Method and device for determining electrochemical impedance spectroscopy and battery health state

Abstract

The invention discloses a method and a device for determining an electrochemical impedance spectrum and a battery health state, and belongs to the technical field of electronic equipment. The determination method comprises the steps of performing pulse charging on a battery of the electronic equipment based on a preset pulse current, and collecting an electrical characteristic curve of the battery; performing curve reconstruction on the electrical characteristic curve through an interpolation method to obtain a reconstructed electrical characteristic curve; based on the reconstructed electrical characteristic curve, determining an electrical characteristic frequency domain coefficient of the battery; and determining the electrochemical impedance spectrum of the battery according to the electrical characteristic frequency domain coefficient.

Description

Technical Field

[0001] The present application belongs to the technical field of electronic equipment, and specifically relates to a method and device for determining electrochemical impedance spectroscopy and battery health status. Background Art

[0002] In related technologies, the management strategy for lithium-ion batteries is mainly based on the development of battery management algorithms based on the three external characteristics of the battery: battery current, battery voltage and battery temperature, including state estimation, performance evaluation, charge and discharge control, and safety warning management.

[0003] In the actual operation of electronic devices, due to complex working conditions and limited processing capabilities of electronic devices, it is impossible to accurately judge the status of lithium-ion batteries based solely on the above-mentioned limited external characteristics, resulting in inaccurate estimation of the battery status of electronic devices. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method and device for determining electrochemical impedance spectroscopy and battery health status, which can solve the problem of inaccurate battery status estimation of electronic devices.

[0005] In a first aspect, an embodiment of the present application provides a method for determining an electrochemical impedance spectrum of a battery of an electronic device, the determination method comprising:

[0006] Based on a preset pulse current, pulse charging is performed on the battery of the electronic device and an electrical characteristic curve of the battery is collected;

[0007] reconstructing the electrical characteristic curve by an interpolation method to obtain a reconstructed electrical characteristic curve;

[0008] Determining the battery's electrical characteristic frequency domain coefficient based on the reconstructed electrical characteristic curve;

[0009] The electrochemical impedance spectrum of the battery is determined based on the electrical characteristic frequency domain coefficients.

[0010] In a second aspect, an embodiment of the present application provides a method for determining the battery health status of a battery of an electronic device, the determination method comprising:

[0011] Determining the current internal resistance of the battery according to the electrochemical impedance spectrum of the battery; wherein the electrochemical impedance spectrum is determined according to the method for determining the electrochemical impedance spectrum of the battery of the electronic device in the first aspect;

[0012] Determine the current maximum dischargeable total capacity of the battery based on the current internal resistance;

[0013] A current battery state of health of the battery is determined based on the current maximum dischargeable total capacity and the initial maximum dischargeable total capacity of the battery.

[0014] In a third aspect, an embodiment of the present application provides a device for determining an electrochemical impedance spectrum of a battery of an electronic device, the device comprising:

[0015] An acquisition module, configured to pulse charge the battery of the electronic device based on a preset pulse current and acquire an electrical characteristic curve of the battery;

[0016] A first curve reconstruction module is used to reconstruct the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve;

[0017] a determination module, configured to determine the battery's electrical characteristic frequency domain coefficients based on the reconstructed electrical characteristic curve; and

[0018] The electrochemical impedance spectrum of the battery is determined based on the electrical characteristic frequency domain coefficients.

[0019] In a fourth aspect, an embodiment of the present application provides a device for determining a battery health status of a battery of an electronic device, the device comprising:

[0020] a second determination module, configured to determine the current internal resistance of the battery according to the electrochemical impedance spectrum of the battery; wherein the electrochemical impedance spectrum is determined by the device for determining the electrochemical impedance spectrum of the battery of the electronic device as in the third aspect; and

[0021] Determining the current maximum dischargeable total capacity of the battery based on the current internal resistance; and

[0022] A current battery state of health of the battery is determined based on the current maximum dischargeable total capacity and the initial maximum dischargeable total capacity of the battery.

[0023] In a fifth aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method of the first aspect and / or the second aspect are implemented.

[0024] In a sixth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method of the first aspect and / or the second aspect are implemented.

[0025] In the seventh aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps of the method of the first aspect and / or the second aspect.

[0026] In an eighth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method of the first aspect and / or the second aspect.

[0027] In an embodiment of the present application, the electrical characteristic parameters of the battery under pulse charging conditions are collected during the process of pulse charging the battery. By interpolation, the data points on the electrical characteristic curve are interpolated, thereby reconstructing the electrical characteristic curve with a low sampling frequency, obtaining a reconstructed electrical characteristic curve with more sampling points, thereby obtaining an electrochemical impedance spectrum (EIS) at a higher sampling frequency, thereby realizing online estimation of the electrochemical impedance spectrum of the battery at the electronic device end. The electrochemical impedance spectrum can fully explore the internal characteristics of the battery, thereby achieving higher and more accurate battery management and accurate estimation of the battery state. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A flow chart illustrating a method for determining an electrochemical impedance spectrum of a battery of an electronic device according to some embodiments of the present application;

[0029] Figure 2 A schematic diagram showing electrical characteristic curves of some embodiments of the present application;

[0030] Figure 3 A schematic diagram showing electrical characteristic curves of some embodiments of the present application;

[0031] Figure 4 A schematic diagram showing a first curve segment of some embodiments of the present application;

[0032] Figure 5 A schematic diagram showing a second curved line segment of some embodiments of the present application is shown;

[0033] Figure 6 A schematic diagram showing a reconstructed voltage curve according to some embodiments of the present application;

[0034] Figure 7 A schematic diagram of a curve segment of a current curve at the start of a pulse current is shown in some embodiments of the present application;

[0035] Figure 8 A schematic diagram of a curve segment of a current curve of some embodiments of the present application at the moment when the pulse current stops is shown;

[0036] Figure 9 A schematic diagram showing a reconstructed current curve according to some embodiments of the present application;

