CN112462269A - Battery health state estimation method and device based on online alternating current impedance - Google Patents
Battery health state estimation method and device based on online alternating current impedance Download PDFInfo
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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
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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]
- G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
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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]
- G01R31/392—Determining battery ageing or deterioration, e.g. state of health
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Abstract
The invention provides a method and a device for estimating the state of health of a battery based on online alternating-current impedance, which solve the problem that the existing method for estimating the state of health of the battery is only suitable for the offline state of the battery and is not suitable for the dynamic characteristic of the battery. The method and the device for estimating the state of health of the battery based on the online alternating-current impedance, provided by the embodiment of the invention, comprise the following steps: measuring the on-line alternating current impedance of the battery; converting the online alternating current impedance into an equivalent element parameter; and obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
Description
Technical Field
The invention relates to the technical field of batteries, in particular to a battery health state estimation method and device based on online alternating-current impedance.
Background
In recent years, electrochemical energy storage technologies represented by lithium ion batteries are rapidly developed, and the technical economy is remarkably improved. Under the common promotion of global energy storage policies, technologies and markets, as far as 2019 s, according to the statistics of a global energy storage project library of the central-Guancun energy storage industry and technology alliance (CNESA), 13.6GW (not containing a pumped storage unit) is installed in a global energy storage system, wherein 9520.5MW is installed in the electrochemical energy storage system, and the accumulated installed amount of lithium ion batteries is the largest in scale and is 8453.9MW in various electrochemical energy storage technologies, so that huge application potential is displayed. The lithium ion battery monomer is a basic element forming an energy storage battery system, and the health state of the lithium ion battery in the energy storage system is directly related to the residual service life and the operation safety of the energy storage system, so that the accurate estimation of the degradation state of the lithium ion battery and the identification of the lithium ion battery fault are of great importance to the energy storage system.
At present, methods for estimating health status mainly include an experience-based method, a performance-based method, a mechanism-based method, a feature-based method, a data-driven method and the like, but these methods are methods for detecting the offline state of a lithium ion battery and are not suitable for the dynamic characteristics of the lithium ion battery, and the understanding of the dynamic characteristics of the battery is to expect that the functional state of the battery can be recognized more accurately from the application point of view, manage the battery efficiently and safely, and ensure the long-term safe and stable operation of the battery, while a "static" research mode is not suitable for the field of battery application, is more focused on basic research, and is difficult to implement in practical engineering application. For example, the Electrochemical Impedance Spectroscopy (EIS) technique is an electrical measurement method using a small-amplitude sine wave as a disturbance signal, and information of a test system in the aspects of materials science, dynamics, reaction mechanism and the like can be obtained by combining relevant theories such as an Electrochemical theory and the like. Electrochemical Impedance Spectroscopy (EIS) has the advantage of reflecting the electrochemical reaction mechanism inside the battery in situ, without damage, and through a suitable equivalent circuit, can also be used to analyze the source of battery impedance and to find out the cause of battery failure. In addition, because direct current and alternating current signals are simultaneously loaded on the battery, the battery state is difficult to distinguish and detect, the noise is large, and the test result is difficult to analyze. Based on the above factors, the ac impedance spectrum is not suitable for direct use in online state sensing of the battery.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for estimating a state of health of a battery based on online ac impedance, which solve the problem that the current method for estimating a state of health of a battery is only applicable to an offline state of the battery, and is not applicable to dynamic characteristics of the battery.
The method and the device for estimating the state of health of the battery based on the online alternating-current impedance, provided by the embodiment of the invention, comprise the following steps: measuring the on-line alternating current impedance of the battery; converting the online alternating current impedance into an equivalent element parameter; and obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
In one embodiment, before obtaining the state of health of the battery based on the equivalent element parameter and the correlation with the state of health, the method includes: establishing an association relationship, comprising: selecting the online alternating current impedance frequency of the battery, and superposing the online alternating current impedance frequency to form an excitation signal; carrying out charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period; after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery; and establishing an incidence relation based on the online alternating current impedance data and the health states of different cycle times.
In one embodiment, after each calibration is finished, in the charging process of the battery, obtaining online alternating current impedance data under different preset time periods based on the excitation signal includes: after each calibration is finished, charging the battery; and in the charging process, the excitation signal is applied to the battery under a preset charge state or energy state, and online alternating current impedance data is obtained.
In one embodiment, correlating the online ac impedance data with the health status for different numbers of cycles comprises: constructing an equivalent circuit diagram; obtaining equivalent element parameters based on the equivalent circuit diagram and the online alternating current impedance data under a plurality of cycle periods; and carrying out nonlinear fitting on the equivalent element parameters and the health state to establish an association relationship.
