CN113093039A - Lithium ion battery impedance model and parameter identification method - Google Patents
Lithium ion battery impedance model and parameter identification method Download PDFInfo
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- HBBGRARXTFLTSG-UHFFFAOYSA-N Lithium ion Chemical compound [Li+] HBBGRARXTFLTSG-UHFFFAOYSA-N 0.000 title claims abstract description 90
- 229910001416 lithium ion Inorganic materials 0.000 title claims abstract description 90
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000001453 impedance spectrum Methods 0.000 claims description 51
- 238000000157 electrochemical-induced impedance spectroscopy Methods 0.000 claims description 36
- 230000007613 environmental effect Effects 0.000 claims description 20
- 230000001419 dependent effect Effects 0.000 claims description 9
- 238000012360 testing method Methods 0.000 claims description 9
- 101100042631 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) SIN3 gene Proteins 0.000 claims description 8
- 230000001939 inductive effect Effects 0.000 claims description 4
- QHGJSLXSVXVKHZ-UHFFFAOYSA-N dilithium;dioxido(dioxo)manganese Chemical compound [Li+].[Li+].[O-][Mn]([O-])(=O)=O QHGJSLXSVXVKHZ-UHFFFAOYSA-N 0.000 description 13
- 239000003990 capacitor Substances 0.000 description 11
- 230000009471 action Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 239000006185 dispersion Substances 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000009828 non-uniform distribution Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000007784 solid electrolyte Substances 0.000 description 1
- 230000003746 surface roughness Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
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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]
- G01R31/389—Measuring internal impedance, internal conductance or related variables
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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]
- G01R31/3644—Constructional arrangements
- G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
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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]
- G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
Abstract
The application discloses a lithium ion battery impedance model and a parameter identification method, and belongs to the technical field of power batteries. According to the embodiment of the application, the precision of the lithium ion battery impedance model is greatly improved, and the battery model with the lithium ion battery impedance model can be simulated more truly.
Description
Technical Field
The application relates to the technical field of power batteries, in particular to a lithium ion battery impedance model and a parameter identification method.
Background
On a new energy power assembly test rack and a hardware-in-loop HIL rack, a battery model plays an extremely important role, and the precision of the battery model has great influence on simulating the endurance mileage and the power of a whole vehicle test. Meanwhile, the lithium ion battery impedance model in the battery model is taken as an important component, and the accuracy of the lithium ion battery impedance model directly influences the accuracy degree of the battery model.
In the related art, a second-order RC equivalent circuit model is used as a battery model, as shown in fig. 2, the second-order RC equivalent circuit model includes an impedance Rb and a second-order RC circuit, the second-order RC circuit includes an impedance R1, an impedance R2, a capacitor C1 and a capacitor C2, the impedance R1 is connected in series with the impedance R2, the capacitor C1 is connected in parallel with the impedance R1, and the capacitor C2 is connected in parallel with the impedance R2. The second-order RC equivalent circuit model is also a lithium ion battery model adopted by most new energy power assembly rack battery simulators and hardware-in-loop HIL racks, although the lithium ion battery model is simple in structure and can preliminarily simulate the characteristics of the lithium ion battery. But the accuracy of the simulation is still to be improved compared to a real battery.
Disclosure of Invention
The embodiment of the application provides a lithium ion battery impedance model and a parameter identification method, and aims to solve the problem that the impedance model in a battery model in the related art is lack of precision.
In a first aspect, a lithium ion battery impedance model is provided, which comprises an inductor L, an impedance Rb, and a second-order RC circuit connected in series in sequence, and each-order PC circuit is a parallel circuit.
In some embodiments, the second order RC circuit includes an impedance R1, an impedance R2, a constant phase angle element CPE1, and a constant phase angle element CPE2, the impedance R1 being in series with the impedance R2, the constant phase angle element CPE1 being in parallel with the impedance R1, and the constant phase angle element CPE2 being in parallel with the impedance R2.
In some embodiments, the inductance L is a porous electrode inductive reactance.
