WO2021143592A1 - 电池等效电路模型的建立方法、健康状态估算方法及装置 - Google Patents

电池等效电路模型的建立方法、健康状态估算方法及装置 Download PDF

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WO2021143592A1
WO2021143592A1 PCT/CN2021/070443 CN2021070443W WO2021143592A1 WO 2021143592 A1 WO2021143592 A1 WO 2021143592A1 CN 2021070443 W CN2021070443 W CN 2021070443W WO 2021143592 A1 WO2021143592 A1 WO 2021143592A1
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Prior art keywords
battery
relaxation time
time distribution
spectrum
resistor
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PCT/CN2021/070443
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English (en)
French (fr)
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李良昱
李娟�
李阳兴
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华为技术有限公司
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Publication of WO2021143592A1 publication Critical patent/WO2021143592A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health

Definitions

  • This application relates to the technical field of battery management, in particular to a method for establishing an equivalent circuit model of a battery, a method for estimating the state of health of a battery, a battery management chip, and electrical equipment.
  • the equivalent circuit model has become a typical model widely used in battery management chips for simulating battery behavior due to its low complexity, fast computability, and real-time capability.
  • ECM equivalent circuit model
  • the existing equivalent circuit is not established based on the intrinsic polarization process inside the battery, and has artificial randomness, which causes the physical meaning behind the different components in the established equivalent circuit model to be unclear. That is, the existing battery equivalent circuit model has low accuracy, and thus cannot accurately distinguish different electrochemical processes of different active electrodes inside the battery.
  • the purpose of this application is to provide a method for establishing a battery equivalent circuit model, a method for estimating a battery state of health, a battery management chip and electrical equipment, which can improve the accuracy of establishing a battery model and the accuracy of estimating the battery state of health.
  • an embodiment of the present application discloses a method for establishing an equivalent circuit model of a battery, including:
  • the preset state parameters include preset temperature parameters and preset state-of-charge parameters
  • a battery equivalent circuit model is established according to the relaxation time distribution spectrum.
  • the technical solution described in the first aspect converts the electrochemical impedance spectrum of the battery obtained under preset state parameters into a relaxation time distribution, and establishes an equivalent circuit model of the battery according to the relaxation time distribution spectrum. That is, the different relaxation times of different polarization processes are used to distinguish the different polarization processes inside the battery, and then an equivalent circuit model that can reflect the internal characteristics of the different polarization processes inside the battery can be obtained.
  • the equivalent circuit model has a clear The physical meaning of, and uniqueness, thereby improving the accuracy of the establishment of the battery equivalent circuit model.
  • the calculating the relaxation time distribution spectrum of the battery according to the electrochemical impedance spectrum includes: The relationship between the chemical impedance spectrum and the relaxation time distribution adopts a relaxation time distribution analysis method to convert the electrochemical impedance spectrum from the frequency domain to the time domain, thereby obtaining the relaxation time distribution spectrum; wherein Different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • the calculating the relaxation time distribution spectrum of the battery according to the electrochemical impedance spectrum includes: The relationship between the chemical impedance spectrum and the relaxation time distribution is obtained by deconvolution. The different peaks in the relaxation time distribution spectrum correspond to the different dynamics in the battery. The relaxation time of the process.
  • the establishing a battery equivalent circuit model according to the relaxation time distribution spectrum includes:
  • a battery equivalent circuit model reflecting the internal characteristics of the battery is established according to the different internal resistances inside the battery.
  • the battery equivalent circuit model includes a resistance element and M circuit units connected in parallel with resistance and capacitance; where M is equal to a preset frequency in the relaxation time distribution spectrum.
  • M is equal to a preset frequency in the relaxation time distribution spectrum.
  • the battery equivalent circuit model includes:
  • Voltage source used to characterize the open circuit voltage of the battery
  • An ohmic resistance electrically connected to the positive electrode of the voltage source, used to characterize the ohmic internal resistance of the battery;
  • the first circuit unit is electrically connected to the ohmic resistor, and includes a first resistor and a first capacitor connected in parallel, and is used to characterize the polarization process caused by the contact resistance of the battery;
  • the second circuit unit is electrically connected to the first circuit unit, and includes a second resistor and a second capacitor connected in parallel, and is used to characterize the polarization process caused by the battery negative electrode solid electrolyte interface film and the negative electrode charge transfer resistance;
  • the third circuit unit is electrically connected between the second circuit unit and the positive electrode of the voltage output terminal, and includes a third resistor and a third capacitor connected in parallel, and is used to characterize the polarization process caused by the positive electrode charge transfer resistance of the battery .
  • each circuit unit represents a polarization process caused by a different internal resistance, so that the battery model has a clear physical meaning, and the model structure is simple and easy to identify parameters.
  • an embodiment of the present application discloses a method for estimating the state of health of a battery, including:
  • each electrochemical impedance spectrum includes the electrochemical impedance spectra of the battery at each preset state of charge and each temperature; the n is greater than 0 and less than or equal to N, and N is For the cycle life of the battery, the n cycles refer to n cycles selected from 0 to N cycles;
  • the corresponding battery equivalent circuit model is established according to the relaxation time distribution spectrum under each of the n cycles, and the battery internal parameters are calculated; wherein, the battery internal parameters include those in the battery equivalent circuit model The parameter of at least one element;
  • the battery health status under each cycle of the n cycles is the rated discharge capacity of the battery under the current cycle and the rated battery under the initial state The ratio of discharge capacity;
  • Parameter fitting is performed on the battery internal parameters under the n cycles and the battery health status under the n cycles to obtain a relational expression between the battery health status and the battery internal parameters.
  • the technical solution described in the second aspect converts the electrochemical impedance spectrum of the battery in each cycle into a relaxation time distribution, and establishes an equivalent circuit model of the battery according to the relaxation time distribution spectrum. That is, by using the different relaxation times of different polarization processes to distinguish the different polarization processes inside the battery, an equivalent circuit model that can reflect the internal characteristics of the different polarization processes inside the battery can be obtained, making the equivalent circuit model clear The physical meaning of, and uniqueness, thereby improving the accuracy of the establishment of the battery equivalent circuit model.
  • the interval between the number of adjacent cycles in the selected n cycles should be greater than the preset number.
  • the calculation of the corresponding relaxation time distribution spectrum according to the electrochemical impedance spectroscopy of each of the n cycles includes: according to the n cycles The relationship between the electrochemical impedance spectroscopy and the relaxation time distribution of each cycle in the cycle, the relaxation time distribution analysis method is used to convert the electrochemical impedance spectroscopy from the frequency domain to the time domain, so as to obtain the corresponding relaxation time. Relaxation time distribution spectrum; wherein, different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • the corresponding battery equivalent circuit model is established according to the relaxation time distribution spectrum in each of the n cycles, and the internal parameters of the battery are calculated, include:
  • a battery equivalent circuit model reflecting the internal characteristics of the battery is established according to the different internal resistances of the battery; the battery internal parameters include parameters of at least one element reflecting the internal characteristics of the battery in the battery equivalent circuit model.
  • the battery equivalent circuit model includes a resistance element and M circuit units connected in parallel with resistance and capacitance; where M is equal to a preset frequency in the relaxation time distribution spectrum. The number of peak spectra above.
  • the battery equivalent circuit model includes:
  • Ohmic resistance used to characterize the ohmic internal resistance of the battery
  • the first circuit unit includes a first resistor and a first capacitor connected in parallel, and is used to characterize the polarization process caused by the contact resistance of the battery;
  • the second circuit unit including a second resistor and a second capacitor connected in parallel, is used to characterize the polarization process caused by the solid electrolyte interface film of the negative electrode of the battery and the charge transfer resistance;
  • the third circuit unit including a third resistor and a third capacitor connected in parallel, is used to characterize the polarization process caused by the charge transfer resistance of the positive electrode of the battery;
  • the internal parameters of the battery include the resistance value of the ohmic resistor, the resistance value of the first resistor, the capacitance value of the first capacitor, the resistance value of the second resistor, the capacitance value of the second capacitor, The resistance of the third resistor, the capacitance of the third capacitor, the time constant of the polarization process caused by the battery contact resistance, the polarization caused by the battery's negative solid electrolyte interface film and the charge transfer resistance One or more of the time constant of the process or the time constant of the polarization process caused by the charge transfer resistance of the positive electrode of the battery.
  • the battery internal parameter is a time constant representing the polarization process caused by the positive electrode charge transfer resistance
  • the relationship expression between the battery state of health and the battery internal parameter Specifically: the expression of the relationship between the battery health status and the time constant representing the polarization process caused by the positive electrode charge transfer resistance.
  • the estimation method further includes:
  • the specific state is a preset state where the external characteristic parameters of the battery are in;
  • an embodiment of the present application discloses a battery management chip, including:
  • the obtaining module is used to obtain the electrochemical impedance spectroscopy of the battery under preset state parameters; wherein the preset state parameters include preset temperature parameters and preset state-of-charge parameters;
  • a data processing module for calculating the relaxation time distribution spectrum of the battery according to the electrochemical impedance spectrum
  • the model establishment module is used to establish an equivalent circuit model of the battery according to the relaxation time distribution spectrum.
  • the data processing module is configured to use a relaxation time distribution analysis method to analyze the electrochemical impedance spectroscopy according to the relationship between the electrochemical impedance spectroscopy and the relaxation time distribution.