[0037] Figure 10 shows a waveform diagram of electrochemical impedance spectroscopy of some embodiments of the present application;

[0038] Figure 11Some logic diagrams for determining electrochemical impedance spectra of the present application are shown;

[0039] Figure 12 A flow chart showing a method for determining the battery health status of batteries of some electronic devices of the present application;

[0040] Figure 13 A schematic diagram showing the linear relationship between the maximum dischargeable total capacity and the internal resistance of the battery of some embodiments of the present application is shown;

[0041] Figure 14 A schematic diagram showing aging curves of some embodiments of the present application;

[0042] Figure 15 A structural block diagram showing an apparatus for determining an electrochemical impedance spectrum of a battery of an electronic device according to some embodiments of the present application is shown;

[0043] Figure 16 A structural block diagram showing a device for determining a battery health status of a battery of an electronic device according to some embodiments of the present application is shown;

[0044] Figure 17 shows a structural block diagram of an electronic device according to an embodiment of the present application;

[0045] Figure 18 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application. DETAILED DESCRIPTION

[0046] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0047] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0048] The following, in conjunction with the accompanying drawings, describes in detail the electrochemical impedance spectroscopy and battery health status determination method and determination device provided in the embodiments of the present application through specific embodiments and their application scenarios.

[0049] In some embodiments of the present application, a method for determining the electrochemical impedance spectrum of a battery in an electronic device is provided. Electrochemical impedance spectroscopy is a non-destructive and effective electrochemical testing tool, and is an important means of measuring battery characteristics and estimating battery status. By utilizing impedance spectrum information in different frequency bands to model and identify parameters of lithium-ion batteries, it is possible to fully explore the internal characteristics of the battery, better implement effective battery management, and accurately estimate the battery status.

[0050] Traditionally, electrochemical impedance spectroscopy (EIS) identification requires proprietary equipment. There are two main methods for online EIS identification. The first involves adding an AC excitation source to the positive and negative terminals of the battery, applying active AC excitation at varying frequencies to the battery to obtain the AC response, thereby calculating the EIS. The second, more complex, method involves performing time-frequency conversion on the battery's square wave to calculate the corresponding current and voltage sinusoidal function curves, thereby estimating the battery's EIS.

[0051] In the time-frequency conversion method, the accuracy of the estimated electrochemical impedance spectrum is greatly affected by the sampling frequency, which is particularly obvious in the high-frequency region. The higher the sampling frequency, the higher the accuracy of the obtained electrochemical impedance spectrum. On the electronic device side, the maximum sampling frequencies for battery voltage or battery current are generally 1Hz, 2Hz, 5Hz and 10Hz, and high-frequency sampling can only be enabled under specific conditions. Even with the highest frequency of 10Hz sampling, after time-frequency conversion, only the impedance between 0.01Hz and 1Hz can be obtained, and the impedance obtained in the range of 0.5Hz to 1Hz is less accurate. This makes it impossible to accurately obtain the electrochemical impedance spectrum of the battery through high-frequency sampling on the electronic device side.

[0052] In response to the above problems, the present invention provides a method for determining the electrochemical impedance spectrum of a battery of an electronic device. Figure 1 A flow chart showing a method for determining the electrochemical impedance spectrum of a battery of an electronic device in some embodiments of the present application is shown. Figure 1 As shown, the determination method includes:

[0053] Step 102 : pulse charging the battery of the electronic device based on a preset pulse current, and collecting an electrical characteristic curve of the battery.

[0054] In an embodiment of the present application, the pulse period of the preset pulse current ranges from 10s to 100s. Exemplarily, the pulse period of the pulse current is 60s. Exemplarily, the preset pulse current is a pulse current of 0.1C to 0.5C. Exemplarily, the preset pulse current is a pulse current of 0.3C. The electronic device collects the electrical characteristic curve of the battery at a sampling frequency of 10 Hz or less.

[0055] For example, Figure 2 and Figure 3 Schematic diagram showing the electrical characteristic curves of some embodiments of the present application, such as Figure 2 As shown, Figure 2 The curve in is the current curve collected by the analog to digital converter (ADC) of the electronic device. Figure 3 As shown, Figure 3 The curve in FIG is the voltage curve collected by the ADC of the electronic device.

[0056] Step 104 : reconstructing the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve.

[0057] In the embodiments of this application, the sampling frequency of electronic devices is generally no greater than 10Hz, which cannot guarantee the accuracy of EIS estimation at all frequencies. To address this, this application uses interpolation to reconstruct the collected raw electrical characteristic curves. This interpolation method reconstructs the original 10Hz sampling frequency data into 10,000Hz data, thereby achieving high-precision EIS estimation.

[0058] Exemplarily, the above interpolation methods include proximity interpolation, spline interpolation, cubic polynomial interpolation, Hermite polynomial interpolation, piecewise linear interpolation, and the like.

[0059] Step 106 : Determine the battery's electrical characteristic frequency domain coefficient based on the reconstructed electrical characteristic curve.

[0060] In the embodiment of the present application, the electrical characteristic curve is refitted based on the interpolated electrical characteristic data to obtain a reconstructed electrical characteristic curve. For example, the reconstructed electrical characteristic curve is equivalent to 10000 Hz sampling data.

[0061] Step 108 : determining the electrochemical impedance spectrum of the battery according to the electrical characteristic frequency domain coefficient.

[0062] In an embodiment of the present application, based on the current data and voltage data in the reconstructed electrical characteristic curve, frequency domain conversion is performed using a wavelet function or a fast Fourier transform function, and then the EIS at a specific frequency is obtained by the ratio of the conversion function coefficients, that is, the electrochemical impedance spectrum of the battery is obtained.