In a second aspect, a method for identifying parameters of an impedance model of a lithium ion battery is also provided, which includes the steps of:
providing a battery to be tested with lithium ion battery impedance in advance, and establishing a battery circuit with a lithium ion battery impedance model according to the battery to be tested;
determining the battery capacity of the battery to be tested;
adjusting the battery to be tested to an appointed state, and exciting the battery to be tested by adopting sine wave voltage signals with different frequencies to obtain an impedance spectrum EIS of the battery to be tested in the state;
calling the battery circuit by using impedance spectrum EIS analysis software, assigning values to each impedance element in a lithium ion battery impedance model of the battery circuit, and obtaining the impedance spectrum EIS of the battery circuit after assignment and parameters of each impedance element;
comparing the assigned impedance spectrum EIS of the battery circuit with the impedance spectrum EIS of the battery to be tested;
updating the assignment of each impedance element according to the comparison result until the impedance spectrum EIS of the battery circuit and the impedance spectrum EIS of the battery to be tested meet the fitting condition, and outputting the finally obtained parameters of each impedance element;
and taking the output parameters of the impedance elements as the parameters of the lithium ion battery impedance model in a specified state.
In some embodiments, the dependent variable of the state includes an SOC state, and the specific step of adjusting the battery to be tested to a specific state includes:
and adjusting the SOC state of the battery to be tested to a specified SOC state.
In some embodiments, the dependent variables of the state include SOC state and ambient temperature, and specifically include the steps of:
and adjusting the SOC state of the battery to be tested to a specified SOC state, and measuring corresponding parameters at different environmental temperatures in the specified SOC state.
In some embodiments, the dependent variable of the state further includes a cycle number, which specifically includes:
and adjusting the cycle number of the battery to be tested to a specified cycle number, and measuring corresponding parameters of different SOC states and different environmental temperatures under the specified cycle number.
In some embodiments, further comprising:
according to all the output parameters, a three-dimensional data table is created, and the three dimensions are SOC state, environment temperature and cycle number;
and determining other parameters under the SOC state, the ambient temperature and the cycle number by adopting an interpolation method based on the three-dimensional data table.
In some embodiments, after adjusting the battery to be tested to a specified state, before exciting the battery to be tested by using sine wave voltage signals with different frequencies, the method further includes the steps of:
and standing the battery to be tested at a specified environmental temperature for more than 6 hours if the environmental temperature is above 25 ℃, or for more than 24 hours if the environmental temperature is less than 25 ℃.
In some embodiments, the initial assignment is of the same order of magnitude as the individual impedance elements in the lithium ion battery impedance.
The beneficial effect that technical scheme that this application provided brought includes: the precision of the lithium ion battery impedance model is improved, and the battery model with the lithium ion battery impedance model is simulated more truly.
The embodiment of the application provides a lithium ion battery impedance model, an inductance L is additionally arranged on the basis of a conventional lithium ion battery impedance model, the structure is simple, the overall error rate of the lithium ion battery impedance model and an actually measured impedance spectrum in the embodiment of the application is 0.952%, the overall error rate of the conventional lithium ion battery impedance model and the actually measured impedance spectrum is 16.8%, the improvement of the precision of the improved lithium ion battery impedance model is obviously seen, and the battery model with the lithium ion battery impedance model is simulated more truly.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a circuit structure diagram of an impedance model of a lithium ion battery according to an embodiment of the present disclosure;
FIG. 2 is a circuit diagram of a conventional impedance model of a lithium ion battery;
fig. 3 is a schematic flowchart of a parameter identification method for a lithium ion battery impedance model according to an embodiment of the present disclosure;
FIG. 4 is an impedance spectrum EIS of a 25AH lithium manganate battery with a temperature of 25 ℃/SOC of 50% after Nyquist frequency treatment;
fig. 5 is a comparison between a fitting result of the impedance model of the lithium ion battery provided in the embodiment of the present application and an actually measured impedance spectrum;
fig. 6 shows impedance element parameter values identified by the lithium ion battery impedance model according to the embodiment of the present disclosure;
FIG. 7 is a comparison of a fitting result of a conventional lithium ion battery impedance model with a measured impedance spectrum;
fig. 8 shows values of impedance element parameters identified by a conventional lithium ion battery impedance model.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all 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 application.
The embodiment of the application provides a lithium ion battery impedance model, which can improve the precision of the lithium ion battery impedance model and simulate a battery model with the lithium ion battery impedance model more truly.
As shown in fig. 1, an impedance model of a lithium ion battery includes an inductor L, an impedance Rb, and a second-order RC circuit connected in series in sequence, and each of the second-order RC circuits is a parallel circuit.
Further, the second order RC circuit includes an impedance R1, an impedance R2, a constant phase angle element CPE1, and a constant phase angle element CPE2, the impedance R1 being connected in series with the impedance R2, the constant phase angle element CPE1 being connected in parallel with the impedance R1, and the constant phase angle element CPE2 being connected in parallel with the impedance R2.