  • the impedance spectrum is converted from the frequency domain to the time domain, thereby obtaining the relaxation time distribution spectrum; wherein, different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • the data processing module is configured to obtain the relaxation time by a deconvolution method according to the relationship between the electrochemical impedance spectrum and the relaxation time distribution. Distribution spectrum; wherein, different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • the model building module is used to identify different polarization processes in the battery according to the relaxation time of different dynamic processes in the battery; and then according to the battery Different internal polarization processes determine the different internal resistances inside the battery; and then establish a battery equivalent circuit model reflecting the internal characteristics of the battery according to the different internal resistances inside the battery.
  • the battery equivalent circuit model includes a resistance element and M circuit units connected in parallel with resistance and capacitance; where M is equal to a preset frequency in the relaxation time distribution spectrum. The number of peak spectra above.
  • the battery equivalent circuit model includes:
  • Voltage source used to characterize the open circuit voltage of the battery
  • An ohmic resistance electrically connected to the positive electrode of the voltage source, used to characterize the ohmic internal resistance of the battery;
  • the first circuit unit is electrically connected to the ohmic resistor, and includes a first resistor and a first capacitor connected in parallel, and is used to characterize the polarization process caused by the contact resistance of the battery;
  • the second circuit unit is electrically connected to the first circuit unit, and includes a second resistor and a second capacitor connected in parallel, and is used to characterize the polarization process caused by the battery negative electrode solid electrolyte interface film and the negative electrode charge transfer resistance;
  • the third circuit unit is electrically connected between the second circuit unit and the positive electrode of the voltage output terminal, and includes a third resistor and a third capacitor connected in parallel, and is used to characterize the polarization process caused by the positive electrode charge transfer resistance of the battery .
  • an embodiment of the present application discloses a battery management chip, including:
  • the obtaining module is used to obtain each electrochemical impedance spectra of the battery under n cycles; each of the electrochemical impedance spectra includes the electrochemical impedance spectra of the battery at each preset state of charge and each temperature; the n is greater than 0 and less than Equal to N, where N is the cycle life of the battery, and the n cycles refer to n cycles selected from 0 to N cycles; the acquisition module is also used to acquire the cycle life of each of the n cycles The battery health status; wherein the battery health status in each cycle is the ratio of the rated discharge capacity of the battery in the current cycle to the rated discharge capacity in the initial state of the battery;
  • a data processing module for calculating the corresponding relaxation time distribution spectrum according to the electrochemical impedance spectrum of each of the n cycles.
  • the model establishment module is used to establish the corresponding battery equivalent circuit model according to the relaxation time distribution spectrum under each cycle of the n cycles, and calculate the internal parameters of the battery; wherein, the internal parameters of the battery include the Parameters of at least one element in the battery equivalent circuit model;
  • the data processing module is further configured to perform parameter fitting on the battery internal parameters under the n cycles and the battery health status under the n cycles to obtain the relationship expression between the battery health status and the battery internal parameters .
  • the data processing module is configured to adopt relaxation according to the relationship between the electrochemical impedance spectroscopy and the relaxation time distribution of each of the n cycles.
  • the time distribution analysis method converts the electrochemical impedance spectrum from the frequency domain to the time domain, thereby obtaining its corresponding relaxation time distribution spectrum; wherein, the different peaks in the relaxation time distribution spectrum correspond to the inside of the battery Relaxation time for different dynamic processes.
  • the model establishment module is configured to identify the relaxation time of different dynamic processes inside the battery under each of the n cycles Different polarization processes inside the battery; and then determine the different internal resistances inside the battery according to the different polarization processes inside the battery; and then establish the battery equivalent that reflects the internal characteristics of the battery according to the different internal resistances inside the battery A circuit model; the battery internal parameters include parameters of at least one element that reflects the internal characteristics of the battery in the battery equivalent circuit model.
  • the battery equivalent circuit model includes a resistance element and M circuit units connected in parallel with resistance and capacitance; where M is equal to a preset frequency in the relaxation time distribution spectrum. The number of peak spectra above.
  • the battery equivalent circuit model includes:
  • Ohmic resistance used to characterize the ohmic internal resistance of the battery
  • the first circuit unit includes a first resistor and a first capacitor connected in parallel, and is used to characterize the polarization process caused by the contact resistance of the battery;
  • the second circuit unit including a second resistor and a second capacitor connected in parallel, is used to characterize the polarization process caused by the solid electrolyte interface film of the negative electrode of the battery and the charge transfer resistance;
  • the third circuit unit including a third resistor and a third capacitor connected in parallel, is used to characterize the polarization process caused by the charge transfer resistance of the positive electrode of the battery;
  • the internal parameters of the battery include the resistance value of the ohmic resistor, the resistance value of the first resistor, the capacitance value of the first capacitor, the resistance value of the second resistor, the capacitance value of the second capacitor, The resistance of the third resistor, the capacitance of the third capacitor, the time constant of the polarization process caused by the battery contact resistance, the polarization caused by the battery's negative solid electrolyte interface film and the charge transfer resistance One or more of the time constant of the process or the time constant of the polarization process caused by the charge transfer resistance of the positive electrode of the battery.
  • the battery management chip further includes a state estimation module
  • the data processing module is also used to obtain battery internal parameters of the battery in a specific state according to the battery state equation of the battery equivalent circuit model; the specific state is a preset state where the external characteristic parameters of the battery are located;
  • the state estimation module is used to obtain the battery health state of the battery in the specific state according to the battery internal parameters in the specific state and the relationship expression between the battery health state and the battery internal parameters.
  • an embodiment of the present application discloses an electrical device, including a battery and the charge management chip as described in the third aspect or the battery management chip as described in the fourth aspect; the battery management chip and the battery power supply Connect, monitor and manage the battery.
  • Fig. 1 is a functional block diagram of an electric device in an embodiment of the application.
  • Fig. 2 is a flowchart of a method for establishing an equivalent circuit model in an embodiment of the application.
  • FIG. 3 is a schematic diagram of the electrochemical impedance spectrum of the battery obtained in an embodiment of the application.
  • Fig. 4 is a relaxation time distribution spectrum obtained by calculating the electrochemical impedance spectroscopy in Fig. 3.
  • Figure 5 is a schematic diagram of the time constant distribution of different polarization processes inside the battery.
  • FIG. 6 is a schematic diagram of an equivalent circuit model of a battery in an embodiment of the application.
  • FIG. 7 is a flowchart of a method for estimating the state of health of a battery in an embodiment of the application.
  • FIG. 8 is a schematic diagram of electrochemical impedance spectroscopy under 10 cycles obtained in an embodiment of the application.
  • Fig. 9 is a relaxation time distribution spectrum under 10 cycles obtained by calculating the electrochemical impedance spectroscopy under 10 cycles in Fig. 8.
  • Fig. 10 is a schematic diagram of the state of health of the battery under 10 cycles.
  • FIG. 11 is a flowchart of a method for estimating the state of health of a battery in another embodiment of the application.
  • FIG. 12 is a functional block diagram of a battery management chip in an embodiment of the application.
  • FIG. 13 is a functional module diagram of a battery management chip in another embodiment of the application.
  • the embodiments of this application provide a method for establishing a power-consuming device, a battery management chip, a battery equivalent circuit model, and a battery state of health (SOH) estimation method, which are used to establish a more accurate battery model to calculate the battery Health status improves the accuracy of battery health status estimation.
  • SOH battery state of health
  • the method for establishing the equivalent circuit model of the battery and the method for estimating the state of health of the battery in the embodiments of the present application are mainly applicable to electrical equipment with rechargeable batteries.
  • rechargeable batteries include, but are not limited to, lithium-ion batteries, lithium-air batteries, lead-acid batteries, nickel-hydrogen batteries, and nickel-cadmium batteries.
  • the rechargeable battery is described by taking a lithium ion battery with higher energy density and power density as an example.
  • the electrical equipment in the embodiments of the present application includes terminal equipment, electric vehicles, energy storage equipment, and so on.
  • terminal devices refer to electronic products with rechargeable batteries, especially portable devices, such as mobile phones, tablet computers, notebook computers, various wearable devices and other terminal products.
  • battery management chips are required to monitor and estimate the battery to ensure that the battery runs during its safe life cycle.
  • the estimation of the battery health status is particularly important. If the estimation of the battery health status is not accurate, it will lead to the occurrence of battery safety accidents, for example, causing serious consequences such as battery explosion.
  • FIG. 1 is a functional block diagram of an electric device in an embodiment of the application.
  • the electrical equipment 1000 uses a terminal product (such as a mobile phone) as an example for description.
  • the electrical equipment 1000 includes a charging interface 100, a battery management chip 200, a battery 300 and a load 400.
  • the battery 300 may include a protection board (not shown) and a battery cell (not shown), and the load 400 may be any electrical component in the terminal product, such as a display, a communication module, a processor, a memory, a sensor, and Electrical components such as speakers.
  • the current flows as follows: charging interface 100 ⁇ battery management chip 200 ⁇ battery 300; when discharging, the current flows as follows: battery 300 ⁇ load 400.
  • the charging interface 100 may be a USB interface, for example, it may be a Mini USB interface, a Micro USB interface, a USB Type C interface, and so on.
  • the charging interface 100 may be used to connect a charger to charge the electric device 1000, and may also be used to transfer data between the electric device 1000 and peripheral devices. It can also be used to connect earphones and play audio through earphones.
  • the battery management chip 200 is electrically connected between the charging interface 100 and the battery 300.
  • the battery management chip 200 is used to monitor and estimate the state of the battery 300 under different working conditions, so as to improve the utilization rate of the battery 300 and prevent the battery 300 from overcharging and overdischarging, thereby prolonging the service life of the battery 300.
  • the main functions of the battery management chip 200 may include: real-time monitoring of battery physical parameters; battery state estimation; online diagnosis and early warning; charge, discharge and precharge control; balance management and thermal management, etc.