[0063] In the embodiment of the present application, the electrical characteristic parameters of the battery under pulse charging conditions are collected during the pulse charging process of the battery. By interpolation, the data points on the electrical characteristic curve are interpolated, thereby reconstructing the electrical characteristic curve with a low sampling frequency, obtaining a reconstructed electrical characteristic curve with more sampling points, and obtaining an electrochemical impedance spectrum (EIS) at a higher sampling frequency, thereby realizing online estimation of the electrochemical impedance spectrum of the battery at the electronic device end. The electrochemical impedance spectrum can fully explore the internal characteristics of the battery, thereby realizing higher and more accurate battery management and accurate estimation of the battery state.

[0064] In some embodiments of the present application, the electrical characteristic curve includes a voltage curve; the voltage curve includes a first curve segment, a second curve segment, and a third curve segment; the segment lengths of the first curve segment and the second curve segment are associated with a preset time length, and the third curve segment is a curve segment in the voltage curve other than the first curve segment and the second curve segment;

[0065] The electrical characteristic curve is reconstructed by interpolation to obtain a reconstructed electrical characteristic curve, including:

[0066] The first curve segment and the second curve segment are reconstructed by a proximity interpolation method, and the third curve segment is reconstructed by a spline interpolation method to obtain a reconstructed voltage curve.

[0067] In the embodiment of the present application, the electrical characteristic curve specifically includes a voltage curve. When reconstructing the voltage curve, a spline interpolation function and a proximity interpolation method are used in different data segments to define the voltage curve as a piecewise polynomial. The voltage curve is defined to include a first curve segment, a second curve segment, and a third curve segment. The first curve segment is the curve segment at the start of the pulse current, the second curve segment is the curve segment at the stop of the pulse current, and the third curve segment is the curve segment at other times.

[0068] For example, Figure 3 As shown, the first curve segment 302 corresponds to the rising edge of the voltage curve, the second curve segment 304 corresponds to the falling edge of the voltage curve, and the third curve segment 306 is the curve segment of the other part.

[0069] When reconstructing the curve, the proximity interpolation method is used to reconstruct the curve at the moment before the pulse occurs and the moment after the pulse occurs, that is, within the first curve segment. For example, Figure 4 A schematic diagram of a first curve segment of some embodiments of the present application is shown, such as Figure 4 As shown, for the voltage data in the first curve segment 302, the nearest interpolation method is used for interpolation. When reconstructing the electrical characteristic curve by the nearest interpolation method, the target data point is determined in the electrical characteristic curve; wherein the target data point is the data point with the smallest time interval in the electrical characteristic curve; and the target data point is used as the new value to reconstruct the curve. The purpose of this process is to ensure that the instantaneous voltage rise caused by the ohmic internal resistance can be accurately reflected after interpolation. For the voltage data in the other third curve segment 306, the spline interpolation method is used for interpolation, with the aim of better restoring the measured value of the voltage curve in each cycle. Due to the "convexity-preserving" characteristic of the spline interpolation function, the reconstructed voltage curve can still maintain smoothness on the basis of numerical accuracy.

[0070] Similarly, at the moment before the pulse stops and the moment after the pulse stops, that is, in the second curve segment, the proximity interpolation method is also used. For example, Figure 5 A schematic diagram of the second curve segment of some embodiments of the present application is shown, such as Figure 5 As shown, the voltage data in the second curve segment 304 is interpolated using the proximity interpolation method, and the voltage data in the third curve segment 306 is interpolated using the sampling spline interpolation method.

[0071] This application reconstructs the collected voltage curve and uses spline interpolation function and proximity interpolation method in different time periods to define the voltage curve as a piecewise polynomial. This ensures that the instantaneous voltage drop caused by the ohmic internal resistance can be reflected after interpolation, and can better "maintain convexity", maintain smoothness, and restore the measured value of the voltage curve in each cycle.

[0072] In some embodiments of the present application, the midpoint of the first curve segment corresponds to the start time of the pulse current of the preset pulse current; and / or, the midpoint of the second curve segment corresponds to the stop time of the pulse current of the preset pulse current; and / or, the range of the preset time length is: 100ms to 300ms.

[0073] In the embodiments of this application, Figure 4 As shown, for the first curve segment 302, any time between 60.0s and 60.1s can be used as the interpolation switching point. The proximity interpolation method will automatically locate the midpoint during actual operation, that is, the midpoint of the first curve segment corresponds to the pulse current start time of the preset pulse current.

[0074] like Figure 5 As shown, for the second curve segment 304, any time between 120.0s and 120.1s can be used as the interpolation switching point. The proximity interpolation method will automatically locate the midpoint during actual operation, that is, the midpoint of the second curve segment corresponds to the pulse current stopping time of the preset pulse current.

[0075] The first curve segment is the curve segment of the voltage curve within a preset duration. The preset duration ranges from 100ms to 300ms. For example, taking the preset duration as 100ms and defining the pulse current start time as t0, the first curve segment is the curve segment within the time range [t0-100ms, t0+100ms].

[0076] Similarly, the pulse current stopping moment is defined as t1, and the second curve segment is the curve segment within the time range of [t1-100ms, t1+100ms].

[0077] Figure 6 Schematic diagram showing the reconstructed voltage curves of some embodiments of the present application, such as Figure 6 As shown, the reconstructed red voltage curve basically coincides with the blue original voltage curve, and the measured value of the voltage curve in each cycle can be accurately restored.

[0078] In some embodiments of the present application, the electrical characteristic curve includes a current curve; and reconstructing the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve includes:

[0079] The current curve is reconstructed by the proximity interpolation method to obtain the reconstructed current curve.

[0080] In the embodiments of this application, Figure 2 As shown, compared with the voltage curve, the pulse current curve is relatively stable, so the collected current curve is also relatively stable, and the original characteristics of the current curve can be accurately restored by the proximity interpolation method. Figure 7 FIG1 shows a schematic diagram of a curve segment of a current curve of some embodiments of the present application at the start of a pulse current. At the start of the pulse current, the reconstructed current curve is as follows: Figure 7 shown.

