CN115656861A - Power battery diagnosis device and method based on equalization circuit - Google Patents
Power battery diagnosis device and method based on equalization circuit Download PDFInfo
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Abstract
The invention provides a power battery diagnosis device and method based on an equalization circuit. The battery diagnosis method includes: injecting a multi-frequency periodic signal into a reference current of the equalizing circuit, and exciting a battery by using an output current; sampling to obtain battery voltage and current data, and obtaining an electrochemical impedance spectrum of the battery through fast Fourier transform; establishing a battery impedance model for analyzing electrochemical impedance spectrum change; obtaining an electrochemical impedance spectrum of the battery under the same detection condition during diagnosis, comparing the electrochemical impedance spectrum with historical information to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting an increment threshold value; when the increment exceeds the threshold value, the battery is diagnosed as a fault, the fault type such as virtual connection and micro short circuit is analyzed, and aging, impedance inconsistency and the like are diagnosed in an auxiliary mode. The diagnosis device is based on an equalization circuit, the equipment of the diagnosis device is integrated in a battery management system, and the battery fault is diagnosed on line by utilizing electrochemical impedance spectrum information.
Description
Technical Field
The invention belongs to the technical field of battery management, and particularly relates to a power battery diagnosis device and method based on an equalization circuit.
Background
The lithium ion battery has higher energy density and power density, longer service life and wider application in the aspects of new energy vehicles and energy storage. The problem of battery safety is also receiving increasing attention, and the fault diagnosis of the battery becomes a necessary function of a battery management system, so that the battery can be effectively diagnosed, the use safety of the battery can be improved, the service life of a battery pack can be prolonged, and the damage of the battery can be avoided.
Battery faults are researched by adopting Electrochemical Impedance Spectroscopy (EIS), different impedance components can be analyzed by detecting alternating current impedance values under different frequencies, and battery faults can be diagnosed from battery electrochemical impedance spectroscopy parameter changes, so that the EIS is increasingly emphasized in battery diagnosis.
An EIS detection device based on active equalization injects multi-frequency periodic signals into an equalization control loop in an active equalization circuit, and batteries are excited by superposed currents; after the battery current and voltage data are subjected to FFT (fast Fourier transform) processing, complex impedance information under each disturbance frequency is obtained, and an electrochemical impedance spectrum in a disturbance frequency range is further obtained.
Disclosure of Invention
In order to solve the problems of defects and shortcomings in the prior art and consider the space for further improvement and promotion in the prior art, the invention provides a power battery diagnosis device and method based on an equalization circuit. The scheme can realize the integration of an EIS detection function and a battery equalization function; and the battery fault is diagnosed in real time through the change of the battery EIS in the battery management system, so that the management and the monitoring of the battery are realized.
The device has two modes, an equalization mode and a diagnostic mode. The battery diagnosis method includes: injecting a multi-frequency periodic signal into a reference current of the equalizing circuit, and exciting a battery by using an output current; sampling to obtain battery voltage and current data, and obtaining an electrochemical impedance spectrum of the battery through fast Fourier transform; establishing a battery impedance model for analyzing electrochemical impedance spectrum change; obtaining an electrochemical impedance spectrum of the battery under the same detection condition during diagnosis, comparing the electrochemical impedance spectrum with historical information to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting an increment threshold value; when the increment exceeds the threshold value, the battery is diagnosed as a fault, the fault type such as virtual connection and micro short circuit is analyzed, and aging, impedance inconsistency and the like are diagnosed in an auxiliary mode. The diagnosis device is based on an equalization circuit, the equipment of the diagnosis device is integrated in a battery management system, and the battery fault is diagnosed on line by utilizing electrochemical impedance spectrum information.
The technical scheme adopted by the invention for solving the technical problem is as follows:
a power battery diagnosis device and terminal equipment based on an equalizing circuit comprise a battery active equalizing circuit, a battery string combination, a signal conditioning circuit, a PWM (Pulse Width Modulation) driving circuit, an information storage device and other various software and hardware which are necessary for forming a battery management system.
When the balancing circuit works, a multi-frequency periodic signal is injected into the reference current of the balancing circuit, and the battery is excited by the output current; sampling to obtain battery voltage and current data, and obtaining an electrochemical impedance spectrum of the battery through fast Fourier transform; establishing a battery impedance model for analyzing electrochemical impedance spectrum change; obtaining an electrochemical impedance spectrum of the battery under the same detection condition during diagnosis, comparing the electrochemical impedance spectrum with historical information to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting an increment threshold value; when the increment exceeds the threshold value, a battery fault is diagnosed, and the fault type is analyzed.
The battery diagnosis device is based on an active equalization circuit, the active equalization circuit is used as a power circuit to provide excitation, and terminal equipment of the battery diagnosis device can be integrated in a battery management system and used as a component part of hardware and functions of the battery management system.
The active equalization circuit in the diagnosis device is an energy bidirectional transfer type equalization circuit, such as: buck-Boost equalizer circuit, cuk equalizer circuit, etc. The diagnosable number of the batteries of the device is determined by the number of the batteries connected in the equalizing circuit, and the battery comprises X monomers, wherein X is more than or equal to 2; when a plurality of batteries in the equalizing circuit are simultaneously excited, the EIS can be detected by acquiring the voltage and current data of the excited batteries, so that the diagnostic device can diagnose the plurality of batteries simultaneously.