  • the most important and critical part of the battery management chip 200 is the accurate modeling of the battery 300 and the accurate estimation of the state.
  • the battery 300 since many parameters of the battery 300 have non-linear characteristics, it brings extremely high challenges to the state evaluation and modeling of the battery 300.
  • ECM equivalent circuit model
  • the existing equivalent circuit is not established based on the intrinsic polarization process inside the battery, and has artificial randomness, which causes the physical meaning behind the different components in the established equivalent circuit model to be unclear.
  • the establishment of the traditional equivalent circuit model is based on the researcher's own experience using limited basic elements (such as resistance, capacitance, inductance, etc.) to combine the corresponding circuit to match the relevant test data of the battery.
  • FIG. 2 is a flowchart of the method for establishing an equivalent circuit model in an embodiment of the present application.
  • the method for establishing the equivalent circuit model includes the following steps.
  • Step S101 Obtain electrochemical impedance spectroscopy of the battery under preset state parameters; wherein the preset state parameters include preset temperature parameters and preset state-of-charge parameters.
  • the electrochemical workstation can use an AC impedance test method to obtain the electrochemical impedance spectrum of the battery.
  • the preset temperature parameter is 25° C.
  • the preset state of charge (SOC) parameter is 100%. It can be understood that, in other embodiments, the preset temperature parameter may also be 20° C., 22° C., etc., and the preset state of charge parameter may also be 90%, 95%, etc., which are not specifically limited here.
  • FIG. 3 is a schematic diagram of the electrochemical impedance spectrum of the battery obtained in an embodiment of the application.
  • the horizontal axis in FIG. 3 represents the real part of the impedance
  • the vertical axis represents the imaginary part of the impedance.
  • a battery cell with a capacity of 4120 mAh is taken as an example for description.
  • the electrochemical impedance spectroscopy in FIG. 3 is the electrochemical impedance spectroscopy obtained when the cell temperature is 25° C. and the state of charge SOC is 100%, using an electrochemical workstation to perform an AC impedance test on the cell.
  • the test condition is an amplitude of 10 mV and a frequency range of 100 kHz to 0.05 Hz.
  • step S102 needs to be performed to correct The multiple electrochemical planning processes are accurately identified and distinguished.
  • Step S102 Calculate the relaxation time distribution spectrum of the battery according to the electrochemical impedance spectrum.
  • the analysis method of the relaxation time distribution is used to analyze the electric
  • the chemical impedance spectrum is converted from the frequency domain to the time domain, thereby obtaining the relaxation time distribution spectrum.
  • the impedance data is converted from the frequency domain to the time domain based on the Matlab algorithm.
  • the relaxation time distribution spectrum can be obtained by a deconvolution method.
  • deconvolution methods include, but are not limited to, Fourier transform (Fourier transform), maximum entropy principle (Maximum entropy), Bayesian approach (Bayesian approach), and ridge regression (Tikhonov regularization), etc.
  • the battery not only has different components such as positive electrode, negative electrode, electrolyte and current collector, but also has multiple interfaces of negative electrode/electrolyte, positive electrode/electrolyte, negative electrode/current collector and positive electrode/current collector, and electronic Or when ions are driven by an external circuit (charging or discharging) through the above components or interfaces, a variety of different physical and chemical processes will occur, thereby triggering changes in battery impedance and polarization.
  • a different frequency is applied to the battery. Measure the ratio of the AC potential to the current signal. The ratio is the impedance of the system. The impedance is the result of the above-mentioned different polarization processes.
  • the relaxation time distribution method is used to convert the impedance spectrum of the battery from the frequency domain to the time domain, so that the different relaxation times of different polarization processes can be used. , To distinguish the different polarization processes inside the battery.
  • Fig. 4 is the relaxation time distribution spectrum obtained by calculating the electrochemical impedance spectroscopy in Fig. 3.
  • the horizontal axis in Figure 4 represents the relaxation time
  • the vertical axis represents the polarization resistance.
  • the electrochemical impedance spectroscopy has three obvious peaks c, peak d, and peak e in the time domain, which indicate the frequency of the electrochemical polarization in the impedance spectroscopy. There are three distinct dynamic processes in the range.
  • different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • Step S103 Establish a battery equivalent circuit model according to the relaxation time distribution spectrum.
  • FIG. 5 is a schematic diagram of the time constant distribution of different polarization processes inside the battery.
  • the schematic diagram shown in Fig. 5 can be obtained by analyzing the different polarization processes inside the battery and the corresponding response time scale.
  • the processes corresponding to the three peaks can be accurately identified and distinguished in combination with Figure 5, which are the polarization process caused by contact resistance and the negative solid electrolyte.
  • this step first identify the different polarization processes inside the battery according to the relaxation time of the different dynamic processes inside the battery; then, determine the different polarization processes inside the battery according to the different polarization processes inside the battery. Different internal resistances; finally, a battery equivalent circuit model reflecting the internal characteristics of the battery is established according to the different internal resistances inside the battery.
  • FIG. 6 is a schematic diagram of an equivalent circuit model of a battery in an embodiment of the application.
  • the battery equivalent circuit model includes a resistor element R 0 and M circuit units connected in parallel with resistors and capacitors.
  • M is equal to the number of peak spectra above the preset frequency in the relaxation time distribution spectrum.
  • the preset frequency is 0.1 Hz. It can be understood that in other implementation manners, the preset frequency may also be set according to specific design conditions, which is not specifically limited in the embodiment of the present application.
  • the battery equivalent circuit model includes a voltage source U ocv , an ohmic resistance R 0 , a first circuit unit, a second circuit unit, and a third circuit unit.
  • the voltage source U ocv is used to characterize the open circuit voltage of the battery.
  • the ohmic resistance R 0 is electrically connected to the positive electrode of the voltage source U ocv , and is used to characterize the ohmic internal resistance of the battery.
  • the first circuit unit is electrically connected to the ohmic resistor R 0 and includes a first resistor R 1 and a first capacitor C 1 connected in parallel for characterizing the polarization process caused by the contact resistance of the battery.
  • the second circuit unit is electrically connected to the first circuit unit, and includes a second resistor R 2 and a second capacitor C 2 connected in parallel, which are used to characterize the polarization caused by the battery negative electrode solid electrolyte interface film and the negative electrode charge transfer resistance Process.
  • the third circuit unit is electrically connected between the second circuit unit and the positive electrode of the voltage output terminal, and includes a third resistor R 3 and a third capacitor C 3 connected in parallel, which are used to characterize the charge transfer resistance caused by the positive electrode of the battery. Polarization process.
  • the method for establishing the equivalent circuit model of the battery in the embodiment of the present application converts the electrochemical impedance spectrum of the battery obtained under preset state parameters into a general relaxation time distribution, and builds the battery according to the relaxation time distribution spectrum, etc. Effective circuit model. That is, the different relaxation times of different polarization processes are used to distinguish the different polarization processes inside the battery, and then an equivalent circuit model that can reflect the internal characteristics of the different polarization processes inside the battery can be obtained.
  • the equivalent circuit model has a clear The physical meaning of, and uniqueness, thereby improving the accuracy of the establishment of the battery equivalent circuit model.
  • the present application also provides a method for estimating the state of health of a battery based on the foregoing battery equivalent circuit model.
  • FIG. 7 is a flowchart of the method for estimating the state of health of a battery in an embodiment of the application.
  • the method for estimating the state of health of the battery includes the following steps.
  • Step S201 Obtain each electrochemical impedance spectrum under n cycles of the battery; each electrochemical impedance spectrum includes the electrochemical impedance spectra of the battery at each preset state of charge and each temperature; the n is greater than 0 and less than or equal to N , N is the cycle life of the battery, and the n cycles refer to n cycles selected from 0 to N cycles.
  • the interval between the number of adjacent two cycles in the selected n cycles should be greater than the preset number, for example, the preset number can be 30, 40, or 50. This is not limited.
  • FIG. 8 is a schematic diagram of electrochemical impedance spectroscopy under 10 cycles obtained in an embodiment of the application.
  • the horizontal axis in FIG. 8 represents the real part of the impedance
  • the vertical axis represents the imaginary part of the impedance.
  • a battery with a capacity of 4120 mAh is taken as an example for description.
  • the electrochemical impedance spectroscopy under 10 cycles shown in Figure 7 is when the temperature parameter of the battery is 25°C and the preset state-of-charge parameter is 100%, the electrochemical workstation is used to perform the measurement of the battery under 10 cycles.
  • the test conditions under each cycle are amplitude 10mV and frequency range 100kHz ⁇ 0.05Hz.
  • the 10 cycles respectively include the 0th cycle (not cycled), the 50th cycle, the 100th cycle, the 150th cycle, the 250th cycle, the 350th cycle, the 450th cycle, The 550th cycle, the 650th cycle, and the 750th cycle.
  • preset temperature parameters and preset state parameters in each cycle in this embodiment are the same. In other embodiments, the preset temperature parameters and preset state parameters in each cycle may also be different. There is no limitation here.
  • Step S202 Calculate the corresponding relaxation time distribution spectrum according to the electrochemical impedance spectrum of each of the n cycles.
  • FIG. 9 is a relaxation time distribution spectrum under 10 cycles obtained by calculating the electrochemical impedance spectra under 10 cycles in FIG. 8.
  • the horizontal axis in FIG. 9 represents the frequency (the inverse of the relaxation time)
  • the vertical axis represents the polarization resistance.
  • the relaxation time distribution method is adopted to convert the impedance data of the battery under different charge and discharge cycles from the frequency domain to the time domain based on the matrix laboratory (Matlab) algorithm.
