Power Battery Diagnostic Device and Method Based on Balancing Circuit

Abstract

The present invention provides a power battery diagnostic device and method based on a balancing circuit. The device has two modes: balancing and diagnosis. The battery diagnostic method includes: injecting a multi-frequency periodic signal into the reference current of the balancing circuit to excite the battery with the output current; sampling to obtain battery voltage and current data, and obtaining the electrochemical impedance spectrum of the battery through fast Fourier transform processing; establishing a battery impedance model for analyzing the change of the electrochemical impedance spectrum; during diagnosis, obtaining the electrochemical impedance spectrum of the battery under the same detection conditions, comparing it with historical information to obtain the resistance increments of the ohmic resistance and charge transfer resistance, and setting an increment threshold; when the increment exceeds the threshold, diagnosing the battery as faulty, and analyzing the fault type, such as loose connection, micro-short circuit, and assisting in diagnosing aging, impedance inconsistency, etc. The diagnostic device of this solution is based on a balancing circuit, and its equipment is integrated in the battery management system, and uses the electrochemical impedance spectrum information to diagnose battery faults online.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery management, and particularly relates to a power battery diagnosis device and method based on a balancing circuit. Background Art

[0002] Lithium-ion batteries have higher energy density, power density and longer service life, and are increasingly widely used in new energy vehicles and energy storage. Battery safety issues have also attracted increasing attention. Battery fault diagnosis has become an essential function of the battery management system. Effective diagnosis of the battery can improve the safety of battery use, extend the service life of the battery pack, and avoid battery damage.

[0003] Using battery Electrochemical Impedance Spectroscopy (EIS) to study battery faults, different impedance components can be analyzed by detecting the AC impedance values at different frequencies, and battery faults can be diagnosed from the changes in battery EIS parameters. Therefore, EIS has been increasingly valued in battery diagnosis.

[0004] An EIS detection device based on active balancing, that is, injecting multi-frequency periodic signals into the balancing control loop in the active balancing circuit to excite the battery by the superimposed current; after processing the battery current and voltage data by FFT (Fast Fourier Transform), the complex impedance information at each perturbation frequency is obtained, and then the electrochemical impedance spectrum within the perturbation frequency range is obtained. Summary of the Invention

[0005] To solve the defects and deficiencies existing in the prior art and considering that there is still room for further improvement and enhancement in the prior art, the present invention proposes a power battery diagnosis device and method based on a balancing circuit, establishing a battery EIS detection device based on the active balancing circuit, and diagnosing battery faults from the changes in battery EIS. This solution can integrate the EIS detection function and the battery balancing function; and instantaneously diagnose battery faults through the changes in battery EIS in the battery management system, realizing the management and monitoring of the battery.

[0006] The device has two modes, an equalization mode and a diagnostic mode. The battery diagnostic method includes: injecting a multi-frequency periodic signal into the reference current of the equalization circuit to excite the battery with the output current; sampling to obtain battery voltage and current data, and obtaining the electrochemical impedance spectrum of the battery through fast Fourier transform processing; establishing a battery impedance model for analyzing the change of the electrochemical impedance spectrum; during diagnosis, obtaining the electrochemical impedance spectrum of the battery under the same detection conditions, comparing it with historical information to obtain the resistance increment of the ohmic resistance and charge transfer resistance, and setting an increment threshold; when the increment exceeds the threshold, diagnosing the battery as faulty and analyzing the type of fault, such as loose connection, micro short circuit, and assisting in diagnosing aging, impedance inconsistency, etc. The diagnostic device of this solution is based on the equalization circuit, and its equipment is integrated in the battery management system, and uses the electrochemical impedance spectrum information to diagnose battery faults online.

[0007] The technical solution adopted by the present invention to solve its technical problems is:

[0008] A power battery diagnostic device and terminal device based on an equalization circuit, including a battery active equalization circuit, a battery string combination, a signal conditioning circuit, a PWM (Pulse Width Modulation) drive circuit, an information storage device, and other various necessary software and hardware components that make up the battery management system.

[0009] During operation, a multi-frequency periodic signal is injected into the reference current of the equalization circuit to excite the battery with the output current; sampling to obtain battery voltage and current data, and obtaining the electrochemical impedance spectrum of the battery through fast Fourier transform processing; establishing a battery impedance model for analyzing the change of the electrochemical impedance spectrum; during diagnosis, obtaining the electrochemical impedance spectrum of the battery under the same detection conditions, comparing it with historical information to obtain the resistance increment of the ohmic resistance and charge transfer resistance, and setting an increment threshold; when the increment exceeds the threshold, diagnosing the battery as faulty and analyzing the type of fault.

[0010] The battery diagnostic device is based on the active equalization circuit, and the active equalization circuit is used as a power circuit to provide excitation. Its terminal device can be integrated in the battery management system and is used as a component of the battery management system hardware and functions.

