

[0070] When the excitation current changes, the balance is destroyed and the Hall sensor outputs a signal, that is, the above process is repeated to regain balance. Any change in the excitation current will destroy this balance, thereby realizing the transmission of the excitation current signal.

[0071] like Figure 3 As shown, further, step S2 is specifically as follows:

[0072] Using multi-sinusoidal signals, input to the programmable power supply;

[0073] The programmable power supply charges the battery, and the data acquisition card is used to collect the voltage and current signals of the battery;

[0074] The finite-length voltage and current signals are intercepted by using the window function, and the voltage function and the current function are obtained by performing fast Fourier transform respectively.

[0075] The ratio of the voltage function to the current function is the AC impedance spectrum of the battery.

[0076] like Figure 4 As shown, further, step S3 is specifically as follows:

[0077] The current and state of charge are used as inputs of the electrical equivalent circuit model, and the electrical equivalent circuit model outputs voltage and heat generation power;

[0078] The heat generation power and the ambient temperature are used as inputs of the thermal equivalent circuit model, which outputs the actual battery temperature and acts on the battery AC impedance spectrum;

[0079] The actual temperature of the battery is applied to the AC impedance spectrum and then inputted back into the electrical equivalent circuit model;

[0080] The electrical equivalent circuit model and the thermal equivalent circuit model are coupled through the Butler-Volmer equation to form a battery model with electric and thermal factors coupled with AC impedance characteristics in the time-frequency domain.

[0081] like Figure 5 As shown, further, step S4 is specifically as follows:

[0082] Use scanning electron microscopy or solid-state nuclear magnetic resonance in-situ material characterization to extract lithium deposition severity maps at each stage of lithium deposition appearance, lithium deposition initiation, and lithium deposition aggravation;

[0083] Based on the above-mentioned method for obtaining the AC impedance spectrum, the impedance characteristic change trends of the AC impedance spectrum showing a downward trend, the AC impedance spectrum starting to decline, and the AC impedance spectrum decreasing trend aggravating are obtained respectively;

[0084] Use model-driven or data-driven machine learning algorithms to deeply explore the mapping relationship between the severity of lithium deposition and the characteristic trend of AC impedance spectroscopy;

[0085] According to the impedance characteristic change trend, the lithium deposition severity map is reversely compared to realize lithium deposition detection.

[0086] The above are preferred embodiments of the present invention. Any changes made according to the technical solution of the present invention, as long as the resulting functions do not exceed the scope of the technical solution of the present invention, belong to the protection scope of the present invention.

Claims

1. Detection method of lithium deposition at negative electrode of low-temperature fast-charge lithium battery based on AC impedance spectroscopy, It is characterized in that The following steps are involved: S1. Superimpose signals at different frequency points to form a fast-sweep multi-sine synthetic signal, input it into a programmable power supply to generate an excitation current, use a Hall sensor to achieve excitation current signal transmission, and measure the transmitted current signal and battery terminal voltage through a data acquisition card; S2, using the excitation current generated by the multi-sine synthesis signal to charge the battery, measuring the battery voltage and current signals, intercepting the finite length voltage and current signals through a window function to perform fast Fourier transform, and obtaining the battery AC impedance spectrum during the battery charging process; S3. According to the Butler-Volmer equation, a battery model that integrates the time-frequency domain electrothermal factor coupling AC impedance characteristics of the battery electrical equivalent circuit model and the thermal equivalent circuit model is established to eliminate the influence of the electrothermal factor on the AC impedance during the charging process; S4. Using a model-driven or data-driven method, a mapping relationship between the AC impedance spectrum and the severity of lithium deposition is established, and the severity of lithium deposition is determined by analyzing the change trend of the AC impedance spectrum, thereby realizing lithium deposition detection; Step S3 is as follows: The current and state of charge are used as inputs of the electrical equivalent circuit model, and the electrical equivalent circuit model outputs voltage and heat generation power; The heat generation power and the ambient temperature are used as inputs of the thermal equivalent circuit model, which outputs the actual battery temperature and acts on the battery AC impedance spectrum; The actual temperature of the battery is applied to the AC impedance spectrum and then inputted back into the electrical equivalent circuit model; The electrical equivalent circuit model and the thermal equivalent circuit model are coupled through the Butler-Volmer equation to form a battery model with electric and thermal factors coupled with AC impedance characteristics in the time-frequency domain. Step S4 is specifically as follows: Use scanning electron microscopy or solid-state nuclear magnetic resonance in-situ material characterization to extract lithium deposition severity maps at each stage of lithium deposition appearance, lithium deposition initiation, and lithium deposition aggravation; Based on the above-mentioned method for obtaining the AC impedance spectrum, the impedance characteristic change trends of the AC impedance spectrum showing a downward trend, the AC impedance spectrum starting to decline, and the AC impedance spectrum decreasing trend aggravating are obtained respectively; Use model-driven or data-driven machine learning algorithms to deeply explore the mapping relationship between the severity of lithium deposition and the characteristic trend of AC impedance spectroscopy; According to the impedance characteristic change trend, the lithium deposition severity map is reversely compared to realize lithium deposition detection.

2. The method for detecting lithium deposition at the negative electrode of a low-temperature fast-charging lithium battery based on AC impedance spectroscopy according to claim 1, It is characterized in that In step S1, the Hall sensor is used to implement the excitation current signal transmission as follows: When the programmable power supply generates an excitation current flowing through the Hall sensor, the magnetic field generated on the wire is gathered by the magnetic ring and induced to the Hall device. The generated signal output is used to drive the power tube and turn it on, thereby obtaining a compensation current. The compensation current then generates a magnetic field through a multi-turn winding, and the magnetic field is exactly opposite to the magnetic field generated by the excitation current, thereby compensating the original magnetic field and gradually reducing the output of the Hall device; When the magnetic field generated by multiplying the excitation current by the number of turns is equal, the compensation current no longer increases. At this time, the Hall sensor plays the role of indicating zero magnetic flux. At this time, the excitation current is tested by the compensation current. When the excitation current changes, the balance is destroyed and the Hall sensor outputs a signal, that is, the above process is repeated to regain balance. Any change in the excitation current will destroy this balance, thereby realizing the transmission of the excitation current signal.

3. The method for detecting lithium deposition at the negative electrode of a low-temperature fast-charging lithium battery based on AC impedance spectroscopy according to claim 2, It is characterized in that Step S1 is specifically as follows: Utilize multi-sine synthesis signal to input into programmable power supply; The programmable power supply charges the battery, and the data acquisition card is used to collect the voltage and current signals of the battery; The finite-length voltage and current signals are intercepted by using the window function, and the voltage function and the current function are obtained by performing fast Fourier transform respectively. The ratio of the voltage function to the current function is the AC impedance spectrum of the battery.

Images