  • Step S203 Calculate battery internal parameters according to the relaxation time distribution spectrum in each of the n cycles; wherein, the battery internal parameters include at least the battery equivalent circuit model established according to the foregoing establishment method The parameter of a component.
  • the battery equivalent circuit model in each of the n cycles, only the internal parameters of the battery need to be calculated according to the relaxation time distribution spectrum, that is, the battery equivalent circuit model can be pre-established and preset in the system according to the aforementioned establishment method. , As long as the parameters in the battery equivalent circuit model are calculated. In other embodiments, the corresponding battery equivalent circuit model (as shown in FIG. 6) can also be established in each of the n cycles, and the internal parameters of the battery can be calculated.
  • the internal parameters of the battery include parameters of at least one element reflecting the internal characteristics of the battery in the battery equivalent circuit model.
  • One or more of the time constants ⁇ 3 ( ⁇ 3 R 3 ⁇ C 3) of the induced polarization process.
  • Step S204 Obtain the battery health status under each cycle in the n cycles; wherein the battery health status under each cycle is the rated discharge capacity of the battery in the current cycle and the battery initial state The ratio of the rated discharge capacity below.
  • FIG. 10 is a schematic diagram of the battery health status under 10 cycles.
  • the horizontal axis in FIG. 10 represents the number of cycles
  • the vertical axis represents the battery health status.
  • Step S205 Perform parameter fitting on the battery internal parameters under the n cycles and the battery health status under the n cycles to obtain a relational expression between the battery health status and the battery internal parameters.
  • the relationship between the time constant ⁇ 3 representing the polarization process caused by the positive charge transfer resistance and the battery health state SOH can be analyzed based on the regression analysis algorithm of Matlab, and it can be concluded that there is a simple relationship between ⁇ 3 and the battery SOH.
  • the obvious linear relationship can be used as an internal parameter of the battery to evaluate the health state SOH of the battery cell.
  • the battery internal parameter represents the time constant of the polarization process caused by the positive electrode charge transfer resistance
  • the relationship expression between the battery health status and the battery internal parameters is specifically: battery health The expression of the relationship between the state and the time constant representing the polarization process caused by the positive electrode charge transfer resistance.
  • FIG. 11 shows the battery health status in another embodiment of the application.
  • Step S301 Obtain battery internal parameters of the battery in a specific state according to the battery state equation of the battery equivalent circuit model; the specific state is a preset state where the external characteristic parameters of the battery are located.
  • the external characteristic parameter includes at least one of a current parameter, a voltage parameter, or a temperature parameter.
  • the external characteristic parameter reaches a specific threshold, it is determined that the battery is in the specific state.
  • the battery state equation is used to simulate the voltage-current behavior of the battery under different operating conditions.
  • the battery state equation established based on the battery equivalent circuit model in FIG. 6 is as follows:
  • the external characteristic parameter when the external characteristic parameter reaches a certain threshold, first perform an online impedance test on the battery, and record the voltage and current data during the online impedance test.
  • the online impedance test can choose the frequency domain method or the time domain method according to actual conditions, which is not limited here. Then the voltage and current data recorded during the online impedance test are substituted into the above battery state equation, and the internal parameters of the battery R 0 , R 1 , C 1 , ⁇ 1 , R 2 , C 2 , ⁇ 2 can be obtained through parameter identification, R 3 , C 3 , ⁇ 3 .
  • Step S302 Obtain the battery health status of the battery in the specific state according to the battery internal parameters in the specific state and the relational expression between the battery health status and the battery internal parameters.
  • the current online health status of the battery can be estimated.
  • the battery health state SOH estimation method proposed in the embodiments of the application converts the electrochemical impedance spectrum of the battery in each cycle into a relaxation time distribution, and establishes an equivalent circuit model of the battery according to the relaxation time distribution spectrum. That is, by using the different relaxation times of different polarization processes to distinguish the different polarization processes inside the battery, an equivalent circuit model that can reflect the internal characteristics of the different polarization processes inside the battery can be obtained, making the equivalent circuit model clear The physical meaning of, and uniqueness, thereby improving the accuracy of the establishment of the battery equivalent circuit model.
  • the battery management chip 200 includes an acquisition module 210, a data processing module 220, a model establishment module 230, and a storage module 240.
  • the obtaining module 210 is used to obtain the electrochemical impedance spectroscopy of the battery under preset state parameters; wherein, the preset state parameters include preset temperature parameters and preset state-of-charge parameters.
  • the data processing module 220 is configured to calculate the relaxation time distribution spectrum of the battery according to the electrochemical impedance spectrum.
  • the model building module 230 is used to build a battery equivalent circuit model according to the relaxation time distribution spectrum.
  • the storage module 240 is used to store the battery equivalent circuit model.
  • the data processing module 220 is configured to adopt a relaxation time distribution analysis method according to the relationship between the electrochemical impedance spectrum and the relaxation time distribution to convert the electrochemical impedance spectrum from the frequency domain to the time domain, Thereby, the relaxation time distribution spectrum is obtained; or, the data processing module 220 is configured to obtain the relaxation time distribution by deconvolution according to the relationship between the electrochemical impedance spectrum and the relaxation time distribution Spectrum.
  • different peaks in the relaxation time distribution spectrum correspond to relaxation times of different dynamic processes inside the battery.
  • the model building module 230 is used to identify different polarization processes inside the battery according to the relaxation time of different dynamic processes inside the battery; determine the different polarization processes inside the battery according to the different polarization processes inside the battery Resistance; According to the different internal resistances inside the battery, a battery equivalent circuit model reflecting the internal characteristics of the battery is established.
  • FIG. 13 is a functional module diagram of a battery management chip in another embodiment of the application. Different from the battery management chip 200 in FIG. 11, the battery management chip 200 in this embodiment further includes a data processing module 250, a detection module 260 and an estimation module 270.
  • the acquiring module 210 acquires each electrochemical impedance spectra of the battery under n cycles; each of the electrochemical impedance spectra includes the electrochemical impedance spectra of the battery at each preset state of charge and each temperature; the n is greater than 0 and less than Equal to N, where N is the cycle life of the battery, and the n cycles refer to n cycles selected from 0 to N cycles.
  • the data processing module 220 is configured to calculate the corresponding relaxation time distribution spectrum according to the electrochemical impedance spectrum of each of the n cycles.
  • the data processing module 220 is further configured to calculate the internal parameters of the battery according to the relaxation time distribution spectrum in each of the n cycles.
  • the internal parameters of the battery include parameters of at least one element in the battery equivalent circuit model established according to the foregoing establishment method.
  • the acquiring module 210 is also used to acquire the battery health status in each cycle of the n cycles; wherein the battery health status in each cycle is the rated discharge capacity of the battery in the current cycle and The ratio of the rated discharge capacity of the battery in the initial state.
  • the data processing module 250 is also used to perform parameter fitting on the battery internal parameters under the n cycles and the battery health status under the n cycles to obtain the relationship expression between the battery health status and the battery internal parameters Mode.
  • the detection module 260 is used to detect the external characteristic parameters of the battery.
  • the data processing module 250 is also used to obtain battery internal parameters of the battery in a specific state according to the battery state equation of the battery equivalent circuit model; the specific state is a preset state of the external characteristic parameters of the battery.
  • the state estimation module 270 is configured to obtain the battery health state of the battery in the specific state according to the battery internal parameters in the specific state and the relationship expression between the battery health state and the battery internal parameters.
  • the storage module 240 is used to store the battery equivalent circuit model, internal parameters, the relationship expression between the battery health state and the battery internal parameters, the battery state equation established based on the battery equivalent circuit, and the The detected current and voltage are temperature parameter information.
  • the data processing module 220 is used to analyze the relationship between the electrochemical impedance spectroscopy and the relaxation time distribution in each of the n cycles by using a relaxation time distribution analysis method to analyze the electrochemical
  • the impedance spectrum is converted from the frequency domain to the time domain, thereby obtaining its corresponding relaxation time distribution spectrum; wherein, different peaks in the relaxation time distribution spectrum correspond to the relaxation times of different dynamic processes inside the battery.
  • the model building module 230 is used to identify different polarization processes in the battery according to the relaxation time of the different dynamic processes inside the battery under each of the n cycles;
  • the different polarization processes of the battery determine the different internal resistances within the battery;
  • the battery equivalent circuit model reflecting the internal characteristics of the battery is established according to the different internal resistances of the battery;
  • the battery internal parameters include the battery equivalent circuit The parameter of at least one element reflecting the internal characteristics of the battery in the model.
  • the method for establishing the equivalent circuit model and the method for estimating the state of battery health provided in this application can be implemented in hardware or firmware, or can be stored in, for example, read-only memory (Read-Only Memory, ROM), random access
  • the software or computer code in computer-readable storage media such as memory (Random Access Memory, RAM), floppy disk, hard disk, or magneto-optical disk, or can be stored as original on a remote recording medium or non-transitory machine-readable medium.
  • the computer code is downloaded from the network and stored in a local recording medium, so that the method described here can utilize a general-purpose computer or a special processor or be programmed in a programmable or programmable gate array such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA)
  • a computer, processor, microprocessor, controller, or programmable hardware includes memory components, such as RAM, ROM, flash memory, etc., when the computer, processor, or hardware implements the processing methods described herein, the storage
  • the memory component can store or receive the software or computer code.
  • the execution of the code converts the general-purpose computer into a special-purpose computer for executing the processing shown here.
  • the computer-readable storage medium may be a solid-state memory, a memory card, an optical disc, and the like.
  • the computer-readable storage medium stores program instructions for the computer, mobile phone, tablet computer, or the electrical equipment of the present application to execute the aforementioned equivalent circuit model establishment method and battery health state estimation method.