[0081] akin, Figure 8 The schematic diagram of the curve segment of the current curve of some embodiments of the present application at the moment when the pulse current stops is shown. At the moment when the pulse current stops, at the end stage of the pulse current, the reconstructed current curve is as follows: Figure 8 shown.

[0082] Figure 9 Schematic diagram showing the reconstructed current curve of some embodiments of the present application, such as Figure 9As shown, the reconstructed red current curve basically coincides with the blue original current curve, and the measured value of the current curve in each cycle can be accurately restored.

[0083] This application can accurately estimate the EIS of batteries.

[0084] In some embodiments of the present application, the current curve before reconstruction is a current curve at a first sampling frequency, and the current after reconstruction is a current curve at an equivalent second sampling frequency; wherein the first sampling frequency ranges from 1 Hz to 100 Hz; and the second sampling frequency ranges from 1000 Hz to 100,000 Hz.

[0085] In the embodiment of the present application, the first sampling frequency is exemplarily the original sampling frequency. Exemplarily, the first sampling frequency is 10 Hz. The second sampling frequency is the equivalent sampling frequency of the reconstructed curve. Exemplarily, the second sampling frequency is 10,000 Hz. The originally stable current curve is reconstructed using a proximity interpolation method, and the current curve at the 10 Hz sampling frequency is reconstructed into current data at 10,000 Hz, thereby achieving an accurate estimation of the battery EIS.

[0086] In some embodiments of the present application, the reconstructed electrical characteristic curve includes a reconstructed current curve and a reconstructed voltage curve, and the electrical characteristic frequency domain coefficient includes a current frequency domain coefficient and a voltage frequency domain coefficient;

[0087] Based on the reconstructed electrical characteristic curve, determine the battery's electrical characteristic frequency domain coefficients, including:

[0088] determining current data based on the reconstructed current curve, and determining voltage data based on the reconstructed voltage curve;

[0089] Perform frequency domain conversion on the current data and voltage data to obtain the current frequency domain coefficient and the voltage frequency domain coefficient.

[0090] In the present embodiment, the reconstructed current and voltage curves are converted to the frequency domain using transfer functions, and the EIS (electrochemical impedance spectroscopy) at a specific frequency is obtained by comparing the transfer functions. The transfer function can be a wavelet function or a fast Fourier transform function.

[0091] Taking frequency domain conversion by wavelet function as an example, the following formulas (1) and (2) show the wavelet conversion function:

[0092]

[0093] The wavelet coefficients can be obtained from the above formulas (1) and (2), and the wavelet coefficients are shown in formula (3):

[0094]

[0095] In formula (1), formula (2) and formula (3), ψ(t) is the wavelet transform function, t is the sampling time, f(t) is the signal input, including current signal input or voltage signal input, a is the scale parameter, b is the time parameter, and e is the natural base, f b is the Gaussian function attenuation coefficient, f c is the center frequency of the mother wavelet, is the wavelet coefficient, and i is the complex number identifier.

[0096] The voltage frequency domain coefficient and the current frequency domain coefficient are obtained respectively through the above wavelet function, and the electrochemical impedance spectroscopy EIS can be obtained according to the ratio of the voltage frequency domain coefficient and the current frequency domain coefficient.

[0097] For example, Figure 10 The waveform diagrams of electrochemical impedance spectroscopy of some embodiments of the present application are shown in FIG. Figure 10 As shown in the figure, Zreal is the real part value, Zimag is the imaginary part value, the circle is the EIS obtained by time-frequency conversion based on the reconstructed electrical characteristic curve, the curve is the actual measured EIS, and the star mark is the EIS obtained by time-frequency conversion based on the original electrical characteristic curve. It can be clearly seen that the reconstructed electrical characteristic curve can obtain EIS at more frequencies, and it is consistent with the actual measured EIS.

[0098] For example, Figure 11 Some logic diagrams for determining electrochemical impedance spectra of the present application are shown, such as Figure 11 As shown, a time-frequency conversion function is selected, and the current signal and voltage signal are reconstructed respectively. The voltage frequency domain conversion and the current frequency domain conversion are performed by the time-frequency conversion function to obtain the voltage frequency domain coefficient and the current frequency domain coefficient respectively, and finally the electrochemical impedance spectrum is obtained.

[0099] For example, take the electronic device scenario as an example. The electronic device is plugged into a charger to charge the battery. After 60 seconds, the charging is interrupted by the charger IC control for 60 seconds, and then normal charging is continued. During this period, the ADC sampling will send the real-time collected current and voltage data to the driver chip according to a sampling period of 0.1s. At this time, the driver will recognize the current data and voltage data under a pulse charging condition with a period of 120s, and simultaneously process the reconstruction task of the current data and voltage data. That is, the spline function is used to convert the current data and voltage data of the 0.1s sampling period into the current data and voltage data equivalent to the 0.001s sampling period, and then according to Figure 11 The logic shown uses a wavelet transform algorithm to calculate the battery impedance, thereby obtaining EIS in the frequency range of 0.01 Hz to 1000 Hz.

[0100] In some embodiments of the present application, a method for determining the battery health status of a battery of an electronic device is provided. Figure 12 A flow chart showing a method for determining the battery health status of batteries of some electronic devices that are very young in nature, such as Figure 12 As shown, the determination method includes:

[0101] Step 1202, determining the current internal resistance of the battery based on the electrochemical impedance spectroscopy of the battery;

[0102] The electrochemical impedance spectrum is determined according to the method for determining the electrochemical impedance spectrum of the battery of the electronic device in any of the above embodiments;

[0103] Step 1204: determining the current maximum dischargeable total capacity of the battery based on the current internal resistance;

[0104] Step 1206 : Determine the current battery health status of the battery based on the current maximum dischargeable total capacity and the initial maximum dischargeable total capacity of the battery.