When the directions of energy transfer in the active equalizer are different, the batteries connected with the two ends of the active equalizer can supply power and can also be used as batteries to be tested. The discharged battery at the input end of the active equalizer is used as a power supply direct current source, and the equalizing circuit provides exciting current for the battery to be tested at the load end, so that the battery at the load end is diagnosed without an additional power supply.
The diagnostic device has two operation modes, a diagnostic mode and an equalization mode.
In the diagnosis mode, impedance spectrum information of the single batteries is detected through an active equalization-based EIS detection device, and battery faults are diagnosed through changes of the EIS information.
In the equalization mode, the bidirectional equalization circuit in the diagnostic device equalizes the battery SOC (State of charge). And obtaining the SOC information of the single battery by using a related SOC estimation method, taking the SOC difference value as a balance criterion when the SOC of the battery connected at one end in the balance circuit is higher than that of the battery at the other end, and starting balance when the difference value is higher than a set threshold value. The end with higher SOC is used as an input end, the end with lower SOC is used as a load end, the on-off of a switch tube is controlled through a PWM signal output by a balance control circuit, so that a battery at the input end is discharged, and a battery at the output end is charged by balance current; and when the SOC difference value converges to the balance threshold value, ending the SOC balance between the batteries. The control of the balance current can adopt balance related control methods such as fuzzy control, PID control, self-adaptive control and the like, and the related balance control method and the balance strategy are not described again because the invention mainly provides a diagnosis method.
In the diagnostic device, an active equalization circuit is connected with a battery string; the voltage and current signal ends of the battery string are connected with the signal conditioning circuit; the output end of the signal conditioning circuit is connected with an ADC pin of a battery management system sampling module; the PWM output end of the digital controller is connected to the input end of the PWM driving circuit; the output end of the PWM driving circuit is connected with the grid electrode of each switching tube in the active equalization circuit; the information storage device is connected with an I/O port of the battery management system.
The signal conditioning circuit performs AC/DC signal separation on the voltage and current of the battery, removes the influence of DC and high-frequency noise interference, and amplifies the signal.
The function of collecting the voltage and current signals of the battery is realized by a sampling module in the battery management system, and an additional hardware circuit is not needed. Considering the sampling precision and the frequency range of the disturbance signal, the battery management system sampling module is preferably an analog front-end chip with higher sampling frequency.
The PWM driving circuit amplifies the PWM control pulse output by the digital controller to be enough to drive the switching tube, provides enough driving capability and avoids overvoltage and overcurrent of the power device.
The digital controller is used for system control, signal processing, impedance spectrum calculation, fault diagnosis and the like, and can adopt a digital controller or a microcomputer in a battery management system.
The information storage device is used for storing impedance spectrum information obtained in the initial and subsequent measurement of each battery, providing historical information for battery diagnosis as a basis, and can adopt various product forms capable of implementing computer programs, such as a disk memory, a CD-ROM, a flash memory, an optical memory and the like.
Based on the device, the invention provides a power battery diagnosis method based on an equalization circuit, which is characterized in that: the diagnosis device diagnoses the failure of the battery based on the EIS information of the battery. The sizes of the ohmic resistor and the charge transfer resistor are obtained through key characteristics of the EIS of the battery, the EIS of the battery is obtained under the same detection condition in subsequent operation, resistance value increment of the ohmic resistor and the charge transfer resistor is obtained by comparing historical information, a resistance value increment threshold value is set, and the battery with the increment exceeding the threshold value is diagnosed as a fault.
Based on the detected EIS changes, the determination of the possible fault type of the faulty battery specifically includes:
the ohmic resistance appears in the EIS image as a real-axis left intersection of the EIS, which shifts to the right along the real axis as the EIS image increases. Under the same detection condition, when the ohmic resistance is remarkably increased, possible faults are abnormal physical and chemical changes of an electrode material, abnormal increase of the resistance of a diaphragm and contact resistance increase of parts, such as virtual connection; when the ohmic resistance reduction exceeds a threshold, a possible failure is a battery micro-short.
The charge transfer resistance is expressed as a semi-circular arc diameter in an intermediate frequency region in the EIS, and when the charge transfer resistance becomes larger, the semi-circular arc height of the EIS image increases along the imaginary axis direction, and the diameter of the semi-circular arc increases. A possible failure is an increase in the positive impedance; when the amount of decrease in the charge transfer resistance exceeds the threshold value, a micro short circuit inside the battery is considered. The resistance increment threshold corresponding to the fault state needs to be comprehensively determined by testing and engineering experience of batteries of specific models.
During the long-term operation of the battery, the diagnosis of the aging of the battery and the impedance inconsistency among the batteries can be further assisted through the resistance value increment.
The aging of the battery leads to a significant increase in the resistance of the ohmic resistance and the charge transfer resistance. And setting an aging retirement threshold according to experimental data, and providing a basis for replacement and maintenance when the resistance value increment and the cycle number of the battery reach the retirement degree.