[0011] The active equalization circuit in the diagnostic device is an energy bidirectional transfer type equalization circuit, such as: Buck-Boost equalization circuit, Cuk equalization circuit, etc. The number of batteries that the device can diagnose is determined by the number of batteries connected in the equalization circuit, including X single cells, where X≥2; when multiple batteries in the equalization circuit are in the excited state at the same time, the voltage and current data of the excited batteries can be obtained to detect the EIS, so the diagnostic device can diagnose multiple batteries at the same time.

[0012] When the direction of energy transfer in the active balancer is different, the batteries connected to its two ends may supply power or be used as the battery under test. The discharging battery at the input end of the active balancer serves as a power supply DC source, and the balancing circuit provides an excitation current to the battery under test at the load end, thereby diagnosing the battery at the load end without the need for an additional power supply.

[0013] The diagnostic device has two operating modes, namely the diagnostic mode and the balancing mode.

[0014] In the diagnostic mode, the impedance spectrum information of the single battery is detected by the EIS detection device based on active balancing, and the battery fault is diagnosed based on the change of the EIS information.

[0015] In the balancing mode, the bidirectional balancing circuit in the diagnostic device performs the balancing of the battery SOC (State of Charge). The SOC information of the single battery is obtained through relevant methods of SOC estimation. When the SOC of the battery connected to one end of the balancing circuit is higher than that of the battery at the other end, the SOC difference is used as the balancing criterion. When the difference is higher than the set threshold, the balancing is started. The end with the higher SOC is used as the input end, and the end with the lower SOC is used as the load end. The on-off of the switching tube is controlled by the PWM signal output by the balancing control circuit, so that the battery at the input end discharges, and the balancing current charges the battery at the output end; when the SOC difference converges within the balancing threshold, the SOC balancing between the batteries ends. The control of the balancing current can adopt balancing-related control methods such as fuzzy control, PID control, and adaptive control. Since the present invention mainly provides a diagnostic method, the relevant balancing control methods and balancing strategies are not elaborated here.

[0016] In the diagnostic device, the active balancing circuit is connected to the battery string; the voltage and current signal terminals of the battery string are connected to the signal conditioning circuit; the output terminal of the signal conditioning circuit is connected to the ADC pin of the sampling module of the battery management system; the PWM output terminal of the digital controller is connected to the input terminal of the PWM driving circuit; the output terminal of the PWM driving circuit is connected to the gate of each switching tube in the active balancing circuit; the information storage device is connected to the I / O port of the battery management system.

[0017] The signal conditioning circuit separates the AC and DC signals of the battery voltage and current, removes the influence of DC and high-frequency noise interference, and amplifies the signals.

[0018] The function of collecting the battery voltage and current signals is realized by the sampling module in the battery management system without the need for an additional hardware circuit. Considering the sampling accuracy and the frequency range of the disturbance signal, the sampling module of the battery management system is preferably an analog front-end chip with a higher sampling frequency.

[0019] The PWM drive circuit amplifies the PWM control pulses output by the digital controller to a level sufficient to drive the switching transistor, providing sufficient driving capability and avoiding overvoltage and overcurrent in the power devices.

[0020] The digital controller is used for system control, signal processing, calculating impedance spectra, fault diagnosis, etc., and can use the digital controller or microcomputer in the battery management system.

[0021] The information storage device is used to store the impedance spectrum information obtained in the initial and subsequent measurements of each battery, providing historical information as a basis for battery diagnosis, and can adopt various product forms such as disk memories, CD-ROMs, flash memories, optical memories, etc. that can implement computer programs.

[0022] Based on the above devices, the present invention provides a power battery diagnosis method based on a balancing circuit, characterized in that: the diagnosis device diagnoses battery faults based on the EIS information of the battery. The magnitudes of the ohmic resistance and charge transfer resistance are obtained through the key features of the battery EIS. During subsequent operation, the EIS of the battery is obtained under the same detection conditions, and the resistance value increments of the ohmic resistance and charge transfer resistance are obtained by comparing historical information. A resistance value increment threshold is set, and batteries with an increment exceeding the threshold are diagnosed as faulty.

[0023] Based on the detected EIS changes, making a judgment on the possible fault types of faulty batteries specifically includes:

[0024] The ohmic resistance is manifested as the left intersection point of the real axis of the EIS in the EIS image. When it increases, the EIS image shifts to the right along the real axis. Under the same detection conditions, when the ohmic resistance increases significantly, the possible faults include abnormal physical and chemical changes in the electrode material, abnormal increase in the separator resistance, and increase in the contact resistance of parts, such as virtual connection; when the decrease amount of the ohmic resistance exceeds the threshold, the possible fault is micro-short circuit of the battery.

[0025] The charge transfer resistance is manifested as the diameter of the semi-circular arc in the intermediate frequency region in the EIS. When the charge transfer resistance becomes larger, the height of the semi-circular arc of the EIS image increases along the imaginary axis direction, and the diameter of the semi-circular arc increases. The possible faults include increased positive electrode impedance; when the decrease amount of the charge transfer resistance exceeds the threshold, it is considered that there is a micro-short circuit inside the battery. The resistance value increment threshold corresponding to the fault state needs to be determined comprehensively based on the tests of specific model batteries and engineering experience.