Generally, the surface of the lithium ion battery electrode is a porous structure, and specifically, the inductance L is a porous electrode inductive reactance.
Fig. 2 is a conventional impedance model of a lithium ion battery, which includes an impedance Rb, and a second-order RC circuit, where the second-order RC circuit includes an impedance R1, an impedance R2, a capacitor C1, and a capacitor C2, the impedance R1 is connected in series with the impedance R2, the capacitor C1 is connected in parallel with the impedance R1, and the capacitor C2 is connected in parallel with the impedance R2.
Compared with a conventional lithium ion battery impedance model, in the embodiment of the present application, a porous electrode inductive reactance is connected to an end of the impedance Rb away from the second-order RC circuit, and meanwhile, a constant phase angle element CPE is used to replace a capacitor C, where an impedance formula of the capacitor C is as follows:
in the formula, ZCIs the impedance of a capacitor C, CCIs a capacitance value;
the impedance formula of the constant phase angle element CPE is:
in the formula, ZCPEThe impedance of the constant phase angle element CPE is represented by Y, which is a capacitance value (unit is identical to the capacitance C), and n represents a physical quantity of the capacitance C deflected by the dispersion effect.
In an actual electrochemical system of the lithium ion battery, the capacitance of an SEI (solid electrolyte interface) layer and the capacitance of an interface double layer inside the lithium ion battery are often non-ideal pure capacitances due to the existence of diffusion effects such as electrode surface roughness, leakage capacitance and current non-uniform distribution, and a constant phase angle element CPE in the electrochemical field can be used as a non-ideal capacitance specially set for fitting, so that the non-ideal pure capacitance in the lithium ion battery can be simulated more truly.
Through verification, the overall error rate of the lithium ion battery impedance model and the actually measured impedance spectrum provided by the embodiment of the application is 0.952%, the overall error rate of the conventional lithium ion battery impedance model and the actually measured impedance spectrum is 16.8%, and the fact that the accuracy of the lithium ion battery impedance model provided by the embodiment of the application is greatly improved can be obviously and visually seen, so that the lithium ion battery impedance model is more real when a battery model with the lithium ion battery impedance model is simulated, and powerful experimental parameters can be provided for later-stage simulation experiments.
As shown in fig. 3, an embodiment of the present application further provides a parameter identification method for a lithium ion battery impedance model, including:
step S1: providing a battery to be tested with lithium ion battery impedance in advance, and establishing a battery circuit with a lithium ion battery impedance model according to the battery to be tested;
step S2: determining the battery capacity of the battery to be tested;
step S3: adjusting the battery to be tested to an appointed state, and exciting the battery to be tested by adopting sine wave voltage signals with different frequencies to obtain an impedance spectrum EIS of the battery to be tested in the state;
step S4: calling the battery circuit by using impedance spectrum EIS analysis software, assigning values to each impedance element in a lithium ion battery impedance model of the battery circuit, and obtaining the impedance spectrum EIS of the battery circuit after assignment and parameters of each impedance element;
step S5: comparing the assigned impedance spectrum EIS of the battery circuit with the impedance spectrum EIS of the battery to be tested;
step S6: updating the assignment of each impedance element according to the comparison result until the impedance spectrum EIS of the battery circuit and the impedance spectrum EIS of the battery to be tested meet the fitting condition, and outputting the finally obtained parameters of each impedance element;
step S7: and taking the output parameters of the impedance elements as the parameters of the lithium ion battery impedance model in a specified state.
In the embodiment of the application, an impedance spectrum EIS of a battery to be tested in an appointed state is actually obtained, a simulated impedance spectrum EIS is fitted according to assignment values of all impedance elements in a lithium ion battery impedance model in a battery circuit, until the simulated impedance spectrum EIS is closest to the actually measured impedance spectrum EIS, and parameters of all impedance elements corresponding to the simulated impedance spectrum EIS which is closest to the impedance spectrum EIS are output.
The specific method for determining the battery capacity of the battery to be tested is as follows:
at the environment temperature of 25 +/-2 ℃, after the battery to be measured is fully charged with 1C current in a constant-current and constant-voltage mode, standing for more than 30min, performing constant-current discharge on the battery to be measured under the conditions of the same environment temperature and specific discharge current (the current value is referred to an enterprise standard or a national standard according to the battery type), after the discharge is finished, standing for more than 30min, charging and discharging for 5 times in the same mode, and taking the average value of the battery capacity measured for 5 times as the capacity value of the battery to be measured.