The impedance inconsistency between the battery cells is too great, which affects the performance and life of the entire battery pack. The method and the device detect the ohmic resistance and the charge transfer resistance of each monomer in the battery pack under the same detection condition, set the inconsistency threshold value to diagnose the inconsistency of the impedance of the monomers in the battery pack, and provide a basis for replacing and maintaining the monomers of which the inconsistency exceeds the threshold value.
Accordingly, the method comprises the steps of:
step S1, adopting a battery EIS detection device based on active equalization, and injecting a multi-frequency periodic signal into a current reference value of a current control loop after the current reaches a stable state, so that superposed current excites a battery to be detected at a load end;
s2, after the disturbance signal is injected, a sampling module of the battery management system is used for sampling at a frequency f S Synchronously collecting voltage and current signals of the battery; performing Fast Fourier Transform (FFT) on voltage and current information in a digital controller or a microcomputer of a battery management system, and acquiring impedance information under a plurality of disturbance frequencies at one time by an algorithm to further acquire EIS information within a certain frequency range;
s3, establishing a battery impedance equivalent model for analyzing the corresponding relation between the impedance spectrum change and the impedance model parameter change so as to further diagnose the battery fault according to the impedance spectrum;
s4, detecting the EIS of the battery in the state of health under the given temperature, SOC and charge-discharge multiplying power, and using the EIS as a reference standard of the state of health in battery fault diagnosis; then, when the subsequent batteries are balanced, the batteries EIS are detected under the same detection condition, and a battery management system is used for fault diagnosis;
step S5, after the battery EIS is obtained, comparing and analyzing the battery EIS with EIS historical information under the battery health state to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting a threshold value; diagnosing the battery with the resistance increment reaching the threshold value as a fault state, and analyzing possible fault types; and assists in diagnosing battery aging and impedance inconsistencies over long periods of operation of the battery pack.
Further, step S1 specifically includes the following steps:
an energy bidirectional transfer type equalizing circuit is established as an active equalizer ICE, the active equalizer ICE is connected between the two batteries, and energy transfer and mutual excitation between the two batteries are realized by controlling the on-off of different switch tubes;
taking a discharge battery at an input end in the equalizing circuit as a power supply direct current source; taking a load end battery in an excited state as a battery to be tested;
considering electrochemical impedance spectrum detection requires that the cell must be in an equilibrium state or be in a certain stable direct current polarization condition for disturbance and excitation.
Therefore, after the balance current reaches the steady state, in the closed-loop controller for the balance current,injecting a sinusoidal signal into a reference value of the current; the superposed current excites the battery to be tested at the load end; in which the excitation current to the battery is supplied by a direct current I dc Superimposed AC disturbance current I m sin (ω t) is obtained and is expressed as:
I dc +I m sin(ωt)(1)
because the EIS detection and the battery management system share the sampling module to collect information, the limit of the sampling frequency of the analog front-end chip in the range of the disturbance frequency needs to be considered, and the upper limit and the lower limit of the disturbance frequency are comprehensively determined by considering the requirements of the sampling theorem and engineering practice.
Further, step S2 specifically includes the following steps:
injecting a multi-frequency periodic signal into the reference current, and after the current starts to excite the battery to be tested, performing AC/DC signal separation on the voltage and the current in the signal conditioning circuit;
removing the influence of direct current and high-frequency noise interference signals by adopting a method of reversely adding an effective value, and amplifying alternating current signals; then the sampling module in the battery management system takes the frequency f S Synchronously acquiring the conditioned voltage and current signals of the battery to be detected;
considering the problems of sampling precision and frequency aliasing in engineering practice, the sampling frequency f S Usually, the frequency band to be measured is 5 to 10 times of the highest frequency, and the sampling period is at least 2 times of the lowest frequency period of the disturbing signal.
After voltage and current data are obtained, FFT (fast Fourier transform) is carried out on the voltage and current data of the battery in a digital controller or a computer of a battery management system, a current peak point complex signal with a given amplitude value is selected through an algorithm, and a voltage peak point complex signal corresponding to the current peak point frequency is selected; and calculating the voltage and current peak point complex signals under the frequency to obtain complex impedance information under the frequency:
wherein theta is(f) The phase difference of the voltage and the current at the frequency is obtained; v p (f) The amplitude of the voltage peak value point of the frequency is taken as the amplitude of the voltage peak value point of the frequency; i is p (f) The current peak point amplitude is the frequency. R is the real part of the complex impedance, and X is the imaginary part of the complex impedance.
The algorithm program can obtain a plurality of impedance information in the disturbance frequency range at one time, and draw a battery electrochemical impedance spectrum in the disturbance frequency range.
Further, step S3 specifically includes the following steps:
establishing a battery impedance equivalent model for describing and analyzing the corresponding relation between EIS change and battery impedance parameter change: selecting a battery impedance Randles equivalent model which comprises a high-frequency inductor, an ohmic resistor, a charge transfer resistor, an electric double-layer capacitor, warburg diffusion impedance and the like.