[0026] During the long-term operation of the battery, it is also possible to further assist in diagnosing battery aging and impedance inconsistency between batteries through the resistance value increment.

[0027] Battery aging causes a significant increase in the resistance values of the ohmic resistance and charge transfer resistance. An aging retirement threshold is set according to experimental data. For batteries whose resistance value increment and number of cycles both reach the retirement level, a basis for replacement and maintenance is provided.

[0028] Excessive inconsistency in the impedance between battery cells will affect the performance and lifespan of the entire battery pack. By detecting the ohmic resistance and charge transfer resistance of each cell within the battery pack under the same detection conditions according to the present invention, setting an inconsistency threshold to diagnose the inconsistency of the impedance of the cells within the battery pack, and providing a basis for replacement and maintenance for the cells whose inconsistency exceeds the threshold.

[0029] Accordingly, the method includes the following steps:

[0030] Step S1: Using a battery EIS detection device based on active balancing, after the current reaches a steady state, inject multi-frequency periodic signals into the current reference value of the current control loop, thereby superimposing the current to excite the battery under test at the load end;

[0031] Step S2: After injecting the perturbation signal, the sampling module of the battery management system synchronously collects the voltage and current signals of the battery at a frequency f S ; Perform fast Fourier transform (FFT) on the voltage and current information in the digital controller or microcomputer of the battery management system, and obtain impedance information at multiple perturbation frequencies at one time by the algorithm, and then obtain EIS information within a certain frequency range;

[0032] Step S3: Establish an equivalent model of the battery impedance to analyze the corresponding relationship between the impedance spectrum change and the change of the impedance model parameters, so as to further diagnose battery faults according to the impedance spectrum;

[0033] Step S4: Detect the EIS of a healthy state battery under given temperature, SOC, and charge and discharge rate as a reference benchmark for the healthy state in battery fault diagnosis; then during subsequent battery balancing, detect the battery EIS under the same detection conditions for the battery management system to perform fault diagnosis;

[0034] Step S5: After obtaining the battery EIS, compare and analyze it with the historical EIS information of the battery in the healthy state, obtain the resistance increment of the ohmic resistance and the charge transfer resistance, and set a threshold; diagnose the battery with the resistance increment reaching the threshold as a fault state, analyze possible fault types; and assist in diagnosing battery aging and impedance inconsistency during the long-term operation of the battery pack.

[0035] Furthermore, step S1 specifically includes the following steps:

[0036] Establish an energy bidirectional transfer type balancing circuit as the active balancer ICE, connect an active balancer ICE between two batteries, and realize the energy transfer and mutual excitation between the two batteries by controlling the on and off of different switching tubes;

[0037] Take the discharging battery at the input end of the equalization circuit as the power supply DC source; take the battery at the load end in the excited state as the battery under test;

[0038] Considering the requirements of electrochemical impedance spectroscopy detection, the battery must be in a balanced state or under a certain stable DC polarization condition for perturbation and excitation.

[0039] Therefore, after the equalization current reaches the steady state, in the closed-loop controller of the equalization current, a sine signal is injected into the reference value of the current; thus, the superimposed current is used to excite the battery under test at the load end; among them, the excitation current for the battery is composed of the DC current I dc superimposed with the AC perturbation current I m sin(ωt), which is expressed as:

[0040] I dc +I m sin(ωt)(1)

[0041] Since the EIS detection and the battery management system share the sampling module to collect information, the range of the perturbation frequency needs to consider the limitation of the sampling frequency of the analog front-end chip therein. At the same time, considering the sampling theorem and the requirements of engineering practice, the upper and lower limits of the perturbation frequency are determined comprehensively.

[0042] Further, step S2 specifically includes the following steps:

[0043] Inject a multi-frequency periodic signal into the reference current. After the current starts to excite the battery under test, separate the AC and DC signals of the voltage and current in the signal conditioning circuit;

[0044] Adopt the method of inverting and superimposing the effective values to remove the influence of the DC and high-frequency noise interference signals and amplify the AC signal; then, the sampling module in the battery management system synchronously collects the voltage and current signals of the battery under test after conditioning at the frequency f S ;

[0045] In engineering practice, considering the sampling accuracy and frequency aliasing problems, the sampling frequency f S is usually taken as 5 to 10 times or more of the highest frequency in the frequency band under test, and the sampling period is generally selected to be at least 2 times or more of the lowest frequency period of the perturbation signal.

[0046] After obtaining the voltage and current data, perform FFT fast Fourier transform on the battery voltage and current data in the digital controller or computer of the battery management system. Select the complex signal of the current peak point above a given amplitude through the algorithm, and select the complex signal of the voltage peak point corresponding to the frequency of the current peak point; perform operations on the complex signals of the voltage and current peak points at this frequency to obtain the complex impedance information at this frequency:

[0047]

[0048] where θ(f) is the phase difference between voltage and current at this frequency; V p (f) is the amplitude at the peak point of the voltage at this frequency; I p (f) is the amplitude at the peak point of the current at this frequency. R is the real part of the complex impedance, and X is the imaginary part of the complex impedance.