Further, the dependent variable of the state includes an SOC state, and the specific step of adjusting the battery to be tested to an assigned state includes:
and adjusting the SOC state of the battery to be tested to a specified SOC state.
In the embodiment of the present application, the specific steps of adjusting the SOC state of the battery to be tested to the specified SOC state are as follows:
discharging the battery to be tested at the ambient temperature of 25 +/-2 ℃ by using 1C current, wherein the discharge time is (1-n) multiplied by 1h, and n is the SOC value of each test.
The SOC value corresponding to the SOC state of the battery to be measured includes but is not limited to: 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%.
In step S3, an electrochemical workstation is used to apply a small-amplitude sine wave voltage signal (voltage) with a frequency of ω 1 to the battery under testAmplitude of 1 mv-10 mv), a sine wave current signal with frequency omega 2 is generated, meanwhile, the amplitude of the generated sine wave current signal is controlled below 2A, and the ratio of the sine wave voltage signal to the corresponding sine wave current signal is the impedance value Z with frequency omega 1fNamely:
in the formula, E (ω 1) is a voltage value that varies with the frequency ω 1, I (ω 2) is a current value that varies with the frequency ω 2, ω 1 is 2 pi f, and f is a sinusoidal alternating current frequency.
Within the frequency range of 1 m-10K Hz, changing the frequency f of the sine alternating current applied to the battery to be tested, taking 10KHz as the starting frequency and 1mHz as the tail end frequency, changing the frequency f of the applied sine alternating current point by point at regular intervals, and after measuring the corresponding generated sine wave current, obtaining the impedance value Z according to the abovefThe alternating current impedance spectrum EIS of the battery to be tested in the frequency range of 1 m-10K Hz is obtained.
Further, the dependent variables of the state include SOC state and ambient temperature, and specifically include the steps of:
and adjusting the SOC state of the battery to be tested to a specified SOC state, and measuring corresponding parameters at different environmental temperatures in the specified SOC state.
In this embodiment, the SOC state of the battery under test is kept unchanged, and the ambient temperature of the battery under test is changed, which includes but is not limited to: -20 ℃, 10 ℃, 0 ℃, 10 ℃, 25 ℃ and 40 ℃. After the parameters of each impedance element at all the ambient temperatures in a certain SOC state are measured, the SOC state is adjusted to the next SOC state, and the parameters of each impedance element at each ambient temperature are measured continuously.
Further, the dependent variable of the state further includes cycle number, which specifically includes:
and adjusting the cycle number of the battery to be tested to a specified cycle number, and measuring corresponding parameters of different SOC states and different environmental temperatures under the specified cycle number.
In the embodiment of the present application, in order to shorten the test time, a plurality of identical batteries to be tested are selected, the cycle number N of the plurality of batteries to be tested is different, the batteries to be tested include a fresh battery to be tested (cycle number is 0), a battery to be tested whose cycle number N is 500, a battery to be tested whose cycle number N is 1000, a battery to be tested whose cycle number N is 1500, and a battery to be tested whose cycle number N is 2000, and the battery to be tested is identified in different cycle life stages and each element parameter in the lithium ion battery impedance model according to the above step of measuring different SOC states and different environmental temperatures.
Preferably, the method further comprises the following steps:
according to all the output parameters, a three-dimensional data table is created, and the three dimensions are SOC state, environment temperature and cycle number;
and determining other parameters under the SOC state, the ambient temperature and the cycle number by adopting an interpolation method based on the three-dimensional data table.
In this embodiment, a three-dimensional data table is constructed according to three dimensions of the SOC state, the ambient temperature, and the cycle number, in combination with all the measured parameters. For example, at the same environmental temperature and the same cycle number, the parameters of each impedance element of the lithium ion battery impedance model in a certain SOC state between two SOC states are solved by an interpolation method after table lookup to obtain the parameters of each impedance element of the lithium ion battery impedance model in a high SOC state.
Further, after the battery to be tested is adjusted to the designated state, before the battery to be tested is excited by adopting sine wave voltage signals with different frequencies, the method further comprises the following steps:
and standing the battery to be tested at a specified environmental temperature for more than 6 hours if the environmental temperature is above 25 ℃, or for more than 24 hours if the environmental temperature is less than 25 ℃.