In one embodiment, obtaining equivalent element parameters based on the equivalent circuit and the on-line ac impedance data over a plurality of cycle periods comprises: and converting the on-line alternating-current impedance data under a plurality of cycle periods into equivalent element parameters by using the equivalent circuit diagram and a least square method, and extracting the equivalent element parameters.
In one embodiment, the equivalent circuit comprises: the charge transfer internal resistance is connected in series with the Weber impedance, then connected in parallel with the constant phase angle element, and then connected in series with the inductor and the ohmic internal resistance.
In one embodiment, the online AC impedance frequency is selected in the range of 10kHz to 0.01 Hz.
An online ac impedance-based battery state of health estimation apparatus, comprising: a measurement module configured to measure an online alternating current impedance of the battery; a conversion module configured to convert the online alternating current impedance into an equivalent element parameter; and the processing module is configured to obtain the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
In an embodiment of the present invention, the processing module is further configured to:
after each calibration is finished, charging the battery;
and in the charging process, the excitation signal is applied to the battery under a preset charge state or energy state, and online alternating current impedance data is obtained.
In an embodiment of the present invention, the processing module is further configured to:
selecting the online alternating current impedance frequency of the battery, and superposing the online alternating current impedance frequency to form an excitation signal;
carrying out charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period;
after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery;
and establishing an incidence relation based on the online alternating current impedance data and the health states of different cycle times.
In an embodiment of the present invention, the processing module is further configured to:
constructing an equivalent circuit diagram;
obtaining equivalent element parameters based on the equivalent circuit diagram and the online alternating current impedance data under a plurality of cycle periods;
and carrying out nonlinear fitting on the equivalent element parameters and the health state to establish an association relationship.
An electronic device comprising a memory and a processor, the memory configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement any of the online ac impedance-based battery state of health estimation methods described above.
A computer-readable storage medium having a computer program stored therein, the computer program when executed by a processor being configured to implement any of the above-mentioned online ac impedance-based battery state of health estimation methods.
The embodiment of the invention provides a method and a device for estimating the state of health of a battery based on online alternating-current impedance, wherein the method for estimating the state of health of the battery based on the online alternating-current impedance comprises the following steps: measuring the on-line alternating current impedance of the battery; converting the online alternating current impedance into an equivalent element parameter; and obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health. According to the invention, the online alternating current impedance is tested in the battery working engineering, the equivalent circuit model is combined, and the health state of the lithium ion battery is estimated by using a nonlinear fitting method, so that the online prediction of the health state of the lithium ion battery is realized, the estimation time of the health state of the battery is shortened, and the estimation accuracy is improved.
Drawings
Fig. 1 is a schematic flow chart of a method for estimating a state of health of a battery based on online ac impedance according to an embodiment of the present invention.
Fig. 2 is a schematic flow chart of a method for establishing an association relationship between an equivalent element and a battery state of health according to an embodiment of the present invention.
Fig. 3 is an equivalent circuit diagram according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a battery state of health estimation device based on online ac impedance according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
fig. 1 is a schematic flow chart of a method for estimating a state of health of a battery based on online ac impedance according to an embodiment of the present invention.
As shown in fig. 1, the method for estimating the state of health of a battery based on online ac impedance according to the present invention includes:
step S01: the on-line ac impedance of the cell was measured. Wherein, optionally, the battery may be a lithium battery.
Step S02: and converting the online alternating-current impedance into an equivalent element parameter.
And step S03, obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
Fig. 2 is a schematic flow chart of a method for establishing an association relationship between an equivalent element and a battery state of health according to an embodiment of the present invention.
As shown in fig. 2, before obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health, the method includes: establishing an association relationship, comprising:
and S031, selecting the on-line alternating current impedance frequency of the battery, and superposing the on-line alternating current impedance frequency to form an excitation signal. And selecting the frequency of the online alternating current impedance, and superposing the selected frequency, namely taking the excitation signal of the online alternating current impedance as a superposed signal.
Optionally, the online ac impedance frequency is selected in the range of 10kHz to 0.01 Hz. The selection range of the online alternating current impedance frequency can be determined according to actual requirements, and the selection range of the online alternating current impedance frequency is not limited by the invention.
And S032, performing charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period. The calibration method can be executed according to the 'GB/T36276-2018 lithium ion battery for power storage'.
And step S033, after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery. And charging the battery, applying the excitation signal in the step S031 to the battery in a specific charge state or energy state in the charging process, obtaining online alternating current impedance data, and testing a plurality of groups of online alternating current impedance data under different cycle periods by using the method.