The straight line part of the high-frequency region of the electrochemical impedance spectrum corresponds to the impedance of the high-frequency inductor; the left intersection point of the impedance spectrum semi-circular arc line and the real axis corresponds to an ohmic resistor; the semi-circular arc of the intermediate frequency region corresponds to the impedance of the charge transfer resistor and the double electric layer capacitor; the 45 ° slope of the low frequency region corresponds to Warburg diffusion impedance.
When the state of health of the battery is degraded, the high-frequency part of the EIS of the battery is basically not changed; the oblique lines of the low-frequency region diffusion impedance are also basically parallel; the main change of the impedance spectrum occurs in the ohmic resistance and the charge transfer resistance part, namely the half-circular arc part of the intermediate frequency area is obviously changed; neglecting the impedance spectrum parts of the high-frequency area and the low-frequency area does not influence the judgment of the battery EIS change, and the time required by EIS detection can be shortened. Meanwhile, the high-frequency inductance effect is not large at medium and low frequencies, the measurement time is relatively short, and substances cannot diffuse in time, so that the Warburg diffusion impedance and the high-frequency inductance impedance can not be considered by the model.
Therefore, the Randles model of battery impedance is further simplified into three parts of ohmic resistance, charge transfer resistance and electric double-layer capacitance. The analysis difficulty of the battery impedance equivalent model can be reduced, and the circuit characteristics of the battery impedance model are not essentially influenced. The size of ohmic resistance is determined through the left intersection point of the impedance spectrum semi-circular arc line and the real axis, the size of the charge transfer resistance is determined through the semi-circular arc diameter of the intermediate frequency region, and battery faults are diagnosed based on the change of the parameters.
Further, step S4 specifically includes the following steps:
the EIS detection device and the method are used for detecting and obtaining the EIS of the healthy battery at the initial life stage under certain temperature, SOC and charging rate, the EIS is used as a reference standard in battery fault analysis, the ohmic resistance is determined through the left intersection point of the impedance spectrum semi-arc line and the real axis, the charge transfer resistance is determined according to the semi-arc diameter of the intermediate frequency region, and the information is stored in a storage device of diagnosis equipment. In the subsequent fault diagnosis of the power battery, the EIS of the battery is detected by using the same detection condition.
Further, step S5 specifically includes the following steps:
after the single battery EIS is obtained in the subsequent detection, comparing the single battery EIS with the battery health state EIS, calculating to obtain the resistance value increment of the ohmic resistor and the charge transfer resistor, and setting a threshold value of the resistance value increment; when the resistance increment of the battery reaches a set threshold value, diagnosing the battery as a fault; and feeding back fault information to the battery management system. And the resistance increment threshold corresponding to the fault state is comprehensively determined by experiments.
As the ohmic resistance increases, the EIS image shifts to the right along the real axis relative to the EIS image of a healthy cell. The resistance increment of the ohmic resistor is the difference value of the real-axis left intersection point of the current EIS and the real-axis left intersection point of the health state EIS. Under the same detection condition, when the ohmic resistance is obviously increased, the resistance corresponding to the electrode material and the diaphragm is considered to be increased, or the contact resistance of parts is considered to be increased, such as virtual connection and the like. As the ohmic resistance decreases, the EIS image shifts to the left along the real axis relative to the EIS image of a healthy cell. The ohmic resistance reduction rarely occurs in practice, but it may occur that a micro short circuit occurs inside the battery.
The resistance value of the charge transfer resistor is represented as the semi-circular arc diameter of the intermediate frequency region in the EIS, when the charge transfer resistor is increased, the semi-circular arc height is increased along the virtual axis direction, and the diameter of the semi-circular arc is increased; when the charge transfer resistance is reduced, the diameter of the semicircular arc of the impedance spectrum and the height in the virtual axis direction are reduced. Under the same detection condition, if the charge transfer resistance is obviously increased, the impedance of the positive electrode is considered to be increased, the physical and chemical changes of the positive electrode material can occur, or the battery is aged; the occurrence of a micro short inside the battery is also considered when the charge transfer resistance is reduced.
Further, diagnosis of the degree of battery aging and the inconsistency between batteries is aided by the increase in resistance value.
The aging of the battery can obviously increase the resistance values of the ohmic resistor and the charge transfer resistor, after the resistance value increment of the ohmic resistor and the charge transfer resistor is obtained, an aging decommissioning threshold value is set according to experimental data, and a basis for replacing and maintaining the battery is provided for the battery with the resistance value increment and the cycle number reaching the decommissioning degree.
In the long-term operation of the battery pack, the impedance consistency of the single cells in the battery pack changes, and the impedance inconsistency between the single cells is too large, so that the performance and the service life of the whole battery pack are influenced. Therefore, the device and the method of the invention are used for detecting the ohmic resistance and the charge transfer resistance of each single body, setting an inconsistency threshold value for judging the inconsistency of the impedance of the single bodies in the battery pack, and replacing or maintaining the batteries exceeding the inconsistency threshold value.
Compared with the prior art, the beneficial effects of the invention and the preferable scheme thereof comprise:
1. the functional integration of EIS detection, active equalization and fault diagnosis of the battery can be realized; and the application expansion and hardware sharing of the equalizing circuit are realized.