[0105] In the embodiment of the present application, after obtaining the electrochemical impedance spectrum, the electrochemical impedance spectrum can be combined with the battery state of health (SOH) curve to reconstruct the estimation and correction. After obtaining the electrochemical impedance spectrum, the real part of the impedance point at a frequency of 1 Hz in the electrochemical impedance spectrum is defined as the current internal resistance Rct of the battery.

[0106] Figure 13 A schematic diagram showing the linear relationship between the maximum dischargeable total capacity of the battery and the internal resistance of the battery in some embodiments of the present application is shown. Figure 13 As shown, the points are experimental test values, and the curve is the fitting curve. The initial maximum discharge capacity of the battery can be calibrated in the laboratory stage, and then the following is obtained: Figure 13 The relationship shown in the figure is then fitted to obtain the formula (4) that can reflect the relationship between the maximum discharge capacity Qmax and the internal resistance Rct:

[0107] Qmax=8.01-32.79×Rct(4)

[0108] By analyzing the linear relationship between the maximum discharge capacity and the internal resistance, the current internal resistance obtained based on the electrochemical impedance spectroscopy is substituted into formula (4) to obtain the current maximum discharge capacity of the battery.

[0109] The current state of health (SOH) of the battery can be obtained by dividing the current maximum discharge capacity calculated in the above step by the initial maximum discharge capacity recorded when the battery leaves the factory.

[0110] The embodiment of the present application controls the electronic device to determine the electrochemical impedance spectrum of the battery online in real time, and calculates the actual current internal resistance of the battery in real time, thereby accurately calculating the battery health status and achieving more accurate battery status management.

[0111] In some embodiments of the present application, after determining the current battery health state of the battery, the determination method further includes:

[0112] The current internal resistance and the current battery health status are stored accordingly to obtain the corresponding aging curve of the battery;

[0113] The aging curve is reconstructed by spline interpolation method to obtain the reconstructed aging curve.

[0114] In an embodiment of the present application, in the use scenario of an electronic device, during the battery's charge and discharge cycles, the steps of determining the current internal resistance and current battery health status are repeatedly performed, and the corresponding values are stored in a historical record. By repeating these steps throughout the battery's life cycle, the corresponding relationship between the battery health status and internal resistance over the entire battery life cycle can be obtained.

[0115] For example, when the battery health state SOH changes from 100% to 50%, the corresponding battery internal resistance Rct is recorded to obtain a battery aging curve. The data sampling points in the battery aging curve are shown in Table 1 below:

[0116] Table 1

[0117] SOH 100 90 80 70 60 50 Rct 0.026 0.045 0.062 0.099 0.115 0.139

[0118] The battery aging curve is reconstructed by spline interpolation to obtain more detailed SOH and Rct information. The equivalent data sampling points in the reconstructed battery aging curve are shown in Table 2 below:

[0119] Table 2

[0120]

[0121]

[0122] For example, Figure 14 Schematic diagram showing the aging curves of some embodiments of the present application, such as Figure 14 As shown in the figure, in the original aging curve, the circular marks are the sampling points of the original aging curve. In the reconstructed aging curve, the cross-shaped marks are the equivalent sampling points on the reconstructed aging curve. Figure 14 It can be seen that the reconstructed aging curve is smoother, which can be closer to the actual aging of the battery and provide data support for battery management.

[0123] The method for determining the electrochemical impedance spectrum of a battery for an electronic device provided in an embodiment of the present application may be performed by a device for determining the electrochemical impedance spectrum of a battery for an electronic device. In the embodiment of the present application, the device for determining the electrochemical impedance spectrum of a battery for an electronic device is used as an example to illustrate the method for determining the electrochemical impedance spectrum of a battery for an electronic device.

[0124] In some embodiments of the present application, a device for determining the electrochemical impedance spectrum of a battery of an electronic device is provided. Figure 15 A structural block diagram of a device for determining the electrochemical impedance spectrum of a battery of an electronic device in some embodiments of the present application is shown. Figure 15 As shown, the determining device 1500 includes:

[0125] The acquisition module 1502 is configured to pulse charge the battery of the electronic device based on a preset pulse current and acquire an electrical characteristic curve of the battery;

[0126] A first curve reconstruction module 1504 is configured to reconstruct the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve;

[0127] The first determining module 1506 is configured to determine the electrical characteristic frequency domain coefficients of the battery based on the reconstructed electrical characteristic curve; and determine the electrochemical impedance spectrum of the battery according to the electrical characteristic frequency domain coefficients.

[0128] In an embodiment of the present application, the electrical characteristic parameters of the battery under pulse charging conditions are collected during the process of pulse charging the battery. By interpolation, the data points on the electrical characteristic curve are interpolated, thereby reconstructing the electrical characteristic curve with a low sampling frequency, obtaining a reconstructed electrical characteristic curve with more sampling points, thereby obtaining an electrochemical impedance spectrum (EIS) at a higher sampling frequency, thereby realizing online estimation of the electrochemical impedance spectrum of the battery at the electronic device end. The electrochemical impedance spectrum can fully explore the internal characteristics of the battery, thereby achieving higher and more accurate battery management and accurate estimation of the battery state.

[0129] In some embodiments of the present application, the electrical characteristic curve includes a voltage curve; the voltage curve includes a first curve segment, a second curve segment, and a third curve segment; the segment lengths of the first curve segment and the second curve segment are associated with a preset time length, and the third curve segment is a curve segment in the voltage curve other than the first curve segment and the second curve segment;

[0130] The first curve reconstruction module is further used to reconstruct the first curve segment and the second curve segment by using a proximity interpolation method, and to reconstruct the third curve segment by using a spline interpolation method, to obtain a reconstructed voltage curve.

[0131] This application reconstructs the collected voltage curve and uses spline interpolation function and proximity interpolation method in different time periods to define the voltage curve as a piecewise polynomial. This ensures that the instantaneous voltage drop caused by the ohmic internal resistance can be reflected after interpolation, and can better "maintain convexity", maintain smoothness, and restore the measured value of the voltage curve in each cycle.