Alternatively, the charging condition can be constant current of 0.1C-C or constant power of 0.1P-3P. The charging condition can be set according to actual requirements, and the charging condition is not limited by the invention.
And S034, establishing an incidence relation based on the online alternating current impedance data and the health states of different cycle times. An equivalent circuit diagram is constructed, specifically comprising series and parallel connection of several elements of inductance (L), ohmic internal resistance (Rs), SEI film internal resistance (Rsei), charge transfer internal resistance (Rct), constant phase angle element (Q) and Weber impedance (W), wherein the several equivalent elements can be connected in series and parallel at will, in a specific preferred embodiment, as shown in FIG. 3, the equivalent circuit diagram can be formed by connecting the charge transfer internal resistance and the Weber impedance in series, then connecting the charge transfer internal resistance and the constant phase angle element in parallel, and then connecting the charge transfer internal resistance and the ohmic internal resistance in series. Converting online alternating current impedance data under a plurality of cycle periods into equivalent element parameters by using the constructed equivalent circuit through a least square method, extracting the equivalent element parameters, and carrying out nonlinear fitting on the equivalent element parameters and a health State (SOH) to establish an association relation.
According to the invention, the online alternating current impedance is tested in the battery working engineering, the equivalent circuit model is combined, and the health state of the lithium ion battery is estimated by using a nonlinear fitting method, so that the online prediction of the health state of the lithium ion battery is realized, the estimation time of the health state of the battery is shortened, and the estimation accuracy is improved.
Example two:
the method comprises the following steps: selecting 21 frequencies in the range of 1000 Hz-0.1 Hz of online alternating-current impedance frequency, and superposing the 21 frequencies into a waveform;
step two: placing the lithium ion battery in a constant temperature environment of 25 ℃, standing for one hour, performing 1C charge-discharge circulation on the lithium ion battery, performing calibration once every 100 weeks of circulation, optionally performing calibration according to the 'lithium ion battery for power storage of GB/T36276-2018', and recording the calibrated capacity.
Step three: after the calibration in the second step is finished, exciting the battery by using the waveform in the first step in the charging process of the battery, and measuring on-line alternating current impedance data in a 60% charge state;
step four: constructing an equivalent circuit diagram, fitting the on-line alternating current impedance data with different cycle times in the third step into equivalent element parameters by using an equivalent circuit, and extracting the charge transfer internal resistance;
step five: performing nonlinear fitting on the internal charge transfer resistance and the health states with different cycle times to obtain an associated relation between the health State (SOH) and the internal charge transfer resistance (Rct), wherein optionally, the relation may be: SOH ═ 1.351-0.796 × Rct +0.266 × Rct2；
Step six: and (5) testing the online alternating current impedance of a certain battery of the same type in the state of charge of 60%, performing equivalent circuit fitting to obtain a value of the internal resistance to charge transfer (Rct), and substituting the value into the correlation relational expression in the step five to obtain the state of health SOH of 0.954.
According to the invention, the online alternating current impedance is tested in the battery working engineering, the equivalent circuit model is combined, and the health state of the lithium ion battery is estimated by using a nonlinear fitting method, so that the online prediction of the health state of the lithium ion battery is realized, the estimation time of the health state of the battery is shortened, and the estimation accuracy is improved.
Example three:
the battery state of health estimation device 100 comprises a measurement module 10, a conversion module 20 and an alternating current impedance conversion equivalent element parameter. Wherein the measurement module 10 is configured to measure an on-line ac impedance of the battery; the conversion module 20 is configured to convert the online ac impedance into an equivalent element parameter; the processing module 30 is configured to derive a state of health of the battery based on the equivalent element parameters and the correlation to the state of health.
After the measurement module 10 measures the on-line ac impedance of the battery, the conversion module 20 converts the on-line ac impedance into an equivalent element parameter, and then the processing module 30 obtains the state of health of the battery based on the association relationship between the equivalent element parameter and the equivalent element and the state of health of the battery.
The processing module 30 is further configured to: after each calibration is finished, charging the battery; and in the charging process, the excitation signal is applied to the battery under a preset charge state or energy state, and online alternating current impedance data is obtained.
The processing module 30 is further configured to:
selecting the online alternating current impedance frequency of the battery, and superposing the online alternating current impedance frequency to form an excitation signal; carrying out charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period; after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery;
the processing module 30 is further configured to: constructing an equivalent circuit diagram; obtaining equivalent element parameters based on the equivalent circuit diagram and the online alternating current impedance data under a plurality of cycle periods; and carrying out nonlinear fitting on the equivalent element parameters and the health state to establish an association relationship.