[0049] The algorithm program can obtain multiple impedance information within the disturbance frequency range at one time, and draw the battery electrochemical impedance spectrum within the disturbance frequency range.

[0050] Furthermore, step S3 specifically includes the following steps:

[0051] Establish a battery impedance equivalent model to describe and analyze the corresponding relationship between the change of EIS and the change of battery impedance parameters: Select the Randles equivalent model of battery impedance, which includes several parts such as high-frequency inductance, ohmic resistance, charge transfer resistance, double-layer capacitance, and Warburg diffusion impedance.

[0052] The straight part in the high-frequency region of the electrochemical impedance spectrum corresponds to the high-frequency inductance impedance; the left intersection point of the semicircular arc of the impedance spectrum and the real axis corresponds to the ohmic resistance; the semicircular arc in the middle-frequency region corresponds to the impedance of the charge transfer resistance and the double-layer capacitance; the 45° diagonal line in the low-frequency region corresponds to the Warburg diffusion impedance.

[0053] When the battery health state deteriorates, the high-frequency part of its EIS basically remains unchanged; the diagonal line of the diffusion impedance in the low-frequency region is also basically parallel; the main changes in the impedance spectrum occur in the ohmic resistance and charge transfer resistance parts, that is, obvious changes occur in the semicircular arc part in the middle-frequency region; ignoring the impedance spectrum parts in the high-frequency region and the low-frequency region does not affect the judgment of the change of the battery EIS, and can also shorten the time required for EIS detection. At the same time, because the high-frequency inductance has little effect at medium and low frequencies and the measurement time is relatively short, and the substance has no time to diffuse, the Warburg diffusion impedance and the high-frequency inductance impedance can be not considered in the model.

[0054] Therefore, the Randles model of the battery impedance is further simplified into three parts: ohmic resistance, charge transfer resistance, and double-layer capacitance. It can reduce the analysis difficulty of the battery impedance equivalent model and does not have an essential impact on the circuit characteristics of the battery impedance model. Determine the magnitude of the ohmic resistance through the left intersection point of the semicircular arc of the impedance spectrum and the real axis, and determine the magnitude of the charge transfer resistance by the diameter of the semicircular arc in the middle-frequency region, and diagnose the battery fault based on the changes of these parameters.

[0055] Furthermore, step S4 specifically includes the following steps:

[0056] Using an EIS detection device and method, at a certain temperature, SOC, and charging rate, the EIS at the initial stage of the healthy battery life is detected and used as a reference benchmark in battery fault analysis. The ohmic resistance is determined by the left intersection point of the impedance spectrum semi-circular arc line and the real axis, and the charge transfer resistance is determined by the diameter of the semi-circular arc in the intermediate frequency region. This information is stored in the storage device of the diagnostic equipment. In subsequent fault diagnosis of power batteries, the EIS of the battery is detected under the same detection conditions.

[0057] Further, step S5 specifically includes the following steps:

[0058] After obtaining the EIS of a single battery in subsequent detection, it is compared with the EIS of the healthy state of the battery, and the resistance value increments of the ohmic resistance and the charge transfer resistance are calculated, and a threshold for the resistance value increment is set; when the resistance value increment of the battery reaches the set threshold, it is diagnosed as a battery fault; the fault information is fed back to the battery management system. The threshold for the resistance value increment corresponding to the fault state is determined comprehensively by experiments.

[0059] When the ohmic resistance increases, the EIS image shifts to the right along the real axis relative to the EIS image of the healthy battery. The resistance value increment of the ohmic resistance is the difference between the left intersection point of the real axis of the current EIS and the left intersection point of the real axis of the healthy state EIS. Under the same detection conditions, when the ohmic resistance increases significantly, it is considered that the resistance of the electrode material and the separator increases, or the contact resistance of each part increases, such as virtual connection. When the ohmic resistance decreases, the EIS image shifts to the left along the real axis relative to the EIS image of the healthy battery. In practice, the situation of decreasing ohmic resistance rarely occurs, but when it occurs, it may be a micro-short circuit inside the battery.

[0060] The resistance value of the charge transfer resistance is manifested as the diameter of the semi-circular arc in the intermediate frequency region in the EIS. When the charge transfer resistance becomes larger, the height of the semi-circular arc increases along the imaginary axis direction, and the diameter of the semi-circular arc increases; when the charge transfer resistance becomes smaller, the diameter of the impedance spectrum semi-circular arc and the height in the imaginary axis direction decrease. Under the same detection conditions, if the charge transfer resistance increases significantly, it is considered that the impedance of the positive electrode increases, the positive electrode material may undergo physical and chemical changes, or the battery is aging; when the charge transfer resistance decreases, it is also considered that there is a micro-short circuit inside the battery.

[0061] Further, the resistance value increment is used to assist in diagnosing the degree of battery aging and the inconsistency between batteries.