[0132] In some embodiments of the present application, the midpoint of the first curve segment corresponds to the start time of the pulse current of the preset pulse current; and / or, the midpoint of the second curve segment corresponds to the stop time of the pulse current of the preset pulse current; and / or, the range of the preset time length is: 100ms to 300ms.

[0133] In an embodiment of the present application, the proximity interpolation method will automatically locate the midpoint during actual operation, that is, the midpoint of the first curve segment corresponds to the start time of the pulse current of the preset pulse current, and the midpoint of the second curve segment corresponds to the stop time of the pulse current of the preset pulse current. The first curve segment is a curve segment of the voltage curve within a preset time length. The range of the preset time length is 100ms to 300ms. For example, taking the preset time length of 100ms as an example, the start time of the pulse current is defined as t0, then the first curve segment is a curve segment within the time range of [t0-100ms, t0+100ms]. Similarly, the stop time of the pulse current is defined as t1, then the second curve segment is a curve segment within the time range of [t1-100ms, t1+100ms].

[0134] In some embodiments of the present application, the electrical characteristic curve includes a current curve; the first curve reconstruction module is further configured to reconstruct the current curve by using a proximity interpolation method to obtain a reconstructed current curve.

[0135] This application can accurately estimate the EIS of batteries.

[0136] In some embodiments of the present application, the current curve before reconstruction is a current curve at a first sampling frequency, and the current after reconstruction is a current curve at an equivalent second sampling frequency; wherein the first sampling frequency ranges from 1 Hz to 100 Hz; and the second sampling frequency ranges from 1000 Hz to 100,000 Hz.

[0137] The originally smooth current curve is reconstructed through the nearest interpolation method, and the current curve at the 10Hz sampling frequency is reconstructed into 10000Hz current data, thereby achieving accurate estimation of the battery EIS.

[0138] In some embodiments of the present application, the reconstructed electrical characteristic curve includes a reconstructed current curve and a reconstructed voltage curve, and the electrical characteristic frequency domain coefficient includes a current frequency domain coefficient and a voltage frequency domain coefficient;

[0139] The determination module is further configured to determine current data based on the reconstructed current curve, and determine voltage data based on the reconstructed voltage curve;

[0140] The determination device also includes: a conversion module, which is used to perform frequency domain conversion on the current data and the voltage data to obtain current frequency domain coefficients and voltage frequency domain coefficients.

[0141] The voltage frequency domain coefficient and the current frequency domain coefficient are obtained respectively through the above wavelet function, and the electrochemical impedance spectroscopy EIS can be obtained according to the ratio of the voltage frequency domain coefficient and the current frequency domain coefficient.

[0142] In some embodiments of the present application, a device for determining the battery health status of a battery of an electronic device is provided. Figure 16 A structural block diagram of a device for determining the battery health status of a battery of an electronic device in some embodiments of the present application is shown. Figure 16 As shown, the determining device 1600 includes:

[0143] The second determination module 1602 is configured to determine the current internal resistance of the battery based on the electrochemical impedance spectrum of the battery; wherein the electrochemical impedance spectrum is determined by a device for determining the electrochemical impedance spectrum of a battery of an electronic device as in any of the above embodiments; and, based on the current internal resistance, determine the current maximum dischargeable total capacity of the battery; and, based on the current maximum dischargeable total capacity and the initial maximum dischargeable total capacity of the battery, determine the current battery health status of the battery.

[0144] The embodiment of the present application controls the electronic device to determine the electrochemical impedance spectrum of the battery online in real time, and calculates the actual current internal resistance of the battery in real time, thereby accurately calculating the battery health status and achieving more accurate battery status management.

[0145] In some embodiments of the present application, the determining device further includes:

[0146] The storage module is used to store the current internal resistance and the current battery health status to obtain the corresponding aging curve of the battery;

[0147] The second curve reconstruction module is used to reconstruct the aging curve by using a spline interpolation method to obtain a reconstructed aging curve.

[0148] The aging curve reconstructed in this application is smoother, which can be closer to the actual aging of the battery and provide data support for battery management.

[0149] The determination device of the electrochemical impedance spectrum of the battery of the electronic device in the embodiment of the present application can be an electronic device, or it can be a component in the electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal, or it can be other devices except the terminal. Exemplary, electronic equipment can be a mobile phone, a tablet computer, a laptop computer, a palmtop computer, a vehicle-mounted electronic device, a mobile Internet device (Mobile Internet Device, MID), augmented reality (augmentedreality, AR) / virtual reality (virtual reality, VR) equipment, a robot, a wearable device, a super mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personaldigital assistant, PDA), etc., and can also be a server, a network attached storage (Network AttachedStorage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., and the embodiment of the present application is not specifically limited.

[0150] The device for determining the electrochemical impedance spectrum of the battery of the electronic device in the embodiments of the present application can be a device having an operating system. The operating system can be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiments of the present application.

[0151] The device for determining the electrochemical impedance spectrum of a battery of an electronic device provided in the embodiment of the present application can implement each process implemented in the above method embodiment, and will not be described again here to avoid repetition.

[0152] Optionally, an embodiment of the present application further provides an electronic device, Figure 17 FIG. 1 shows a structural block diagram of an electronic device according to an embodiment of the present application. Figure 17 As shown, the electronic device 1700 includes a processor 1702, a memory 1704, and a program or instruction stored in the memory 1704 and executable on the processor 1702. When the program or instruction is executed by the processor 1702, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, they will not be described here.

[0153] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile electronic devices and non-mobile electronic devices.

[0154] Figure 18 A schematic diagram of the hardware structure of an electronic device implementing an embodiment of the present application.

[0155] The electronic device 1800 includes but is not limited to: a radio frequency unit 1801, a network module 1802, an audio output unit 1803, an input unit 1804, a sensor 1805, a display unit 1806, a user input unit 1807, an interface unit 1808, a memory 1809 and a processor 1810 and other components.