The processing module 30 selects the on-line ac impedance frequency of the battery and superimposes the on-line ac impedance frequency to form the excitation signal. And selecting the frequency of the online alternating current impedance, and superposing the selected frequency, namely taking the excitation signal of the online alternating current impedance as a superposed signal. Then, the processing module 30 performs charge and discharge cycles on the battery, and calibrates the battery every preset cycle period. The calibration method can be executed according to the 'GB/T36276-2018 lithium ion battery for power storage'. Then, after each calibration is finished, the processing module 30 obtains online ac impedance data in different preset time periods based on the excitation signal in the charging process of the battery. The method comprises the steps of charging a battery, applying an excitation signal to the battery under a specific charge state or energy state in the charging process, obtaining online alternating current impedance data, and testing a plurality of groups of online alternating current impedance data under different cycle periods by using the method. Finally, the processing module 30 establishes an association relationship based on the online ac impedance data and the health status for different cycle times. And constructing an equivalent circuit diagram, specifically comprising series and parallel connection of several elements of an inductor (L), an ohmic internal resistance (Rs), an SEI (internal resistance of SEI) film, a charge transfer internal resistance (Rct), a constant phase angle element (Q) and a Weber impedance (W), wherein the several equivalent elements can be randomly connected in series and parallel, and optionally, the equivalent circuit diagram can be that the charge transfer internal resistance is connected in series with the Weber impedance, then connected in parallel with the constant phase angle element, and then connected in series with the inductor and the ohmic internal resistance. Converting online alternating current impedance data under a plurality of cycle periods into equivalent element parameters by using the constructed equivalent circuit through a least square method, extracting the equivalent element parameters, and carrying out nonlinear fitting on the equivalent element parameters and a health State (SOH) to establish an association relation.
According to the invention, the online alternating current impedance is tested in the battery working engineering, the equivalent circuit model is combined, and the health state of the lithium ion battery is estimated by using a nonlinear fitting method, so that the online prediction of the health state of the lithium ion battery is realized, the estimation time of the health state of the battery is shortened, and the estimation accuracy is improved.
Example four:
fig. 4 is a schematic structural diagram of a battery state of health estimation device based on online ac impedance according to an embodiment of the present invention.
As shown in fig. 4, the present embodiment provides an electronic device, which may include a memory and a processor, where the memory stores a computer program, and the computer program is executed by the processor to implement the online ac impedance-based battery state of health estimation method according to one embodiment. It is to be appreciated that the electronic device can also include input/output (I/O) interfaces, as well as communication components.
Wherein, the processor is used for executing the online ac impedance-based battery state of health estimation method in the first embodiment. All or part of the steps in (a). The memory is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.
The Processor may be an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is configured to execute the method for estimating the health status of the battery based on the on-line ac impedance in the first embodiment.
The Memory may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk.
Example five:
the present embodiments also provide a computer-readable storage medium. Each functional unit in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium.
Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention.
And the aforementioned storage medium includes: flash memory, hard disk, multimedia card, card type memory (e.g., SD or DX memory, etc.), Random Access Memory (RAM), Static Random Access Memory (SRAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, server, APP application mall, etc., various media that can store program check codes, on which computer programs are stored, which when executed by a processor can implement the following method steps:
step S01: measuring the on-line alternating current impedance of the battery;
step S02: converting the online alternating current impedance into an equivalent element parameter;
step S03: and obtaining the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
The specific implementation and the resulting effects can be described in the first embodiment, and the present invention is not described herein again.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The foregoing describes the general principles of the present application in conjunction with specific embodiments, however, it is noted that the advantages, effects, etc. mentioned in the present application are merely examples and are not limiting, and they should not be considered essential to the various embodiments of the present application. Furthermore, the foregoing disclosure of specific details is for the purpose of illustration and description and is not intended to be limiting, since the foregoing disclosure is not intended to be exhaustive or to limit the disclosure to the precise details disclosed.
The block diagrams of devices, apparatuses, systems referred to in this application are only given as illustrative examples and are not intended to require or imply that the connections, arrangements, configurations, etc. must be made in the manner shown in the block diagrams. These devices, apparatuses, devices, systems may be connected, arranged, configured in any manner, as will be appreciated by those skilled in the art.