Abstract

一种电池等效电路模型的建立方法、基于模型的电池健康状态的估算方法以及使用该方法的相关装置。电池等效电路模型的建立方法包括：获取电池在预设状态参数下的电化学阻抗谱（S101）；其中，预设状态参数包括预设温度参数和预设荷电状态参数；根据电化学阻抗谱计算电池的驰豫时间分布谱（S102）；根据驰豫时间分布谱建立电池等效电路模型（S103）。

Description

电池等效电路模型的建立方法、健康状态估算方法及装置
本申请要求于2020年1月17日提交中国专利局、申请号为202010053974.1、申请名称为“电池等效电路模型的建立方法、健康状态估算方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电池管理技术领域，尤其涉及电池等效电路模型的建立方法、电池健康状态的估算方法、电池管理芯片及用电设备。
背景技术
等效电路模型(ECM)因其具有低复杂性，快速可计算性和可实时性等成为电池管理芯片中模拟电池行为所广泛使用的典型模型。然而，现有的等效电路的建立并不是基于电池内部的本征极化过程所建立，具有人为的随机性存在，进而导致所建立等效电路模型中不同的组成模块背后的物理意义不明。也即，现有的电池等效电路模型精度较低，进而无法准确区分电池内部不同活性电极的不同电化学过程。
发明内容
本申请的目的在于提供一种电池等效电路模型的建立方法、电池健康状态的估算方法、电池管理芯片及用电设备，可以提高电池模型的建立精度以及电池健康状态估算的准确性。
第一方面，本申请实施例公开一种电池等效电路模型的建立方法，包括：
获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数；
根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱；
根据所述驰豫时间分布谱建立电池等效电路模型。
第一方面所描述的技术方案，将在预设状态参数下获取的电池的电化学阻抗谱转化成驰豫时间分布普，并根据所述驰豫时间分布谱建立电池等效电路模型。即利用不同极化过程的弛豫时间不同，将电池内部不同的极化过程区分出来，进而可以得到能够反映电池内部不同极化过程等内部特性的等效电路模型，该等效电路模型具有明确的物理意义，且具有唯一性，进而提高了电池等效电路模型的建立精度。
根据第一方面，为了提高驰豫时间分布谱的转换效率，在一种可能的实现方式中，所述根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱包括：根据所述电化学阻抗谱与弛豫时间分布之间的关系采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第一方面，为了提高驰豫时间分布谱的转换效率，在一种可能的实现方式中，所述根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱包括：根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第一方面，在一种可能的实现方式中，所述根据所述驰豫时间分布谱建立电池等效电路模型包括：
根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；
根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；
根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
如此可以实现电池等效电路模型和驰豫时间分布谱的对应关系。
根据第一方面，在一种可能的实现方式中，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。由于每个谱峰对应不同的极化过程，如此，可以将电池内部的每个极化过程和电池等效电路模型中的电路单元一一对应，使得该电路模型具有明确的物理意义。
根据第一方面，在一种可能的实现方式中，所述电池等效电路模型包括：
电压源，用于表征电池的开路电压；
欧姆电阻，与所述电压源的正极电连接，用于表征电池的欧姆内阻；
第一电路单元，与所述欧姆电阻电连接，并包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
第二电路单元，与所述第一电路单元电连接，并包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及负极电荷传递电阻所引起的极化过程；以及
第三电路单元，电连接于所述第二电路单元和所述电压输出端正极之间，并包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程。
本实施方式中，每个电路单元代表不同的内阻引起的极化过程，使得电池模型具有明确的物理意义，且模型结构简单易于参数辨识。
第二方面，本申请实施例公开一种电池健康状态的估算方法，包括：
获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环；
根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱；
根据所述n次循环中的每一次循环下的驰豫时间分布谱建立其对应的电池等效电路模型，并计算电池内部参数；其中，所述电池内部参数包括所述电池等效电路模型中的至少一个元件的参数；
获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值；
对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
第二方面所描述的技术方案，将电池在每次循环下的电化学阻抗谱转化成驰豫时间分布普，并根据所述驰豫时间分布谱建立电池等效电路模型。即利用不同极化过程的弛豫时间不同，将电池内部不同的极化过程区分出来，可以得到能够反映电池内部不同极化过程等内部特性的等效电路模型，使得该等效电路模型具有明确的物理意义，且具有唯一性，进而提高 了电池等效电路模型的建立精度。进一步地，基于n次循环下该等效电路模型的内部参数及n次循环下的电池健康状态，可以获得精度较高的电池健康状态与电池内部参数之间的关系表达式，可以提高后续在线估算电池健康状态SOH的精度。
其中，为了提高估算的精度，所选取的n次循环中的相邻两次的循环次数之间的间隔应大于预设次数。
根据第二方面，在一种可能的实现方式中，所述根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱包括：根据所述n次循环中的每一次循环的电化学阻抗谱与弛豫时间分布之间的关系，采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得其对应的弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第二方面，在一种可能的实现方式中，所述根据所述n次循环中的每一次循环下的驰豫时间分布谱建立其对应的电池等效电路模型，并计算电池内部参数，包括：
根据所述n次循环中的每一次循环下的所述电池内部不同动力学过程的驰豫时间，识别所述电池内部的不同极化过程；
根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；
根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型；所述电池内部参数包括所述电池等效电路模型中反映所述电池内部特性的至少一个元件的参数。
根据第二方面，在一种可能的实现方式中，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。
根据第二方面，在一种可能的实现方式中，所述电池等效电路模型包括：
欧姆电阻，用于表征电池的欧姆内阻；
第一电路单元，包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
第二电路单元，包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程；以及
第三电路单元，包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程；
所述电池内部参数包括所述欧姆电阻的阻值、所述第一电阻的阻值、所述第一电容的容值、所述第二电阻的阻值、所述第二电容的容值、所述第三电阻的阻值、所述第三电容的容值、所述电池接触电阻引起的极化过程的时间常数、所述电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程的时间常数或电池正极电荷传递电阻所引起的极化过程的时间常数中的一个或多个。
根据第二方面，在一种可能的实现方式中，所述电池内部参数为代表正极电荷转移电阻引起的极化过程的时间常数，所述电池健康状态与电池内部参数之间的关系表达式，具体为：电池健康状态与代表正极电荷转移电阻引起的极化过程的时间常数之间的关系表达式。
根据第二方面，在一种可能的实现方式中，为了实现对电池健康状态的在线估算，所述估算方法还包括：
根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态；
根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
第三方面，本申请实施例公开一种电池管理芯片，包括：
获取模块，用于获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数；
数据处理模块，用于根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱；以及
模型建立模块，用于根据所述驰豫时间分布谱建立电池等效电路模型。
根据第三方面，在一种可能的实现方式中，所述数据处理模块用于根据所述电化学阻抗谱与弛豫时间分布之间的关系采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第三方面，在一种可能的实现方式中，所述数据处理模块用于根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第三方面，在一种可能的实现方式中，所述模型建立模块用于根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；再根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；再根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
根据第三方面，在一种可能的实现方式中，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。
根据第三方面，在一种可能的实现方式中，所述电池等效电路模型包括：
电压源，用于表征电池的开路电压；
欧姆电阻，与所述电压源的正极电连接，用于表征电池的欧姆内阻；
第一电路单元，与所述欧姆电阻电连接，并包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
第二电路单元，与所述第一电路单元电连接，并包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及负极电荷传递电阻所引起的极化过程；以及
第三电路单元，电连接于所述第二电路单元和所述电压输出端正极之间，并包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程。
第四方面，本申请实施例公开一种电池管理芯片，包括：
获取模块，用于获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环；所述获取模块还用于获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值；
数据处理模块，用于根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱；以及
模型建立模块，用于根据所述n次循环中的每一次循环下的驰豫时间分布谱建立其对应的电池等效电路模型，并计算电池内部参数；其中，所述电池内部参数包括所述电池等效电路模型中至少一个元件的参数；
所述数据处理模块还用于对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