2. The device has a diagnosis mode and an equalization mode, different functions can be realized in different modes, the equalization circuit can be used for active equalization among the batteries in the equalization mode, and the equalization circuit can be used for providing energy excitation for the battery to be tested in the diagnosis mode.
3. The resistance increment of the ohmic resistor and the charge transfer resistor is calculated and obtained through the battery EIS obtained by the diagnosis device, so that the power battery fault is diagnosed on line, the possible fault type is analyzed preliminarily, and a basis is provided for fault processing.
4. By monitoring the EIS of the battery, the inconsistency of the impedance in the battery pack can be monitored in long-term operation, and a diagnosis basis of the inconsistency of the impedance is provided; and provides a diagnostic basis for the aging and decommissioning of the battery.
Drawings
The invention is described in further detail below with reference to the following figures and detailed description:
FIG. 1 is a schematic diagram of a fault diagnosis process according to an embodiment of the present invention;
FIG. 2 is a Randles equivalent model and a corresponding impedance spectrum diagram for describing the impedance characteristics of the battery according to the embodiment of the present invention;
FIG. 3 is a state-of-health battery electrochemical impedance spectrum obtained by simulation in an embodiment of the present invention;
FIG. 4 is an EIS obtained by simulating ohmic resistance changes in an embodiment of the invention. The solid line part is a normal battery EIS, the dotted line part is a fault battery EIS, and the circle dotted line part is the fault battery EIS estimated by the FFT algorithm in the scheme. The upper half part of the graph is that the analog ohmic resistance becomes larger, and the lower half part of the graph is that the analog ohmic resistance becomes smaller;
FIG. 5 is an EIS obtained by simulating a change in charge transfer resistance in an embodiment of the present invention. The upper half of the figure shows that the analog charge transfer resistance becomes large, and the lower half shows that the analog charge transfer resistance becomes small.
Detailed Description
In order to make the features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail as follows:
it should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
In this embodiment, a power battery online diagnosis device based on a bidirectional active equalization circuit is taken as an example to perform further analysis.
As shown in fig. 1, the power battery online diagnosis device architecture is based on a bidirectional active equalization circuit. In the bidirectional active balancing circuit, a switching tube is controlled to supply power to an input end battery and excite a load end battery. Electrochemical impedance spectroscopy detection requires that the cell must be in an equilibrium state or under a certain stable dc polarization condition, so a constant current test is employed to excite the cell in a constant current state.
After the current reaches a steady state, injecting a multi-frequency periodic sinusoidal signal into a current reference value of the current control loop, and thus superposing the current to excite the battery to be tested at the load end. The excitation current to the battery is composed of DC current I dc Superimposed AC disturbance current I m sin (ω t) is obtained and is expressed as:
I dc +I m sin(ωt)(1)
after injecting a disturbance signal into the current reference, a sampling module in the battery management system is operated at a frequency f S And synchronously acquiring voltage signals and battery current signals at two ends of the battery to obtain time domain voltage and current data.
And then FFT is carried out on the obtained voltage and current data in a digital controller or a microcomputer of the battery management system to obtain a voltage and current complex signal containing a real part and an imaginary part.
And selecting a current peak point signal with more than a certain amplitude value through an algorithm, and selecting a voltage peak point signal corresponding to the current peak point frequency. And calculating the voltage and current peak point complex signals under the frequency to obtain complex impedance information under the frequency:
wherein theta (f) is the phase difference of the voltage and the current at the frequency; v p (f) The peak voltage amplitude of the frequency; I.C. A p (f)The current peak point amplitude is the frequency. R is the real part of the complex impedance, and X is the imaginary part of the complex impedance.
After impedance information corresponding to a series of disturbance frequencies is obtained, the battery EIS in the disturbance frequency range can be drawn.
And establishing a proper battery impedance equivalent model for describing different components of the battery impedance and determining the corresponding relation between the EIS change and the battery impedance parameter change. In the long-term operation process of the battery, the main change of the impedance spectrum occurs in the ohmic resistance and the charge transfer resistance part, namely the semi-circular arc part of the intermediate frequency region is obviously changed, so that the impedance spectrum parameters are selected by focusing on the intermediate frequency region.
As shown in fig. 2, a Randles impedance model and a corresponding EIS diagram are shown, and the simplified Randles impedance model is selected to describe the battery impedance in the present embodiment, which includes three parts of an ohmic resistance, a charge transfer resistance, and an electric double layer capacitance. The simplification can reduce the analysis difficulty of the impedance equivalent model and does not have essential influence on the characteristics of the impedance circuit. The resistance values of the ohmic resistor and the charge transfer resistor can be obtained through key features on an EIS image corresponding to a Randles impedance model, the size of the ohmic resistor is determined through a left intersection point of an impedance spectrum semi-circular arc line and a real axis, and the size of the charge transfer resistor is determined through the diameter of a semi-circular arc of a medium frequency area.
Firstly, detecting a single battery which is in an initial service life and has a good health state, obtaining EIS of the battery under a certain temperature, SOC and charging rate, obtaining resistance values of an ohmic resistor and a charge transfer resistor, and storing the information into a storage device of equipment to be used as health state reference information in subsequent diagnosis of the battery.