It should also be noted that in the devices, apparatuses, and methods of the present application, the components or steps may be decomposed and/or recombined. These decompositions and/or recombinations are to be considered as equivalents of the present application.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the application. Thus, the present application is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indicators in the embodiments of the present application (such as upper, lower, left, right, front, rear, top, bottom … …) are only used to explain the relative positional relationship between the components, the movement, etc. in a particular posture (as shown in the drawings), and if the particular posture is changed, the directional indicator is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Furthermore, reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims. The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and the like that are within the spirit and principle of the present invention are included in the present invention. The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and the like that are within the spirit and principle of the present invention are included in the present invention.
Claims (13)
1. The method for estimating the state of health of the battery based on the online alternating-current impedance is characterized by comprising the following steps of:
measuring the on-line alternating current impedance of the battery;
converting the online alternating current impedance into an equivalent element parameter;
and obtaining the state of health of the battery based on the association relationship between the equivalent element parameters and the equivalent element and the state of health of the battery.
2. The online ac impedance-based battery state of health estimation method of claim 1, wherein before obtaining the state of health of the battery based on the correlation between the equivalent element parameter and the equivalent element and the state of health of the battery, the method further comprises:
selecting the online alternating current impedance frequency of the battery, and superposing the online alternating current impedance frequency to form an excitation signal;
carrying out charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period;
after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery;
and establishing an incidence relation based on the online alternating current impedance data and the health states of different cycle times.
3. The method for estimating the state of health of the battery based on the on-line ac impedance according to claim 2, wherein after each calibration is finished, in the charging process of the battery, the on-line ac impedance data under different preset time periods are obtained based on the excitation signal, and the method comprises:
after each calibration is finished, charging the battery;
and in the charging process, the excitation signal is applied to the battery under a preset charge state or energy state, and online alternating current impedance data is obtained.
4. The online ac impedance-based battery state of health estimation method of claim 2, wherein correlating the online ac impedance data with the state of health for different cycle times comprises:
constructing an equivalent circuit diagram;
obtaining equivalent element parameters based on the equivalent circuit diagram and the online alternating current impedance data under a plurality of cycle periods;
and carrying out nonlinear fitting on the equivalent element parameters and the health state to establish an association relationship.
5. The online ac impedance-based battery state of health estimation method of claim 4, wherein obtaining equivalent element parameters based on the equivalent circuit and the online ac impedance data over a plurality of cycle periods comprises: and converting the on-line alternating-current impedance data under a plurality of cycle periods into equivalent element parameters by using the equivalent circuit diagram and a least square method, and extracting the equivalent element parameters.
6. The online ac impedance-based battery state of health estimation method of claim 4, wherein the equivalent circuit comprises: the charge transfer internal resistance is connected in series with the Weber impedance, then connected in parallel with the constant phase angle element, and then connected in series with the inductor and the ohmic internal resistance.
7. The online ac impedance-based battery state of health estimation method of claim 2, wherein the online ac impedance frequency is selected in the range of 10kHz to 0.01 Hz.
8. An online ac impedance-based battery state of health estimation apparatus, comprising:
a measurement module configured to measure an online alternating current impedance of the battery;
a conversion module configured to convert the online alternating current impedance into an equivalent element parameter;
and the processing module is configured to obtain the state of health of the battery based on the equivalent element parameters and the correlation with the state of health.
9. The online ac impedance battery state of health estimation device of claim 8, wherein the processing module is further configured to:
after each calibration is finished, charging the battery;
and in the charging process, the excitation signal is applied to the battery under a preset charge state or energy state, and online alternating current impedance data is obtained.
10. The online ac impedance battery state of health estimation device of claim 8, wherein the processing module is further configured to:
selecting the online alternating current impedance frequency of the battery, and superposing the online alternating current impedance frequency to form an excitation signal;
carrying out charge-discharge circulation on the battery, and calibrating the battery at intervals of a preset circulation period;
after each calibration is finished, obtaining online alternating current impedance data under different preset time periods based on the excitation signal in the charging process of the battery;
and establishing an incidence relation based on the online alternating current impedance data and the health states of different cycle times.
11. The online ac impedance battery state of health estimation device of claim 9, wherein the processing module is further configured to:
constructing an equivalent circuit diagram;
obtaining equivalent element parameters based on the equivalent circuit diagram and the online alternating current impedance data under a plurality of cycle periods;
and carrying out nonlinear fitting on the equivalent element parameters and the health state to establish an association relationship.
12. An electronic device comprising a memory and a processor, the memory configured to store one or more computer instructions, wherein the one or more computer instructions, when executed by the processor, implement the online ac impedance-based battery state of health estimation method of claims 1-7.
13. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, is adapted to carry out the online ac impedance-based battery state of health estimation method according to any one of claims 1 to 7.
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