[0062] Battery aging will cause the resistance values of the ohmic resistance and the charge transfer resistance to increase significantly. After obtaining the resistance value increments of the ohmic resistance and the charge transfer resistance, a threshold for aging and retirement is set according to experimental data. For batteries whose resistance value increments and cycle times both reach the retirement level, a basis for battery replacement and maintenance is provided.

[0063] During the long-term operation of the battery pack, the impedance consistency of the individual cells within the pack will change. If the inconsistency of the impedance between individual cells is too large, it will affect the performance and lifespan of the entire battery pack. Therefore, by using the above-mentioned device and method of the present invention, the ohmic resistance and charge transfer resistance of each individual cell are detected, and an inconsistency threshold is set to judge the impedance inconsistency of the individual cells within the battery pack. For batteries that exceed the inconsistency threshold, replacement or maintenance is carried out.

[0064] Compared with the prior art, the beneficial effects of the present invention and its preferred embodiments include:

[0065] 1. It can realize the functional integration of battery EIS detection, battery active balancing, and battery fault diagnosis; and realize the application expansion and hardware sharing of the balancing circuit.

[0066] 2. The device has two modes, namely the diagnostic mode and the balancing mode. Different functions can be realized in different modes. In the balancing mode, the active balancing between batteries can be carried out using the balancing circuit. In the diagnostic mode, the balancing circuit can be used to provide energy excitation to the battery under test.

[0067] 3. Through the battery EIS obtained by the above-mentioned diagnostic device, the resistance increments of the ohmic resistance and charge transfer resistance are calculated, and then the faults of the power battery are diagnosed online, and the possible fault types are preliminarily analyzed, providing a basis for fault handling.

[0068] 4. By monitoring the battery EIS, the impedance inconsistency within the battery pack can be monitored during long-term operation, providing a diagnostic basis for impedance inconsistency; and providing a diagnostic basis for the battery to reach the end of its life due to aging. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments:

[0070] Figure 1 It is a schematic diagram of the fault diagnosis process of an embodiment of the present invention;

[0071] Figure 2 It is a schematic diagram of the Randles equivalent model for describing the impedance characteristics of the battery and the corresponding impedance spectrum of an embodiment of the present invention;

[0072] Figure 3 It is the electrochemical impedance spectrum of a healthy state battery obtained by simulation in an embodiment of the present invention;

[0073] Figure 4 It is the EIS obtained by simulating the change of the ohmic resistance in an embodiment of the present invention. The solid line part is the EIS of a normal battery, the dashed line part is the EIS of a faulty battery, and the dotted dashed line part of the circle is the EIS of the faulty battery estimated by the FFT algorithm in this solution. The upper part of the figure shows the simulation of the increase in the ohmic resistance, and the lower part shows the simulation of the decrease in the ohmic resistance;

[0074] Figure 5 This is the EIS obtained by simulating the change of charge transfer resistance in the embodiments of the present invention. In the figure, the upper part shows the simulation of an increase in charge transfer resistance, and the lower part shows the simulation of a decrease in charge transfer resistance. Detailed implementation manners

[0075] To make the features and advantages of this patent more obvious and understandable, specific embodiments are given below for detailed description as follows:

[0076] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used in this specification have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs.

[0077] It should be noted that the terms used herein are only for describing specific implementation manners and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0078] In this embodiment, a power battery on-line diagnosis device based on a bidirectional active equalization circuit is taken as an example for further analysis.

[0079] As Figure 1 shown, it is the architecture of a power battery on-line diagnosis device based on a bidirectional active equalization circuit. In the bidirectional active equalization circuit, the control switch tube is used to supply power to the input-end battery and excite the load-end battery. Electrochemical impedance spectroscopy detection requires the battery to be in a balanced state or a certain stable DC polarization condition, so a constant current test is adopted to excite the battery under a constant current state.

[0080] After the current reaches a steady state, a multi-frequency periodic sine signal is injected into the current reference value of the current control loop, and the superposed current is used to excite the battery under test at the load end. The excitation current of the battery is obtained by superimposing the DC current I dc with the AC perturbation current I m sin(ωt), which is expressed as:

[0081] I dc +I m sin(ωt) (1)

[0082] After injecting the perturbation signal into the current reference value, the sampling module in the battery management system synchronously collects the voltage signal and battery current signal at both ends of the battery at a frequency f S to obtain time-domain voltage and current data.

[0083] Then, the obtained voltage and current data are subjected to FFT fast Fourier transform in the digital controller or microcomputer of the battery management system to obtain complex voltage and current signals containing real and imaginary parts.

[0084] The algorithm selects the current peak point signal above a certain amplitude and the voltage peak point signal corresponding to the current peak point frequency. The complex signals of the voltage and current peak points at this frequency are calculated to obtain the complex impedance information at this frequency:

[0085]

[0086] Where θ(f) is the phase difference between voltage and current at this frequency; V p (f) is the peak value of the voltage at this frequency; I p (f) is the peak current amplitude at this frequency. R is the real part of the complex impedance, and X is the imaginary part of the complex impedance.