Preferably, the order of magnitude of the initial assignment is the same as the order of magnitude of the individual impedance elements in the lithium ion battery impedance. In this embodiment, a battery circuit is retrieved by using electrochemical impedance spectroscopy EIS analysis software, and initial values are respectively assigned to impedance elements in an impedance model of a lithium ion battery in the battery circuit, for example, the impedance Rb is generally in the order of m Ω, and then the initial value assigned to the impedance Rb is 100m Ω, so that the battery circuit can be iterated to a vicinity of a target value quickly, and if the order of magnitude of the initial values is very different, an error may be caused to be large.
The present application is described below with reference to a specific example.
Taking a 25AH lithium manganate battery for a certain hybrid heavy truck as an example, adjusting the SOC state of the 25AH lithium manganate battery to be tested to 50% in the environment temperature of 25 +/-2 ℃, and standing for more than 6h in the environment temperature of 25 +/-2 ℃; and then, exciting the 25AH lithium manganate battery by using a sine wave voltage signal with the voltage amplitude of 2mV (under the voltage, the current amplitude of the 25AH lithium manganate battery is not more than 1A), wherein the frequency range is 10K-2 mHz, finally, an alternating current impedance spectrum of the 25AH lithium manganate battery in the frequency band can be obtained, then, carrying out Nyquist frequency Nyquist treatment on the alternating current impedance spectrum to obtain an impedance real part-imaginary part curve, only 1 to 2 points close to 0 are reserved for data points with positive imaginary parts, the rest is deleted, and all the data points with negative parts are reserved for data points with imaginary parts, as shown in FIG. 4, the impedance spectrum EIS after the Nyquist frequency treatment is carried out on the 25AH lithium manganate battery with 25 ℃/SOC being 50% is shown in FIG. 4.
Providing two lithium ion battery impedance models, opening Electrochemical Impedance Spectroscopy (EIS) analysis software as shown in figures 1 and 2, respectively calling a conventional lithium ion battery impedance model (figure 2) and an improved lithium ion battery impedance model (figure 1), and carrying out the same subsequent processing steps on the two lithium ion battery impedance models.
Taking an improved impedance model of the lithium ion battery as an example, the impedance model of the lithium ion battery comprises an inductor L, an impedance Rb, an impedance R1, an impedance R2, a constant phase angle element CPE1 and a constant phase angle element CPE2, each impedance element is respectively assigned with an initial value, electrochemical impedance spectrum EIS analysis software automatically adjusts parameters of each impedance element and obtains an impedance spectrum EIS of the impedance model of the lithium ion battery, the obtained impedance spectrum EIS is compared with an alternating current impedance spectrum of a 25AH lithium manganate battery, if the difference between the two impedance spectra is large, the assignment of each impedance element is repeatedly modified until the impedance spectrum EIS of the impedance model of the lithium ion battery is obtained and the alternating current impedance spectrum of the 25AH lithium manganate battery are fitted to be equivalent, as shown in fig. 5, the overall error rate of the impedance model of the lithium ion battery and an actually measured impedance spectrum is 0.952%, and then the parameters of each impedance element of the impedance spectrum EIS of the lithium ion battery impedance model which is fitted to, as shown in fig. 6.
If the impedance model of the lithium ion battery is conventional, finally obtaining an impedance spectrum EIS of the impedance model of the lithium ion battery and an alternating current impedance spectrum fitting condition of a 25AH lithium manganate battery as shown in fig. 7, wherein the overall error rate of the conventional impedance model of the lithium ion battery and the actually measured impedance spectrum is 16.8%, and outputting parameters of each impedance element of the impedance spectrum EIS of the impedance model of the lithium ion battery as shown in fig. 8.
Comparing fig. 5 and fig. 7, it can be seen intuitively that the lithium ion battery impedance model provided by the embodiment of the present application has a higher fitting degree, and more truly simulates the battery to be tested.
At ambient temperature 25 ℃, the SOC state of a 25AH lithium manganate battery was adjusted to: 0. 10%, 20%, 30%, 40%, 60%, 70%, 80%, 90%, 100%, the parameter values identifying the respective impedance elements in the respective SOC states are shown in table 1, where the column on the right side of CPE1 is n, representing the physical quantity of the deflection of the capacitance C due to the dispersion effect.
Table values of respective impedance element parameters at 125 deg.C under different SOC conditions
If the parameter value of SOC 15% is required, the parameter values of SOC 10% and SOC 20% may be selected and calculated by an interpolation method.