As shown in fig. 3, is the healthy battery EIS determined by the method of the present invention. A bidirectional equalization circuit and a battery impedance Randles model are built in Simulink software, and multi-frequency sine superposition signals with the highest frequency of 300Hz and the lowest frequency of 0.1Hz are added. According to the method, the battery impedance model is excited by the current output by the equalizing circuit to obtain the battery voltage and current data, and the EIS of the battery impedance model in the disturbance frequency range is obtained by solving and drawing through the FFT algorithm.
Then in the subsequent battery operation, acquiring EIS information of the battery by adopting the same detection condition and method as the healthy battery EIS, comparing the EIS information with the normal battery EIS, calculating the resistance value increment of the ohmic resistor and the charge transfer resistor, and setting the threshold value of the resistance value increment; when the battery resistance value increment is abnormal to reach the fault degree, the battery fault is diagnosed.
As shown in fig. 4 to 5, the parameter values of the Randles impedance model of the battery in the simulation are modified to respectively simulate the conditions that the ohmic resistance and the charge transfer resistance of the battery are changed, the EIS estimated by the algorithm after the impedance change is obtained by adopting the same detection conditions and method, and the change of the EIS of the battery after the ohmic resistance and the charge transfer resistance are changed can be visually seen. And obtaining the ohmic resistance increment through the translation distance of the EIS semi-circular arc along the real axis, and obtaining the resistance increment of the charge transfer resistor through the increment of the EIS semi-circular arc diameter.
As shown in the upper half of fig. 4, the EIS image shifts to the right along the real axis relative to the EIS image of a healthy cell as the ohmic resistance increases. The ohmic resistance increment exceeds the threshold value, and the possible faults are abnormal electrode material, increased diaphragm resistance or increased contact resistance of parts, such as virtual connection.
As shown in the lower half of fig. 4, the EIS image shifts to the left along the real axis relative to that of a healthy battery when the ohmic resistance decreases. The ohmic resistance reduction rarely occurs in practice, but it may occur that a micro short circuit occurs inside the battery.
As shown in the upper half of fig. 5, when the charge transfer resistance increases, the EIS image semicircular arc height increases in the imaginary axis direction, and the diameter of the semicircular arc increases. When the increase in the charge transfer resistance exceeds the threshold value, it is considered that the positive electrode resistance increases or the battery deteriorates.
As shown in the lower half of fig. 5, when the charge transfer resistance is reduced, the EIS image semicircular arc height is reduced in the virtual axis direction, and the diameter of the semicircular arc is reduced. In practice, the occurrence of micro-short circuits inside the battery is also considered.
The resistance increment thresholds corresponding to different fault states are comprehensively determined by testing and engineering experience of batteries of specific models.
In long-term monitoring, whether the battery reaches the aging and decommissioning degree can be comprehensively judged by recording the cycle number and the resistance value increment of the battery. And comparing the detection results of EIS of each monomer in the battery pack, comparing the resistance values of ohmic resistance and charge transfer resistance of each monomer, and screening the batteries with inconsistency exceeding a threshold value.
The foregoing is directed to preferred embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow. However, any simple modification, equivalent change and modification of the above embodiments according to the technical essence of the present invention will still fall within the protection scope of the technical solution of the present invention.
The present invention is not limited to the above-mentioned preferred embodiments, and other various types of power battery diagnosis apparatus and method based on equalization circuit can be obtained by anyone who can derive the same from the teaching of the present invention.
Claims (10)
1. A power battery diagnosis device based on an equalization circuit is characterized by comprising a battery active equalization circuit, a battery string combination, a signal conditioning circuit, a PWM (pulse-width modulation) driving circuit, an information storage device and a battery management system;
when the circuit works, the circuit is used for injecting a multi-frequency periodic signal into a reference current of an equalizing circuit, and a battery is excited by an output current; sampling to obtain battery voltage and current data, and obtaining an electrochemical impedance spectrum of the battery through fast Fourier transform; establishing a battery impedance model for analyzing electrochemical impedance spectrum change; obtaining an electrochemical impedance spectrum of the battery under the same detection condition during diagnosis, comparing the electrochemical impedance spectrum with historical information to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting an increment threshold value; when the increment exceeds the threshold value, a battery fault is diagnosed, and the fault type is analyzed.
2. The equalization circuit-based power battery diagnosis device according to claim 1, characterized in that: based on the active equalization circuit, the active equalization circuit is used as a power circuit to provide excitation;
the active equalization circuit is an energy bidirectional transfer type equalization circuit, the diagnosable number of the batteries of the device is determined by the number of the batteries connected in the equalization circuit, and the device comprises X single bodies, wherein X is more than or equal to 2.