根据第四方面，在一种可能的实现方式中，所述数据处理模块用于根据所述n次循环中的每一次循环的电化学阻抗谱与弛豫时间分布之间的关系，采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得其对应的弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
根据第四方面，在一种可能的实现方式中，所述模型建立模块用于根据所述n次循环中的每一次循环下的所述电池内部不同动力学过程的驰豫时间，识别所述电池内部的不同极化过程；再根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；再根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型；所述电池内部参数包括所述电池等效电路模型中反映所述电池内部特性的至少一个元件的参数。
根据第四方面，在一种可能的实现方式中，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。
根据第四方面，在一种可能的实现方式中，所述电池等效电路模型包括：
欧姆电阻，用于表征电池的欧姆内阻；
第一电路单元，包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
第二电路单元，包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程；以及
第三电路单元，包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程；
所述电池内部参数包括所述欧姆电阻的阻值、所述第一电阻的阻值、所述第一电容的容值、所述第二电阻的阻值、所述第二电容的容值、所述第三电阻的阻值、所述第三电容的容值、所述电池接触电阻引起的极化过程的时间常数、所述电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程的时间常数或电池正极电荷传递电阻所引起的极化过程的时间常数中的一个或多个。
根据第四方面，在一种可能的实现方式中，所述电池管理芯片还包括状态估算模块；
所述数据处理模块还用于根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态；
所述状态估算模块用于根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
第五方面，本申请实施例公开一种用电设备，包括电池以及如第三方面所述的充电管理芯片或者如第四方面所述的电池管理芯片；所述电池管理芯片与所述电池电连接，并对所述电池进行监测与管理。
附图说明
为了说明本申请实施例或背景技术中的技术方案，下面将对本申请实施例或背景技术中所需要使用的附图进行说明。
图1为本申请实施例中的用电设备的原理框图。
图2为本申请实施例中的等效电路模型的建立方法的流程图。
图3为本申请一实施方式中所获取的电池的电化学阻抗谱的示意图。
图4为对图3中的电化学阻抗谱进行计算得出的驰豫时间分布谱。
图5为电池内部不同极化过程的时间常数分布示意图。
图6为本申请实施例中的电池等效电路模型的示意图。
图7为本申请实施例中的电池健康状态的估算方法的流程图。
图8为本申请实施例中所获取的10次循环下的电化学阻抗谱的示意图。
图9为对图8中的10次循环下的电化学阻抗谱进行计算得出的10次循环下的驰豫时间分布谱。
图10为10次循环下的电池健康状态的示意图。
图11为本申请另一实施例中的电池健康状态的估算方法的流程图。
图12为本申请一实施例中的电池管理芯片的功能模块图。
图13为本申请另一实施例中的电池管理芯片的功能模块图。
具体实施方式
本申请实施例提供了一种用电设备、电池管理芯片、电池等效电路模型的建立方法和电池健康状态(State of Health，SOH)估算方法，用于建立精确度更高的电池模型计算电池健康状态，提高了电池健康状态估算的准确性。
本申请实施例中的电池等效电路模型的建立方法及电池健康状态估算方法主要适用于具有充电电池的用电设备中。其中，充电电池包括但不限于锂离子电池、锂空气电池、铅酸电池、镍氢电池及镍镉电池等。本申请实施例中，充电电池以能量密度和功率密度较高的锂离子电池为例进行说明。
本申请实施例中的用电设备包括终端设备、电动车及储能设备等。其中，终端设备是指具有充电电池的电子产品，尤其是指一些便携设备，如手机、平板电脑、笔记本电脑、各种穿戴设备等终端产品。对于此类使用充电电池的用电设备，就需要电池管理芯片对电池进行监测和估算，以保证电池在其安全生命周期内运行。其中对电池健康状态的估算尤为重要，若是对电池健康状态估算不准，将导致电池安全事故的发生，例如，引起电池爆炸等严重后果。
为了使本技术领域的人员更好地理解本申请方案，下面将结合本申请实施例中的附图，对本申请的实施例进行描述。
请参阅图1，图1为本申请实施例中的用电设备的原理框图。在本实施方式中，用电设备1000以终端产品(如手机)为例进行说明。如图1所示，用电设备1000包括充电接口100、 电池管理芯片200、电池300以及负载400。其中所述电池300可以包括保护板(图未示)和电芯(图未示)，负载400可以是该终端产品内的任何用电组件，如显示器、通信模块、处理器、存储器、传感器以及扬声器等用电组件。在所述用电设备1000充电时电流流向如下：充电接口100→电池管理芯片200→电池300；放电时电流流向如下：电池300→负载400。
在一实施方式中，充电接口100可以是USB接口，例如可以是Mini USB接口，Micro USB接口，USB Type C接口等。充电接口100可以用于连接充电器为用电设备1000充电，也可以用于用电设备1000与外围设备之间传输数据。也可以用于连接耳机，通过耳机播放音频。
电池管理芯片200电连接于所述充电接口100和所述电池300之间。电池管理芯片200用于对电池300在不同工况下的状态进行监测和估算，以提高电池300的利用率，防止电池300出现过充电和过放电，从而延长电池300的使用寿命。具体地，电池管理芯片200的主要功能可包括：电池物理参数实时监测；电池状态估计；在线诊断与预警；充、放电与预充控制；均衡管理和热管理等。
其中电池管理芯片200中最重要和最关键的部分是对电池300的精确建模和状态的准确估计。然而，由于电池300的很多参数具有非线性的特点，给电池300的状态评估和建模带来了极高的挑战。
现有的电池模型可以分为电化学模型、等效电路模型、数学模型和分析模型等。其中等效电路模型(ECM)因其具有低复杂性，快速可计算性和可实时性等成为电池管理芯片中模拟电池行为所广泛使用的典型模型。然而，现有的等效电路的建立并不是基于电池内部的本征极化过程所建立，具有人为的随机性存在，进而导致所建立等效电路模型中不同的组成模块背后的物理意义不明。例如，传统的等效电路模型的建立，是研究者基于自身经验利用有限的基本元件(如电阻、电容、电感等)组合成相应的电路从而匹配电池的相关测试数据。这就造成存在多种不同的电路组合可以匹配同样的测试数据，即等效电路模型的建立具有不唯一性。也即，现有的电池等效电路模型精度较低，进而无法准确区分电池内部不同活性电极的不同电化学过程。
为解决上述问题，本申请实施例提供一种等效电路模型的建立方法，请参阅图2，图2为本申请实施例中的等效电路模型的建立方法的流程图。该等效电路模型的建立方法包括如下步骤。
步骤S101，获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数。
具体地，可以通过电化学工作站采用交流阻抗测试的方式来获取电池的电化学阻抗谱。在本实施方式中，预设温度参数为25℃，预设荷电状态(State of Charge，SOC)参数为100％。可以理解，在其他实施方式中，预设温度参数还可以为20℃、22℃等，所述预设荷电状态参数还可以是90％、95％等，在此不做具体限定。
请参阅图3，图3为本申请一实施方式中所获取的电池的电化学阻抗谱的示意图。其中，图3中的横轴代表阻抗实部，纵轴代表阻抗虚部。在本实施方式中，以容量为4120mAh的电芯为例进行说明。其中，图3中的电化学阻抗谱是电芯在温度为25℃，荷电状态SOC为100％时，利用电化学工作站对电芯进行交流阻抗测试所获取的电化学阻抗谱。本实施方式中，测试条件为振幅10mV，频率范围100kHz～0.05Hz。
从图3中可看出，在中高频阶段存在两个明显的第一弧段a和第二弧段b，说明电芯内部存在多个电化学极化过程，因此，需要执行步骤S102以对该多个电化学计划过程进行准确的识别和区分。
步骤S102，根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱。
在一种实施方式中，根据电池的电化学阻抗谱Z(ω)与弛豫时间分布g(τ)之间的关系(参考下面公式1)，采用弛豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱。例如，采用驰豫时间分布方法，基于Matlab算法将阻抗数据从频域转化为时域。
Figure PCTCN2021070443-appb-000001
另外，还可以根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱。其中，去卷积的方法包括但不限于傅立叶变换(Fourier transform)、最大熵原理(Maximum entropy)、贝叶斯方法(Bayesian approach)及岭回归(ridge regression，Tikhonov regularization)等。
需要说明的是，电池不仅存在正极、负极、电解液和集流体等不同的组分，同时还存在负极/电解液，正极/电解液，负极/集流体和正极/集流体多个界面，电子或离子在外电路(充电或放电)的驱动下通过上述组分或界面时会发生多种不同的物理和化学过程，从而引发电池阻抗和极化的变化，步骤S101中通过给电池施加一个频率不同的小振幅的交流电势波，测量交流电势与电流信号的比值，其中该比值即为系统的阻抗，该阻抗是上述不同极化过程共同表现的结果，由于不同的极化过程在频率上十分接近，因而无法直接从频率域上将每个过程区分出来。而在时间域上，不同的极化过程由暂态趋于某种定态所需要的时间表现出较大的差异，即每个过程的弛豫时间不同，因而可以从时间域上准确的将电池内部的不同极化过程区分出来，而本实施例中即是利用弛豫时间分布的方法，将电池的阻抗谱从频率域转化为时间域，从而可以利用不同极化过程的弛豫时间不同，将电池内部不同的极化过程区分出来。
请参阅图4，图4为对图3中的电化学阻抗谱进行计算得出的驰豫时间分布谱。其中，图4中的横轴代表驰豫时间，纵轴代表极化电阻。从图4中可以看出，所述电化学阻抗谱在时域范围出现了三个明显的谱峰c、谱峰d和谱峰e，即表明在阻抗谱中的电化学极化所在的频率范围内共存在三分明显的动力学过程。
在本实施方式中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
步骤S103，根据所述驰豫时间分布谱建立电池等效电路模型。
请参阅图5，图5为电池内部不同极化过程的时间常数分布示意图。其中图5所示的示意图，可以通过对电池内部不同的极化过程及相应的响应时间尺度进行分析而得出。根据图4中的驰豫时间分布谱中的谱峰所对应的时间常数，结合图5可以准确的识别和区分三个谱峰所对应的过程分别为接触电阻引起的极化过程、负极固体电解质界面膜(SEI)及负极电荷传递电阻引起的极化过程和正极电荷传递电阻引起的极化过程。
因此，在该步骤中，首先根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；然后，根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；最后，根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
请参阅图6，图6为本申请实施例中的电池等效电路模型的示意图。所述电池等效电路模型包括一个电阻元件R 0及M个电阻电容并联的电路单元。其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。本实施方式中，预设频率为0.1Hz。可以理解，其他实施方式中，预设频率还可以根据具体的设计情况而进行设定，本申请实施例对此不作具体限定。