[0087] After obtaining the impedance information corresponding to a series of perturbation frequencies, the battery EIS within the perturbation frequency range can be plotted.

[0088] Establish a suitable battery impedance equivalent model to describe the different components of battery impedance and determine the corresponding relationship between EIS changes and changes in battery impedance parameters. During long-term battery operation, the main changes in the impedance spectrum occur in the ohmic resistance and charge transfer resistance, that is, the semicircular part of the mid-frequency region undergoes significant changes, so the impedance spectrum parameters are selected in the mid-frequency region.

[0089] like Figure 2 As shown in the figure, it is a Randles impedance model and its corresponding EIS schematic diagram. In this embodiment, the simplified battery impedance Randles model is selected to describe the battery impedance, which includes three parts: ohmic resistance, charge transfer resistance, and double-layer capacitance. Such simplification can reduce the difficulty of analyzing the impedance equivalent model and does not have an essential impact on the characteristics of the impedance circuit. The resistance values of ohmic resistance and charge transfer resistance can be obtained by the key features on the EIS image corresponding to the Randles impedance model. The size of the ohmic resistance is determined by the left intersection of the semicircular arc line of the impedance spectrum and the real axis, and the size of the charge transfer resistance is determined by the diameter of the semicircular arc in the intermediate frequency region.

[0090] First, the battery cells that are in the early stages of their life and in good health are tested to obtain the EIS of the battery at a certain temperature, SOC, and charge rate. The values of the ohmic resistance and charge transfer resistance are obtained, and this information is stored in the device's storage device as the health status baseline information for subsequent diagnosis of the battery.

[0091] like Figure 3As shown, it is the EIS of a healthy battery determined by the method of the present invention. A bidirectional equalization circuit and a battery impedance Randles model are built in Simulink software, and a multi-frequency sine superposition signal with a maximum frequency of 300 Hz and a minimum frequency of 0.1 Hz is added. According to the method of the invention, the current output by the equalization circuit is used to excite the battery impedance model to obtain battery voltage and current data, and the EIS of the battery impedance model within the disturbance frequency range is obtained by solving and plotting via the FFT algorithm.

[0092] Then, during the subsequent operation of the battery, the EIS information of the battery is obtained using the same detection conditions and methods as those of the healthy battery EIS. By comparing it with the normal battery EIS, the resistance increments of the ohmic resistance and the charge transfer resistance can be calculated, and the threshold of the resistance increment is set. When the resistance increment of the battery is abnormally large and reaches the fault level, it is diagnosed as a battery fault.

[0093] As Figures 4 to 5 shown, the parameter values of the battery Randles impedance model in the simulation are modified to simulate the cases where the ohmic resistance and the charge transfer resistance of the battery change respectively. Using the same detection conditions and methods, the EIS estimated by the algorithm after the impedance change is obtained, and the change of the battery EIS after the change of the ohmic resistance and the charge transfer resistance can be intuitively seen. The increment of the ohmic resistance is obtained from the translation distance of the EIS semi-circle along the real axis, and the resistance increment of the charge transfer resistance can be obtained from the increment of the diameter of the EIS semi-circle.

[0094] As Figure 4 shown in the upper part of [], when the ohmic resistance increases, the EIS image shifts to the right along the real axis relative to the EIS image of the healthy battery. When the increment of the ohmic resistance exceeds the threshold, the possible faults include abnormal electrode materials, increased diaphragm resistance, or increased contact resistance of each part of the parts, such as virtual connection.

[0095] As Figure 4 shown in the lower part of [], when the ohmic resistance decreases, the EIS image shifts to the left along the real axis relative to the EIS image of the healthy battery. In practice, the situation of decreasing ohmic resistance rarely occurs, but when it occurs, it may be due to a micro short circuit inside the battery.

[0096] As Figure 5 shown in the upper part of [], when the charge transfer resistance increases, the height of the EIS semi-circle increases along the imaginary axis direction, and the diameter of the semi-circle increases. When the increment of the charge transfer resistance exceeds the threshold, it is considered that the positive electrode impedance increases or the battery ages.

[0097] As Figure 5 shown in the lower part of [], when the charge transfer resistance decreases, the height of the EIS semi-circle decreases along the imaginary axis direction, and the diameter of the semi-circle decreases. In practice, it is also considered that there is a micro short circuit inside the battery.

[0098] The resistance increment threshold corresponding to different fault states is determined by the comprehensive consideration of the tests of specific model batteries and engineering experience.

[0099] During long-term monitoring, by recording the battery cycle count and resistance increment, it is possible to comprehensively determine whether the battery has reached the degree of aging and retirement. By comparing the detection results of the EIS of each cell in the battery pack and comparing the resistance values of the ohmic resistance and charge transfer resistance of each cell, it is possible to screen out the cells with inconsistency exceeding the threshold.

[0100] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention in any other form. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

[0101] This patent is not limited to the above best implementation manner. Anyone inspired by this patent can obtain various other forms of power battery diagnostic devices and methods based on the balancing circuit. All equal changes and modifications made according to the scope of the patent application of the present invention shall fall within the scope covered by this patent.