3. The equalization circuit-based power battery diagnosis device according to claim 1, characterized in that:
there are two modes of operation, diagnostic and equalization:
in a diagnosis mode, detecting impedance spectrum information of a single battery through an active equalization-based EIS detection device, and diagnosing battery faults through changes of EIS information;
in the balancing mode, a bidirectional balancing circuit in the diagnosis device balances the SOC of the battery; obtaining SOC information of the single batteries by a related method of SOC estimation, taking an SOC difference value as a balance criterion when the SOC of the battery connected with one end in the balance circuit is higher than that of the battery at the other end, and starting balance when the difference value is higher than a set threshold value; the end with higher SOC is used as an input end, the end with lower SOC is used as a load end, the PWM signal output by the balance control circuit controls the on-off of the switch tube, so that the battery at the input end is discharged, and the balance current charges the battery at the output end; when the SOC difference value converges to the balance threshold value, the SOC balance between the batteries is finished;
in the diagnosis device, an active equalization circuit is connected with a battery string; the voltage and current signal ends of the battery string are connected with the signal conditioning circuit; the output end of the signal conditioning circuit is connected with an ADC pin of a battery management system sampling module; the PWM output end of the digital controller is connected to the input end of the PWM driving circuit; the output end of the PWM driving circuit is connected with the grid electrode of each switching tube in the active equalization circuit; the information storage device is connected with an I/O port of the battery management system.
4. A power battery diagnosis method based on an equalization circuit is characterized in that: the equalization circuit-based power cell diagnostic apparatus of claim 1:
the fault diagnosis of the battery by the diagnosis device is based on the EIS information of the battery; the sizes of the ohmic resistor and the charge transfer resistor are obtained through key characteristics of the EIS of the battery, the EIS of the battery is obtained under the same detection condition in subsequent operation, resistance value increments of the ohmic resistor and the charge transfer resistor are obtained by comparing historical information, a resistance value increment threshold value is set, and the battery with the increment exceeding the threshold value is diagnosed as a fault.
5. The equalization circuit-based power battery diagnosis method according to claim 4, characterized in that:
the method comprises the following steps:
step S1, adopting a battery EIS detection device based on active equalization, and injecting a multi-frequency periodic signal into a current reference value of a current control loop after the current reaches a stable state, so that superposed current excites a battery to be detected at a load end;
s2, after the disturbance signal is injected, a sampling module of the battery management system uses the frequency f S Synchronously collecting voltage and current signals of the battery; performing Fast Fourier Transform (FFT) on voltage and current information in a digital controller or a microcomputer of a battery management system, and acquiring impedance information under a plurality of disturbance frequencies at one time by an algorithm to further acquire EIS information within a certain frequency range;
s3, establishing a battery impedance equivalent model for analyzing the corresponding relation between the impedance spectrum change and the impedance model parameter change so as to further diagnose the battery fault according to the impedance spectrum;
s4, detecting the EIS of the battery in the state of health under the given temperature, SOC and charge-discharge multiplying power, and using the EIS as a reference standard of the state of health in battery fault diagnosis; then, when the subsequent batteries are balanced, the batteries EIS are detected by adopting the same detection conditions, and a battery management system is used for carrying out fault diagnosis;
step S5, after the battery EIS is obtained, comparing and analyzing the battery EIS with EIS historical information under the battery health state to obtain resistance value increment of an ohmic resistor and a charge transfer resistor, and setting a threshold value; diagnosing the battery with the resistance increment reaching the threshold value as a fault state, and analyzing possible fault types; and assists in diagnosing battery aging and impedance inconsistencies over long periods of operation of the battery pack.
6. The power battery diagnosis method based on the equalization circuit according to claim 5, characterized in that:
the step S1 specifically includes the following steps:
an energy bidirectional transfer type equalizing circuit is established as an active equalizer ICE, the active equalizer ICE is connected between the two batteries, and energy transfer and mutual excitation between the two batteries are realized by controlling the on-off of different switch tubes;
taking a discharge battery at an input end in the equalizing circuit as a power supply direct current source; taking a load end battery in an excited state as a battery to be tested;
after the equalizing current reaches a steady state, injecting a sinusoidal signal into a reference value of the current in a closed-loop controller for equalizing the current; thus, the superposed current excites the battery to be tested at the load end; in which the excitation current to the battery is supplied by a direct current I dc Superimposed AC disturbance current I m sin (ω t) is obtained and is expressed as:
I dc +I m sin (ω t) (1) considers the requirements of sampling theorem and engineering practice at the same time, and comprehensively determines the upper limit and the lower limit of the disturbance frequency.
7. The power battery diagnosis method based on the equalization circuit according to claim 5, characterized in that:
the step S2 specifically includes the following steps:
injecting a multi-frequency periodic signal into the reference current, and performing AC-DC signal separation on the voltage and the current of the battery to be tested in the signal conditioning circuit after the current starts to excite the battery to be tested;
removing the influence of direct current and high-frequency noise interference signals by adopting a method of reversely superposing effective values, and amplifying alternating current signals; then by a sampling module in the battery management systemFrequency f S Synchronously acquiring conditioned battery voltage and current signals;
after voltage and current data are obtained, FFT fast Fourier transform is carried out on the voltage and current data of the battery in a digital controller or a computer of a battery management system, a current peak point complex signal with a given amplitude value is selected through an algorithm, and a voltage peak point complex signal corresponding to the current peak point frequency is selected; and calculating the complex signals of the voltage peak point and the current peak point under the frequency to obtain complex impedance information under the frequency:
wherein theta (f) is the phase difference of the voltage and the current at the frequency; v p (f) The peak voltage amplitude of the frequency; i is p (f) The current peak point amplitude value of the frequency; r is a real part of complex impedance, and X is an imaginary part of complex impedance;
and obtaining a plurality of impedance information within the disturbance frequency range at one time, and drawing a battery electrochemical impedance spectrum within the disturbance frequency range.