本实施方式中，所述电池等效电路模型包括电压源U ocv、欧姆电阻R 0、第一电路单元、第二电路单元以及第三电路单元。电压源U ocv用于表征电池的开路电压。欧姆电阻R 0与所述电压源U ocv的正极电连接，用于表征电池的欧姆内阻。第一电路单元与所述欧姆电阻R 0电连接，并包括并联的第一电阻R 1和第一电容C 1，用于表征电池接触电阻所引起的极化过程。第二电路单元与所述第一电路单元电连接，并包括并联的第二电阻R 2和第二电容C 2，用于表征电池负极固体电解液界面膜及负极电荷传递电阻所引起的极化过程。第三电路单元电连接于所述第二电路单元和所述电压输出端正极之间，并包括并联的第三电阻R 3和第三电容C 3，用于表征电池正极电荷传递电阻所引起的极化过程。
本申请实施例中的电池等效电路模型的建立方法，将在预设状态参数下获取的电池的电化学阻抗谱转化成驰豫时间分布普，并根据所述驰豫时间分布谱建立电池等效电路模型。即利用不同极化过程的弛豫时间不同，将电池内部不同的极化过程区分出来，进而可以得到能够反映电池内部不同极化过程等内部特性的等效电路模型，该等效电路模型具有明确的物理意义，且具有唯一性，进而提高了电池等效电路模型的建立精度。
本申请还提供一种基于上述电池等效电路模型的电池健康状态估算方法，具体请参阅图7，图7为本申请实施例中的电池健康状态的估算方法的流程图。该电池健康状态的估算方法包括如下步骤。
步骤S201，获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环。
其中，为了提高估算的精度，所选取的n次循环中的相邻两次的循环次数之间的间隔应大于预设次数，例如，预设次数可以是30次、40次或者50次，在此不做限定。
请参阅图8，图8为本申请实施例中所获取的10次循环下的电化学阻抗谱的示意图。其中，图8中的横轴代表阻抗实部，纵轴代表阻抗虚部。在本实施方式中，以容量为4120mAh的电池为例进行说明。其中，图7中所示的10次循环下的电化学阻抗谱，是电池在温度参数为25℃、预设荷电状态参数为100％时，利用电化学工作站对10次循环下的电池进行交流阻抗测试所获取的电化学阻抗谱。其中每次循环下的测试条件为振幅10mV，频率范围100kHz～0.05Hz。本实施方式中，10次循环分别包括第0次循环(未循环过)、第50次循环、第100次循环、第150次循环、第250次循环、第350次循环、第450次循环、第550次循环、第650次循环和第750次循环。
需要说明的是，本实施方式中的每次循环下的预设温度参数和预设状态参数相同，在其他实施方式中，每次循环下的预设温度参数和预设状态参数也可以不同，在此不做限定。
从图8中可以看出，电池的电化学极化过程随着电池的老化发生了明显的变化，因此需要对和电池老化相关的参数和极化过程进行准确的区分和识别。
步骤S202，根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱。
请参阅图9，图9为对图8中的10次循环下的电化学阻抗谱进行计算得出的10次循环下的驰豫时间分布谱。其中，图9中的横轴代表频率(驰豫时间的倒数)，纵轴代表极化电阻。具体地，与步骤S102的实现方式类似，采用驰豫时间分布法，基于矩阵实验室(Matlab)算法将电池在不同充放电循环次数下的阻抗数据从频域转化为时域。
步骤S203，根据所述n次循环中的每一次循环下的驰豫时间分布谱计算电池内部参数；其中，所述电池内部参数包括根据前述的建立方法所建立的电池等效电路模型中的至少一个元件的参数。
本实施方式中，在n次循环中的每一次循环下只需要根据驰豫时间分布谱计算电池内部参数即可，即电池等效电路模型可以根据前述的建立方法预先建立并预置在系统中，只要对电池等效电路模型中的参数进行计算即可。在其他实施方式中，还可以在n次循环中的每一次循环下建立其对应的电池等效电路模型(如图6所示)，并计算电池内部参数。
其中，所述电池内部参数包括所述电池等效电路模型中反映所述电池内部特性的至少一个元件的参数。例如，所述电池内部参数包括所述欧姆电阻R 0的阻值、所述第一电阻R 1的阻值、所述第一电容C 1的容值、所述第二电阻R 2的阻值、所述第二电容C 2的容值、所述第三电阻R 3的阻值、所述第三电容C 3的容值、所述电池接触电阻引起的极化过程的时间常数τ 1(τ 1＝R 1·C 1)、所述电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程的时间常数τ 2(τ 2＝R 2·C 2)或电池正极电荷传递电阻所引起的极化过程的时间常数τ 3(τ 3＝R 3·C 3)中的一个或多个。
结合如图6所建立的电等效电路模型和图9所示的10次循环下的驰豫时间分布谱，可以看出，代表正极电荷转移电阻引起的极化过程的时间常数τ 3的电池内部参数与电池的健康状态SOH有着明显的关联。
步骤S204，获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值。
请参阅图10，图10为10次循环下的电池健康状态的示意图。其中，图10中的横轴代表循环次数，纵轴代表电池健康状态。首先获取每次循环次数下的电池的当前额定放电容量；再用每次循环次数下的电池的当前额定放电容量除以电池初始状态下的额定放电容量，即可获得每一次循环下的电池健康状态。
步骤S205，对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
具体地，可以基于Matlab的回归分析算法对代表正极电荷转移电阻引起的极化过程的时间常数τ 3和电池健康状态SOH之间的关系进行分析，可以得出τ 3和电池SOH之间存在简单明显的线性关系，可以作为电池的内部参数来评估电芯的健康状态SOH，本实施方式中，二者之间的关系表达式为SOH(％)＝-174.53·τ 3+101.72。
根据上述公式可知，只要获得代表正极电荷转移电阻引起的极化过程的时间常数τ 3，再根据上述公式即可获悉电池当前的健康状态。
也即，在本实施方式中，所述电池内部参数为代表正极电荷转移电阻引起的极化过程的时间常数，所述电池健康状态与电池内部参数之间的关系表达式，具体为：电池健康状态与代表正极电荷转移电阻引起的极化过程的时间常数之间的关系表达式。
可以理解，随着电池的在线使用，电池的内部参数也在发生改变，因此为了提高电池健康状态的在线估算精度，请参阅图11，图11为本申请另一实施例中的电池健康状态的估算方法的流程图。与图7中的估算方法不同的是，图10中的电池健康状态的估算方法还包括如下步骤。
步骤S301，根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态。
其中，外部特征参数包括电流参数、电压参数或者温度参数中的至少一个。当外部特征参数达到特定阈值时，确定电池处于所述特定状态。
电池状态方程用于模拟电池不同工况下的电压-电流行为，本实施方式中，基于图6中的电池等效电路模型所建立的电池状态方程如下公式2：
Figure PCTCN2021070443-appb-000002
其中，该状态方程在充电时为“+”，放电时为“-”，V(t)是输出变量，R 0，R 1、τ 1，R 2、τ 2，R 3、τ 3为状态变量，且τ 1＝R 1·C 1、τ 2＝R 2·C 2、τ 3＝R 3·C 3。
在一实施方式中，当外部特征参数达到特定阈值时，首先对电池进行在线阻抗测试，并记录在线阻抗测试时的电压和电流数据。其中，在线阻抗测试根据实际条件可以选择频域法或时域法，在此不做限定。然后将在线阻抗测试时记录的电压和电流数据，代入上述电池状态方程中，通过参数辨识即可获取电池内部参数R 0，R 1、C 1，τ 1，R 2、C 2，τ 2，R 3、C 3，τ 3。
步骤S302，根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
具体地，将步骤S301中所获取的内部参数τ3代入步骤S205所获得的电池健康状态与电池内部参数之间的关系表达式，即可估算出电池的当前的在线健康状态。
本申请实施例所提出的电池健康状态SOH估算方法，将电池在每次循环下的电化学阻抗谱转化成驰豫时间分布普，并根据所述驰豫时间分布谱建立电池等效电路模型。即利用不同极化过程的弛豫时间不同，将电池内部不同的极化过程区分出来，可以得到能够反映电池内部不同极化过程等内部特性的等效电路模型，使得该等效电路模型具有明确的物理意义，且具有唯一性，进而提高了电池等效电路模型的建立精度。进一步地，基于n次循环下该等效电路模型的内部参数及n次循环下的电池健康状态，可以获得精度较高的电池健康状态与电池内部参数之间的关系表达式，可以提高后续在线估算电池健康状态SOH的精度。
请参阅图12，图12为本申请一实施例中的电池管理芯片的功能模块图。如图12所示，所述电池管理芯片200包括获取模块210、数据处理模块220、模型建立模块230以及存储模块240。
所述获取模块210用于获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数。
所述数据处理模块220用于根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱。
所述模型建立模块230用于根据所述驰豫时间分布谱建立电池等效电路模型。
所述存储模块240用于存储所述电池等效电路模型。
具体地，所述数据处理模块220用于根据所述电化学阻抗谱与弛豫时间分布之间的关系采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱；或者，所述数据处理模块220用于根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱。其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
所述模型建立模块230用于根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
请参阅图13，图13为本申请另一实施例中的电池管理芯片的功能模块图。与图11中的电池管理芯片200不同的是，本实施方式中的电池管理芯片200还包括数据处理模块250、检测模块260以及估算模块270。
所述获取模块210获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环。
所述数据处理模块220用于根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱。
所述数据处理模块220还用于根据所述n次循环中的每一次循环下的驰豫时间分布谱计算电池内部参数。所述电池内部参数包括根据前述建立方法所建立的电池等效电路模型中的至少一个元件的参数。
所述获取模块210还用于获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值。
所述数据处理模块250还用于对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
所述检测模块260用于检测电池的外部特征参数。
所述数据处理模块250还用于根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态。
所述状态估算模块270用于根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
所述存储模块240用于存储所述电池等效电路模型、内部参数、所述电池健康状态与电池内部参数之间的关系表达式、基于所述电池等效电路所建立的电池状态方程及所述检测的电流、电压即温度参数信息。
具体地，所述数据处理模块220用于根据所述n次循环中的每一次循环的电化学阻抗谱与弛豫时间分布之间的关系，采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得其对应的弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
所述模型建立模块230用于根据所述n次循环中的每一次循环下的所述电池内部不同动力学过程的驰豫时间，识别所述电池内部的不同极化过程；根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型；所述电池内部参数包括所述电池等效电路模型中反映所述电池内部特性的至少一个元件的参数。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的电池管理芯片的各个模块的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