Claims

1. A power battery diagnostic device based on a balancing circuit, characterized in that, Including: battery active balancing circuit, battery string combination, signal conditioning circuit, PWM drive circuit, information storage device and battery management system; When working, it is used to inject a multi-frequency periodic signal into the reference current of the balancing circuit, and the battery is stimulated by the output current; Battery voltage and current data are sampled and processed by fast Fourier transform to obtain the battery's electrochemical impedance spectrum. A battery impedance model is established to analyze changes in the electrochemical impedance spectrum. During diagnosis, the battery's electrochemical impedance spectrum is obtained under the same testing conditions and compared with historical information to obtain the resistance increments of the ohmic resistance and charge transfer resistance, and an increment threshold is set. When the increment exceeds the threshold, a battery fault is diagnosed and the fault type is analyzed. There are two operating modes: diagnostic mode and balancing mode: In diagnostic mode, the impedance spectrum information of the single battery is detected through the EIS detection device based on active balancing, and battery faults are diagnosed based on changes in EIS information; In balancing mode, the bidirectional balancing circuit in the diagnostic device balances the battery SOC. SOC information for individual cells is obtained through SOC estimation methods. When the SOC of a battery connected to one end of the balancing circuit is higher than that of the battery at the other end, the SOC difference is used as a balancing criterion. When the difference exceeds a set threshold, balancing is initiated. The end with the higher SOC serves as the input end, and the end with the lower SOC serves as the load end. The PWM signal output by the balancing control circuit controls the on-off switching of the switch, discharging the input end battery and charging the output end battery with balancing current. When the SOC difference converges to within the balancing threshold, SOC balancing between the batteries is terminated. In the diagnostic device, the active balancing circuit is connected to the battery string; the voltage and current signal ends of the battery string are connected to the signal conditioning circuit; the output end of the signal conditioning circuit is connected to the ADC pin of the battery management system sampling module; the PWM output end of the digital controller is connected to the input end of the PWM drive circuit; the output end of the PWM drive circuit is connected to the gate of each switch tube in the active balancing circuit; and the information storage device is connected to the I / O port of the battery management system.

2. The power battery diagnosis device based on a balancing circuit according to claim 1, characterized in that: Based on the active balancing circuit, the active balancing circuit is used as the power circuit to provide excitation; The active balancing circuit is a bidirectional energy transfer balancing circuit. The number of batteries that can be diagnosed by the device is determined by the number of batteries connected to the balancing circuit, which includes X cells, where X≥2.

3. A power battery diagnosis method based on a balancing circuit, characterized in that: According to the power battery diagnostic device based on the balancing circuit as claimed in claim 1: The following steps are involved: Step S1: Using a battery EIS detection device based on active balancing, after the current reaches a steady state, a multi-frequency periodic signal is injected into the current reference value of the current control loop, thereby superimposing the current to stimulate the battery under test at the load end; Step S2, after injecting the perturbation signal, the sampling module of the battery management system synchronously collects the voltage and current signals of the battery at a frequency f S ; perform fast Fourier transform (FFT) on the voltage and current information in the digital controller or microcomputer of the battery management system, and obtain the impedance information at multiple perturbation frequencies at one time by the algorithm, so as to obtain the EIS information within a certain frequency range; Step S3, establishing a battery impedance equivalent model to analyze the corresponding relationship between the impedance spectrum changes and the impedance model parameter changes, so as to further diagnose battery faults based on the impedance spectrum; Step S4, detect the EIS of the healthy state battery at a given temperature, SOC, and charge-discharge rate, which serves as the reference benchmark for the healthy state in battery fault diagnosis; then, when performing subsequent battery balancing, detect the battery EIS under the same detection conditions for the battery management system to conduct fault diagnosis; Step S5, after obtaining the battery EIS, compare and analyze it with the historical EIS information of the battery in the healthy state, obtain the resistance increments of the ohmic resistance and charge transfer resistance, and set thresholds; diagnose the battery with a resistance increment reaching the threshold as a fault state, analyze possible fault types; and assist in diagnosing battery aging and impedance inconsistency during the long-term operation of the battery pack.

4. The power battery diagnosis method based on an equalization circuit according to claim 3, wherein: Step S1 specifically includes the following steps: Establish an energy bidirectional transfer type equalization circuit as the active equalizer ICE. Connect an active equalizer ICE between two batteries. By controlling the on-off of different switching tubes, realize the energy transfer and mutual excitation between the two batteries; Regard the discharging battery at the input end of the equalization circuit as the power supply DC source; regard the battery at the load end in the excited state as the battery to be tested; After the balancing current reaches a steady state, in the closed-loop controller of the balancing current, a sine signal is injected into the reference value of the current; thereby, the superimposed current is used to excite the battery under test at the load end; wherein the excitation current for the battery is obtained by superimposing a DC current I dc and an AC perturbation current I m sin(ωt), expressed as: I dc +I m sin(ωt) (1) Simultaneously consider the requirements of the sampling theorem and engineering practice, and comprehensively determine the upper and lower limits of the perturbation frequency.