8. The equalization circuit-based power battery diagnosis method according to claim 5, characterized in that:
the step S3 specifically includes the following steps:
establishing a battery impedance equivalent model for describing and analyzing the corresponding relation between EIS change and battery impedance parameter change: selecting a battery impedance Randles equivalent model;
the straight line part of the high-frequency region of the electrochemical impedance spectrum corresponds to the impedance of the high-frequency inductor; the left intersection point of the impedance spectrum semi-circular arc line and the real axis corresponds to an ohmic resistor; the semi-circular arc of the intermediate frequency region corresponds to the impedance of the charge transfer resistor and the double electric layer capacitor; the 45-degree oblique line of the low-frequency region corresponds to Warburg diffusion impedance;
the model does not consider Warburg diffusion impedance and high-frequency inductance impedance;
the battery impedance Randles model is further simplified into three parts of ohmic resistance, charge transfer resistance and double electric layer capacitance; the size of ohmic resistance is determined through the left intersection point of the impedance spectrum semi-arc line and the real axis, the size of the charge transfer resistance is determined through the semi-arc diameter of the intermediate frequency region, and battery faults are diagnosed based on the changes of the ohmic resistance and the charge transfer resistance.
9. The equalization circuit-based power battery diagnosis method according to claim 5, characterized in that:
step S4 specifically includes the following steps:
under the given temperature, SOC and charging rate, detecting and obtaining EIS at the initial stage of the service life of the healthy battery as a reference standard in battery fault analysis, determining the size of ohmic resistance through a semi-circular arc line of an impedance spectrum and a left intersection point of a real axis, determining the size of charge transfer resistance through the semi-circular arc diameter of an intermediate frequency region, and storing the information into a storage device of diagnosis equipment; in the subsequent fault diagnosis of the power battery, the EIS of the battery is detected by using the same detection condition.
10. The equalization circuit-based power battery diagnosis method according to claim 5, characterized in that:
the step S5 specifically includes the following steps:
after the single battery EIS is obtained in the subsequent detection, comparing the single battery EIS with the same battery health state EIS, calculating to obtain the resistance value increment of the ohmic resistor and the charge transfer resistor, and setting a threshold value of the resistance value increment; when the resistance increment of the battery reaches a set threshold value, diagnosing the battery as a fault; feeding back fault information to a battery management system;
as the ohmic resistance increases, the EIS image shifts to the right along the real axis relative to the EIS image of a healthy cell; the resistance increment of the ohmic resistor is the difference value of the real-axis left intersection point of the current EIS and the real-axis left intersection point of the health state EIS; under the same detection condition, when the ohmic resistance is obviously increased, considering that the resistance corresponding to an electrode material and a diaphragm is increased, or the contact resistance of each part is increased; when the ohmic resistance is reduced, the EIS image is shifted to the left along the real axis relative to the EIS image of a healthy battery, and the micro short circuit inside the battery is considered;
the resistance value of the charge transfer resistor is represented as the semi-circular arc diameter of the intermediate frequency region in the EIS, when the charge transfer resistor is increased, the semi-circular arc height is increased along the imaginary axis direction, and the diameter of the semi-circular arc is increased; when the charge transfer resistance is reduced, the diameter of a semi-circular arc of an impedance spectrum and the height of an imaginary axis direction are reduced; under the same detection condition, if the charge transfer resistance is obviously increased, the impedance of the positive electrode is considered to be increased, the physical and chemical changes of the positive electrode material can occur, or the battery is aged; when the charge transfer resistance is reduced, it is considered that a micro short occurs inside the battery.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116087794A (en) * | 2023-04-07 | 2023-05-09 | 湖北工业大学 | Battery failure grading early warning method and system |
| CN116298912A (en) * | 2023-03-08 | 2023-06-23 | 上海玫克生储能科技有限公司 | Method, system, equipment and medium for establishing battery micro-short circuit model |
| CN116953556A (en) * | 2023-09-12 | 2023-10-27 | 苏州大学 | Method, system, medium and equipment for online detection of multivariable redundant fault battery |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116298912A (en) * | 2023-03-08 | 2023-06-23 | 上海玫克生储能科技有限公司 | Method, system, equipment and medium for establishing battery micro-short circuit model |
| CN116298912B (en) * | 2023-03-08 | 2023-12-12 | 上海玫克生储能科技有限公司 | Method, system, equipment and medium for establishing battery micro-short circuit model |
| CN116087794A (en) * | 2023-04-07 | 2023-05-09 | 湖北工业大学 | Battery failure grading early warning method and system |
| CN116953556A (en) * | 2023-09-12 | 2023-10-27 | 苏州大学 | Method, system, medium and equipment for online detection of multivariable redundant fault battery |
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