需要说明的是，对于前述的各个方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本申请并不受所描述的动作顺序的限制，因为依据本申请，某一些步骤可以采用其他顺序或者同时进行。
在上述实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详细描述的部分，可以参见其他实施例的相关描述。
本申请实施例方法中的步骤可以根据实际需要进行顺序调整、合并和删减。
本申请提供的等效电路模型的建立方法和电池健康状态的估算方法可以在硬件、固件中实施，或者可以作为可以存储在例如只读存储记忆体(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，简称RAM)、软盘、硬盘或磁光盘的等计算机可读存储介质中的软件或计算机代码，或者可以作为原始存储在远程记录介质或非瞬时的机器可读介质上、通过网络下载并且存储在本地记录介质中的计算机代码，从而这里描述的方法可以利用通用计算机或特殊处理器或在诸如专用集成电路(ASIC)或现场可编程门阵列(FPGA)之类的可编程或专用硬件中以存储在记录介质上的软件来呈现。如本领域能够理解的，计算机、处理器、微处理器、控制器或可编程硬件包括存储器组件，例如，RAM、ROM、闪存等，当计算机、处理器或硬件实施这里描述的处理方法而存取和执行软件或计算机代码时，存储器组件可以存储或接收软件或计算机代码。另外，当通用计算机存取用于实施这里示出的处理的代码时，代码的执行将通用计算机转换为用于执行这里示出的处理的专用计算机。
其中，所述计算机可读存储介质可为固态存储器、存储卡、光碟等。所述计算机可读存储介质存储有程序指令而供计算机、手机、平板电脑、或者本申请的用电设备调用后执行前述的等效电路模型的建立方法及电池健康状态的估算方法。
以上是本申请实施例的实施方式，应当指出，对于本技术领域的普通技术人员来说，在不脱离本申请实施例原理的前提下，还可以做出若干改进和润饰，这些改进和润饰也视为本申请的保护范围。

Claims (19)

  1. 一种电池等效电路模型的建立方法，其特征在于，包括：
    获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数；
    根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱；
    根据所述驰豫时间分布谱建立电池等效电路模型。
  2. 如权利要求1所述的建立方法，其特征在于，所述根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱包括：
    根据所述电化学阻抗谱与弛豫时间分布之间的关系采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
  3. 如权利要求1所述的建立方法，其特征在于，所述根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱包括：
    根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
  4. 如权利要求2所述的建立方法，其特征在于，所述根据所述驰豫时间分布谱建立电池等效电路模型包括：
    根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；
    根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；
    根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
  5. 如权利要求1-4任一项所述的建立方法，其特征在于，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。
  6. 如权利要求5所述的建立方法，其特征在于，所述电池等效电路模型包括：
    电压源，用于表征电池的开路电压；
    欧姆电阻，与所述电压源的正极电连接，用于表征电池的欧姆内阻；
    第一电路单元，与所述欧姆电阻电连接，并包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
    第二电路单元，与所述第一电路单元电连接，并包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及负极电荷传递电阻所引起的极化过程；以及
    第三电路单元，电连接于所述第二电路单元和所述电压输出端正极之间，并包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程。
  7. 一种电池健康状态的估算方法，其特征在于，包括：
    获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环；
    根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱；
    根据所述n次循环中的每一次循环下的驰豫时间分布谱计算电池内部参数；其中，所述电池内部参数包括根据权利要求1-5任一项所述的建立方法所建立的电池等效电路模型中的至少一个元件的参数；
    获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值；
    对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
  8. 如权利要求7所述的估算方法，其特征在于，所述电池等效电路模型包括：
    欧姆电阻，用于表征电池的欧姆内阻；
    第一电路单元，包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
    第二电路单元，包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程；以及
    第三电路单元，包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程；
    所述电池内部参数包括所述欧姆电阻的阻值、所述第一电阻的阻值、所述第一电容的容值、所述第二电阻的阻值、所述第二电容的容值、所述第三电阻的阻值、所述第三电容的容值、所述电池接触电阻引起的极化过程的时间常数、所述电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程的时间常数或电池正极电荷传递电阻所引起的极化过程的时间常数中的一个或多个。
  9. 如权利要求7或8所述的估算方法，其特征在于，所述估算方法还包括：
    根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态；
    根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
  10. 一种电池管理芯片，其特征在于，包括：
    获取模块，用于获取电池在预设状态参数下的电化学阻抗谱；其中，所述预设状态参数包括预设温度参数和预设荷电状态参数；
    数据处理模块，用于根据所述电化学阻抗谱计算所述电池的驰豫时间分布谱；以及
    模型建立模块，用于根据所述驰豫时间分布谱建立电池等效电路模型。
  11. 如权利要求10所述的电池管理芯片，其特征在于，所述数据处理模块用于根据所述电化学阻抗谱与弛豫时间分布之间的关系采用驰豫时间分布的分析方法将所述电化学阻抗谱从频域转化为时域，从而获得所述弛豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
  12. 如权利要求10所述的电池管理芯片，其特征在于，所述数据处理模块用于根据所述电化学阻抗谱与弛豫时间分布之间的关系，通过去卷积的方法得到所述驰豫时间分布谱；其中，所述弛豫时间分布谱中的不同谱峰对应所述电池内部不同动力学过程的驰豫时间。
  13. 如权利要求11所述的电池管理芯片，其特征在于，所述模型建立模块用于根据所述电池内部不同动力学过程的驰豫时间识别所述电池内部的不同极化过程；再根据所述电池内部的不同极化过程确定所述电池内部的不同内阻；再根据所述电池内部的不同内阻建立反映所述电池内部特性的电池等效电路模型。
  14. 如权利要求10-13任一项所述的电池管理芯片，其特征在于，所述电池等效电路模型包括一个电阻元件及M个电阻电容并联的电路单元；其中，M等于所述弛豫时间分布谱中预设频率以上峰谱的个数。
  15. 如权利要求14所述的电池管理芯片，其特征在于，所述电池等效电路模型包括：
    电压源，用于表征电池的开路电压；
    欧姆电阻，与所述电压源的正极电连接，用于表征电池的欧姆内阻；
    第一电路单元，与所述欧姆电阻电连接，并包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
    第二电路单元，与所述第一电路单元电连接，并包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及负极电荷传递电阻所引起的极化过程；以及
    第三电路单元，电连接于所述第二电路单元和所述电压输出端正极之间，并包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程。
  16. 一种电池管理芯片，其特征在于，包括：
    获取模块，用于获取电池n次循环下的各个电化学阻抗谱；所述各个电化学阻抗谱包括各个预设荷电状态和各个温度下的电池的电化学阻抗谱；所述n大于0小于等于N，N为所述电池的循环寿命，所述n次循环是指0至N次循环中选取的n次循环；所述获取模块还用于获取所述n次循环中的每一次循环下的电池健康状态；其中，所述每一次循环下的电池健康 状态为当前循环下的所述电池的额定放电容量与所述电池初始状态下的额定放电容量的比值；以及
    数据处理模块，用于根据所述n次循环中的每一次循环的所述电化学阻抗谱计算其对应的驰豫时间分布谱；
    所述数据处理模块还用于根据所述n次循环中的每一次循环下的驰豫时间分布谱计算电池内部参数；其中，所述电池内部参数包括根据权利要求1-5任一项所述的建立方法所建立的电池等效电路模型中的至少一个元件的参数；
    所述数据处理模块还用于对所述n次循环下的电池内部参数及所述n次循环下的电池健康状态进行参数拟合，以获得电池健康状态与电池内部参数之间的关系表达式。
  17. 如权利要求16所述的电池管理芯片，其特征在于，所述电池等效电路模型包括：
    欧姆电阻，用于表征电池的欧姆内阻；
    第一电路单元，包括并联的第一电阻和第一电容，用于表征电池接触电阻所引起的极化过程；
    第二电路单元，包括并联的第二电阻和第二电容，用于表征电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程；以及
    第三电路单元，包括并联的第三电阻和第三电容，用于表征电池正极电荷传递电阻所引起的极化过程；
    所述电池内部参数包括所述欧姆电阻的阻值、所述第一电阻的阻值、所述第一电容的容值、所述第二电阻的阻值、所述第二电容的容值、所述第三电阻的阻值、所述第三电容的容值、所述电池接触电阻引起的极化过程的时间常数、所述电池负极固体电解液界面膜及电荷传递电阻所引起的极化过程的时间常数或电池正极电荷传递电阻所引起的极化过程的时间常数中的一个或多个。
  18. 如权利要求16或17所述的电池管理芯片，其特征在于，所述电池管理芯片还包括状态估算模块；
    所述数据处理模块还用于根据所述电池等效电路模型的电池状态方程获取电池在特定状态下的电池内部参数；所述特定状态为电池的外部特征参数所处的预设状态；
    所述状态估算模块用于根据特定状态下的电池内部参数及所述电池健康状态与电池内部参数之间的关系表达式获得所述电池在特定状态下的电池的健康状态。
  19. 一种用电设备，其特征在于，包括电池以及如权利要求10-15任一项所述的充电管理芯片或者如权利要求16-18任一项所述的电池管理芯片；所述电池管理芯片与所述电池电连接，并对所述电池进行监测与管理。
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