[0156] Those skilled in the art will understand that the electronic device 1800 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 1810 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 18 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0157] Among them, processor 1810 is used to pulse charge the battery of the electronic device based on a preset pulse current and collect the electrical characteristic curve of the battery; reconstruct the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve; determine the electrical characteristic frequency domain coefficient of the battery based on the reconstructed electrical characteristic curve; and determine the electrochemical impedance spectrum of the battery based on the electrical characteristic frequency domain coefficient.

[0158] In an embodiment of the present application, the electrical characteristic parameters of the battery under pulse charging conditions are collected during the process of pulse charging the battery. By interpolation, the data points on the electrical characteristic curve are interpolated, thereby reconstructing the electrical characteristic curve with a low sampling frequency, obtaining a reconstructed electrical characteristic curve with more sampling points, thereby obtaining an electrochemical impedance spectrum (EIS) at a higher sampling frequency, thereby realizing online estimation of the electrochemical impedance spectrum of the battery at the electronic device end. The electrochemical impedance spectrum can fully explore the internal characteristics of the battery, thereby achieving higher and more accurate battery management and accurate estimation of the battery state.

[0159] Optionally, the electrical characteristic curve includes a voltage curve; the voltage curve includes a first curve segment, a second curve segment, and a third curve segment; the segment lengths of the first curve segment and the second curve segment are associated with a preset time length, and the third curve segment is a curve segment in the voltage curve other than the first curve segment and the second curve segment;

[0160] The processor 1810 is further configured to reconstruct the first curve segment and the second curve segment by using a proximity interpolation method, and reconstruct the third curve segment by using a spline interpolation method, to obtain a reconstructed voltage curve.

[0161] This application reconstructs the collected voltage curve and uses spline interpolation function and proximity interpolation method in different time periods to define the voltage curve as a piecewise polynomial. This ensures that the instantaneous voltage drop caused by the ohmic internal resistance can be reflected after interpolation, and can better "maintain convexity", maintain smoothness, and restore the measured value of the voltage curve in each cycle.

[0162] Optionally, the midpoint of the first curve segment corresponds to the start time of the pulse current of the preset pulse current; and / or, the midpoint of the second curve segment corresponds to the stop time of the pulse current of the preset pulse current; and / or, the range of the preset time length is: 100ms to 300ms.

[0163] In the embodiment of the present application, the first curve segment is a curve segment of the voltage curve within a preset duration. The preset duration ranges from 100ms to 300ms. For example, taking the preset duration of 100ms as an example, the pulse current start time is defined as t0, and the first curve segment is a curve segment within the time range [t0-100ms, t0+100]. Similarly, the pulse current stop time is defined as t1, and the second curve segment is a curve segment within the time range [t1-100ms, t1+100].

[0164] Optionally, the electrical characteristic curve includes a current curve; the processor 1810 is further configured to reconstruct the current curve by using a proximity interpolation method to obtain a reconstructed current curve.

[0165] This application can accurately estimate the EIS of batteries.

[0166] Optionally, the current curve before reconstruction is a current curve at a first sampling frequency, and the current after reconstruction is a current curve at an equivalent second sampling frequency; wherein the first sampling frequency ranges from 1 Hz to 100 Hz; and the second sampling frequency ranges from 1000 Hz to 100000 Hz.

[0167] The originally smooth current curve is reconstructed through the nearest interpolation method, and the current curve at the 10Hz sampling frequency is reconstructed into 10000Hz current data, thereby achieving accurate estimation of the battery EIS.

[0168] Optionally, the reconstructed electrical characteristic curve includes a reconstructed current curve and a reconstructed voltage curve, and the electrical characteristic frequency domain coefficient includes a current frequency domain coefficient and a voltage frequency domain coefficient;

[0169] The processor 1810 is further configured to determine current data based on the reconstructed current curve, and determine voltage data based on the reconstructed voltage curve; and perform frequency domain conversion on the current data and the voltage data to obtain current frequency domain coefficients and voltage frequency domain coefficients.

[0170] The voltage frequency domain coefficient and the current frequency domain coefficient are obtained respectively through the above wavelet function, and the electrochemical impedance spectroscopy EIS can be obtained according to the ratio of the voltage frequency domain coefficient and the current frequency domain coefficient.

[0171] Optionally, processor 1810 is further used to determine the current internal resistance of the battery based on the electrochemical impedance spectroscopy; and, based on the current internal resistance, determine the current maximum dischargeable total capacity of the battery; and, based on the current maximum dischargeable total capacity and the initial maximum dischargeable total capacity of the battery, determine the current battery health status of the battery.

[0172] The embodiment of the present application controls the electronic device to determine the electrochemical impedance spectrum of the battery online in real time, and calculates the actual current internal resistance of the battery in real time, thereby accurately calculating the battery health status and achieving more accurate battery status management.

[0173] Optionally, the processor 1810 is further configured to store the current internal resistance and the current battery health status correspondingly to obtain an aging curve corresponding to the battery; and reconstruct the aging curve by spline interpolation to obtain a reconstructed aging curve.

[0174] The aging curve reconstructed in this application is smoother, which can be closer to the actual aging of the battery and provide data support for battery management.

[0175] It should be understood that in an embodiment of the present application, the input unit 1804 may include a graphics processing unit (GPU) 18041 and a microphone 18042, and the graphics processor 18041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 1806 may include a display panel 18061, and the display panel 18061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 1807 includes a touch panel 18071 and at least one of other input devices 18072. The touch panel 18071 is also called a touch screen. The touch panel 18071 may include two parts: a touch detection device and a touch controller. Other input devices 18072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be repeated here.

[0176] The memory 1809 can be used to store software programs and various data. The memory 1809 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 1809 may include a volatile memory or a non-volatile memory, or the memory 1809 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 1809 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0177] Processor 1810 may include one or more processing units. Optionally, processor 1810 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 1810.