It should be noted that 731m is 0.0731, 551m is 0.551, and "m" means 10 in FIG. 6 of the specification-3。
Meanwhile, the SOC state of the 25AH lithium manganate battery is not changed by the excited sinusoidal alternating current, so that in actual operation, in order to improve the testing efficiency, after the SOC state is adjusted to a specified SOC value, the environmental temperature is changed, and the parameter values of the impedance elements of the lithium ion battery impedance model at different temperatures can be obtained. And then circulating the 25AH lithium manganate battery to the specified circulation times, repeatedly obtaining the parameter values of the impedance elements in different SOC states and different environmental temperatures, and finally obtaining the parameter values of the impedance elements in different circulation times, different SOC states and different environmental temperatures. The cycle number can also be the driving mileage or the service time.
In the description of the present application, it should be noted that the terms "upper", "lower", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, which are only for convenience in describing the present application and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and operate, and thus, should not be construed as limiting the present application. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as appropriate.
It is noted that, in the present application, relational terms such as "first" and "second", and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. The lithium ion battery impedance model is characterized by comprising an inductor L, an impedance Rb and a second-order RC circuit which are sequentially connected in series, wherein each-order PC circuit is a parallel circuit.
2. The impedance model of a lithium-ion battery as claimed in claim 1, wherein the second order RC circuit comprises an impedance R1, an impedance R2, a constant phase angle element CPE1 and a constant phase angle element CPE2, the impedance R1 being connected in series with the impedance R2, the constant phase angle element CPE1 being connected in parallel with the impedance R1, the constant phase angle element CPE2 being connected in parallel with the impedance R2.
3. The impedance model of a lithium ion battery of claim 1, wherein the inductance L is a porous electrode inductive reactance.
4. A parameter identification method of a lithium ion battery impedance model is characterized by comprising the following steps:
providing a battery to be tested with lithium ion battery impedance in advance, and establishing a battery circuit with a lithium ion battery impedance model according to the battery to be tested;
determining the battery capacity of the battery to be tested;
adjusting the battery to be tested to an appointed state, and exciting the battery to be tested by adopting sine wave voltage signals with different frequencies to obtain an impedance spectrum EIS of the battery to be tested in the state;
calling the battery circuit by using impedance spectrum EIS analysis software, assigning values to each impedance element in a lithium ion battery impedance model of the battery circuit, and obtaining the impedance spectrum EIS of the battery circuit after assignment and parameters of each impedance element;
comparing the assigned impedance spectrum EIS of the battery circuit with the impedance spectrum EIS of the battery to be tested;
updating the assignment of each impedance element according to the comparison result until the impedance spectrum EIS of the battery circuit and the impedance spectrum EIS of the battery to be tested meet the fitting condition, and outputting the finally obtained parameters of each impedance element;
and taking the output parameters of the impedance elements as the parameters of the lithium ion battery impedance model in a specified state.
5. The method for parameter identification of an impedance model of a lithium ion battery of claim 4, wherein the state dependent variable comprises a SOC state, and the specific step of adjusting the battery to be tested to a specified state comprises:
and adjusting the SOC state of the battery to be tested to a specified SOC state.
6. The method for parameter identification of an impedance model of a lithium ion battery of claim 4, wherein the state dependent variables comprise an SOC state and an ambient temperature, and specifically comprising the steps of:
and adjusting the SOC state of the battery to be tested to a specified SOC state, and measuring corresponding parameters at different environmental temperatures in the specified SOC state.
7. The method for parameter identification of an impedance model of a lithium ion battery of claim 6, wherein the dependent variable of the state further comprises cycle times, specifically comprising:
and adjusting the cycle number of the battery to be tested to a specified cycle number, and measuring corresponding parameters of different SOC states and different environmental temperatures under the specified cycle number.
8. The method for parameter identification of an impedance model of a lithium ion battery of claim 7, further comprising:
according to all the output parameters, a three-dimensional data table is created, and the three dimensions are SOC state, environment temperature and cycle number;
and determining other parameters under the SOC state, the ambient temperature and the cycle number by adopting an interpolation method based on the three-dimensional data table.
9. The method for parameter identification of an impedance model of a lithium ion battery according to claim 6, wherein after the battery under test is adjusted to a specified state, before the battery under test is excited by sine wave voltage signals of different frequencies, the method further comprises the steps of:
and standing the battery to be tested at a specified environmental temperature for more than 6 hours if the environmental temperature is above 25 ℃, or for more than 24 hours if the environmental temperature is less than 25 ℃.
10. The method of claim 4, wherein the order of magnitude of the initial assignment is the same as the order of magnitude of each impedance element in the lithium ion battery impedance.
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