5. The power battery diagnosis method based on an equalization circuit according to claim 3, wherein: Step S2 specifically includes the following steps: Inject multi-frequency periodic signals into the reference current. After the current starts to excite the battery to be tested, separate the AC and DC signals of the voltage and current of the battery to be tested in the signal conditioning circuit; The method of inverse superposition of effective values is adopted to remove the influence of DC and high-frequency noise interference signals and amplify the AC signals; then the sampling module in the battery management system synchronously samples the conditioned battery voltage and current signals at a frequency f S ​ After obtaining the voltage and current data, perform FFT fast Fourier transform on the battery voltage and current data in the digital controller or computer of the battery management system. Select the complex signal of the current peak point above a given amplitude through the algorithm, and select the complex signal of the voltage peak point corresponding to the frequency of this current peak point; perform operations on the complex signals of the voltage and current peak points at this frequency to obtain the complex impedance information at this frequency: where θ(f) is the phase difference between voltage and current at this frequency; V p (f) is the amplitude of the voltage peak point at this frequency; I p (f) is the amplitude of the current peak point at this frequency; R is the real part of the complex impedance, and X is the imaginary part of the complex impedance; Obtain multiple impedance information within the perturbation frequency range at one time, and draw the electrochemical impedance spectrum of the battery within the perturbation frequency range.

6. The power battery diagnosis method based on an equalization circuit according to claim 3, wherein: Step S3 specifically includes the following steps: Establish a battery impedance equivalent model to describe and analyze the corresponding relationship between the change of EIS and the change of battery impedance parameters: select the Randles equivalent model of the battery impedance; The straight part in the high-frequency region of the electrochemical impedance spectrum corresponds to the high-frequency inductance impedance; the left intersection point of the semicircular arc line of the impedance spectrum and the real axis corresponds to the ohmic resistance; the semicircular arc in the intermediate frequency region corresponds to the impedance of the charge transfer resistance and the double-layer capacitor; the 45° diagonal line in the low-frequency region corresponds to the Warburg diffusion impedance; The model does not consider the Warburg diffusion impedance and the high-frequency inductance impedance; The Randles model of battery impedance is further simplified into three parts: ohmic resistance, charge transfer resistance, and double-layer capacitance. The magnitude of the ohmic resistance is determined by the left intersection point of the impedance spectrum semi-circular arc line and the real axis, and the magnitude of the charge transfer resistance is determined by the diameter of the semi-circular arc in the intermediate frequency region. Battery faults are diagnosed based on the changes in the ohmic resistance and charge transfer resistance.

7. The power battery diagnosis method based on the equalization circuit according to claim 3, characterized in that: Step S4 specifically includes the following steps: At a given temperature, SOC, and charging rate, the EIS at the initial stage of the healthy battery life is detected and used as a reference benchmark in battery fault analysis. The magnitude of the ohmic resistance is determined by the left intersection point of the impedance spectrum semi-circular arc line and the real axis, and the magnitude of the charge transfer resistance is determined by the diameter of the semi-circular arc in the intermediate frequency region. This information is stored in the storage device of the diagnostic device. In subsequent fault diagnosis of the power battery, the EIS of the battery is detected under the same detection conditions.

8. The power battery diagnosis method based on the equalization circuit according to claim 3, characterized in that: Step S5 specifically includes the following steps: After obtaining the EIS of the single battery in subsequent detections, it is compared with the EIS of the same battery in a healthy state, and the resistance increments of the ohmic resistance and charge transfer resistance are calculated, and the threshold of the resistance increment is set. When the resistance increment of the battery reaches the set threshold, it is diagnosed as a battery fault, and the fault information is fed back to the battery management system; When the ohmic resistance increases, the EIS image shifts to the right along the real axis relative to the EIS image of the healthy battery. The resistance increment of the ohmic resistance is the difference between the left intersection point of the real axis of the current EIS and the left intersection point of the real axis of the EIS in the healthy state. Under the same detection conditions, when the ohmic resistance increases significantly, it is considered that the resistance corresponding to the electrode material and diaphragm increases, or the contact resistance of each part increases; when the ohmic resistance decreases, the EIS image shifts to the left along the real axis relative to the EIS image of the healthy battery, considering that there is a micro short circuit inside the battery. The magnitude of the charge transfer resistance is manifested as the diameter of the semi-circular arc in the intermediate frequency region in the EIS. When the charge transfer resistance becomes larger, the height of the semi-circular arc increases along the imaginary axis direction, and the diameter of the semi-circular arc increases; when the charge transfer resistance becomes smaller, the diameter of the impedance spectrum semi-circular arc and the height in the imaginary axis direction decrease. Under the same detection conditions, if the charge transfer resistance increases significantly, it is considered that the impedance of the positive electrode increases, the positive electrode material may undergo physical and chemical changes, or the battery has aged; when the charge transfer resistance decreases, it is considered that there is a micro short circuit inside the battery.

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