[0178] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the above-mentioned method embodiment are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0179] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0180] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0181] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0182] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the above-mentioned method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0183] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0184] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0185] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A method for determining the electrochemical impedance spectrum of a battery of an electronic device, characterized in that: The determination method includes: Performing pulse charging on a battery of the electronic device based on a preset pulse current, and collecting an electrical characteristic curve of the battery; reconstructing the electrical characteristic curve by an interpolation method to obtain a reconstructed electrical characteristic curve; Determining an electrical characteristic frequency domain coefficient of the battery based on the reconstructed electrical characteristic curve; The electrochemical impedance spectrum of the battery is determined according to the electrical characteristic frequency domain coefficient.

2. The determination method according to claim 1, characterized in that The electrical characteristic curve includes a voltage curve; the voltage curve includes a first curve segment, a second curve segment, and a third curve segment; the segment lengths of the first curve segment and the second curve segment are associated with a preset time length, and the third curve segment is a curve segment of the voltage curve other than the first curve segment and the second curve segment; The reconstructing the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve includes: The first curve segment and the second curve segment are reconstructed by using a proximity interpolation method, and the third curve segment is reconstructed by using a spline interpolation method to obtain a reconstructed voltage curve.

3. The determination method according to claim 2, characterized in that: The midpoint of the first curve segment corresponds to the pulse current starting time of the preset pulse current; and / or The midpoint of the second curve segment corresponds to the pulse current stopping moment of the preset pulse current; and / or The preset duration ranges from 100ms to 300ms.

4. The determination method according to claim 1, characterized in that The electrical characteristic curve includes a current curve; and reconstructing the electrical characteristic curve by interpolation to obtain a reconstructed electrical characteristic curve includes: The current curve is reconstructed by using a proximity interpolation method to obtain a reconstructed current curve.

5. The determination method according to claim 1, characterized in that: The reconstructed electrical characteristic curve includes a reconstructed current curve and a reconstructed voltage curve, and the electrical characteristic frequency domain coefficient includes a current frequency domain coefficient and a voltage frequency domain coefficient; The determining, based on the reconstructed electrical characteristic curve, the electrical characteristic frequency domain coefficient of the battery includes: determining current data according to the reconstructed current curve, and determining voltage data according to the reconstructed voltage curve; Perform frequency domain conversion on the current data and the voltage data to obtain current frequency domain coefficients and voltage frequency domain coefficients.

6. A method for determining the battery health status of a battery of an electronic device, characterized in that: The determination method includes: Determining the current internal resistance of the battery according to the electrochemical impedance spectrum of the battery; wherein the electrochemical impedance spectrum is determined according to the method for determining the electrochemical impedance spectrum of a battery of an electronic device according to any one of claims 1 to 5; determining a current maximum dischargeable total capacity of the battery according to the current internal resistance; A current battery health state of the battery is determined based on the current maximum dischargeable total capacity and an initial maximum dischargeable total capacity of the battery.

7. The determination method according to claim 6, characterized in that: After determining the current battery health status of the battery, the determination method further includes: Correspondingly storing the current internal resistance and the current battery health status, and obtaining an aging curve corresponding to the battery; The aging curve is reconstructed by using a spline interpolation method to obtain a reconstructed aging curve.

8. A device for determining the electrochemical impedance spectrum of a battery of an electronic device, characterized in that: The determining device comprises: an acquisition module, configured to perform pulse charging on a battery of the electronic device based on a preset pulse current and acquire an electrical characteristic curve of the battery; a first curve reconstruction module, configured to reconstruct the electrical characteristic curve by an interpolation method to obtain a reconstructed electrical characteristic curve; A first determining module is configured to determine an electrical characteristic frequency domain coefficient of the battery based on the reconstructed electrical characteristic curve; and The electrochemical impedance spectrum of the battery is determined according to the electrical characteristic frequency domain coefficient.

9. The determination device according to claim 8, characterized in that The electrical characteristic curve includes a voltage curve; the voltage curve includes a first curve segment, a second curve segment, and a third curve segment; the segment lengths of the first curve segment and the second curve segment are associated with a preset time length, and the third curve segment is a curve segment of the voltage curve other than the first curve segment and the second curve segment; The first curve reconstruction module is further configured to reconstruct the first curve segment and the second curve segment by using a proximity interpolation method, and to reconstruct the third curve segment by using a spline interpolation method, to obtain a reconstructed voltage curve.

10. The determination device according to claim 8, characterized in that The electrical characteristic curve includes a current curve; The first curve reconstruction module is further configured to reconstruct the current curve by using a proximity interpolation method to obtain a reconstructed current curve.

11. The determination device according to claim 8, characterized in that The reconstructed electrical characteristic curve includes a reconstructed current curve and a reconstructed voltage curve, and the electrical characteristic frequency domain coefficient includes a current frequency domain coefficient and a voltage frequency domain coefficient; The first determining module is further configured to determine current data according to the reconstructed current curve, and determine voltage data according to the reconstructed voltage curve; The determining device further includes: The conversion module is used to perform frequency domain conversion on the current data and the voltage data to obtain current frequency domain coefficients and voltage frequency domain coefficients.

12. A device for determining the battery health status of a battery of an electronic device, characterized in that: The determining device comprises: a second determining module, configured to determine a current internal resistance of the battery according to an electrochemical impedance spectrum of the battery; wherein the electrochemical impedance spectrum is determined by the device for determining the electrochemical impedance spectrum of the battery of the electronic device according to any one of claims 8 to 11; and determining a current maximum dischargeable total capacity of the battery according to the current internal resistance; and A current battery health state of the battery is determined based on the current maximum dischargeable total capacity and an initial maximum dischargeable total capacity of the battery.

13. The determination device according to claim 12, characterized in that The determining device further includes: A storage module, configured to store the current internal resistance and the current battery health status correspondingly, and obtain an aging curve corresponding to the battery; The second curve reconstruction module is used to reconstruct the aging curve by using a spline interpolation method to obtain a reconstructed aging curve.

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