Battery impedance spectrum measurement method, system, equipment, and medium based on grid-connected energy storage converter

Abstract

This invention relates to the field of power electronic converter control technology, and particularly to a method, system, device, and medium for measuring battery impedance spectrum based on a grid-connected energy storage converter. The method first determines multiple target frequencies based on the measurement frequency band of the impedance spectrum to be measured, and generates a small-signal disturbance reference quantity for the current target frequency. This disturbance reference quantity is then superimposed with the nominal control reference quantity used by the grid-connected energy storage converter to maintain the AC-side voltage amplitude, frequency, and phase, thus embedding the impedance measurement excitation into the grid-connected control process. Subsequently, the disturbance is transmitted to the battery side using the AC / DC power coupling of the converter, and the battery terminal voltage and current are synchronously sampled. The voltage and current frequency domain response components corresponding to the target frequencies are extracted, and the battery complex impedance at each target frequency is calculated and the online impedance spectrum is reconstructed. This reduces the impact of impedance measurement disturbances on AC-side voltage support, frequency maintenance, and power regulation.

Description

Technical Field

[0001] This invention relates to the field of power electronic converter control technology, and in particular to a method, system, device and medium for measuring battery impedance spectrum based on grid-connected energy storage converter. Background Technology

[0002] With the increasing penetration of renewable energy and electrochemical energy storage in power systems, the safety, reliability, and lifespan management of battery energy storage systems are becoming increasingly prominent issues. The operating status of batteries directly affects the power support capacity and service life of energy storage power stations, thus requiring the establishment of accurate, timely, and on-site condition monitoring methods.

[0003] Electrochemical impedance spectroscopy (EIS), as an important method for characterizing the internal electrochemical processes of batteries, can reflect ohmic impedance, charge transfer processes, polarization effects, and diffusion behavior, and is of great significance for battery state estimation and health assessment. However, most existing impedance spectroscopy measurements rely on dedicated electrochemical workstations or impedance analyzers, and are usually performed offline, resulting in high testing costs and long testing times, making it difficult to meet the online monitoring needs of energy storage systems.

[0004] In recent years, some online impedance measurement schemes have attempted to reuse the existing power conversion interface of battery systems, obtaining the battery's frequency domain response by introducing disturbances into the converter control loop. Such schemes can reduce additional hardware configuration, but existing research mostly focuses on DC / DC converters or inverters in normal operating modes, with insufficient consideration for grid-connected energy storage converter scenarios. Grid-connected energy storage converters not only undertake AC / DC power exchange but also need to establish and maintain the AC side voltage amplitude, frequency, and phase; their control objectives are coupled with online impedance measurement. However, if existing online impedance methods are directly applied, disturbance signals may affect AC side voltage support, power regulation, and even system stability. Summary of the Invention

[0005] In view of this, in order to solve the above-mentioned technical problems, the present invention provides a method, system, device and medium for measuring battery impedance spectrum based on grid-connected energy storage converter.

[0006] The first aspect of this invention provides a method for measuring battery impedance spectrum based on a grid-connected energy storage converter, the method comprising: Based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, multiple target frequencies for battery impedance identification are determined, and corresponding small signal perturbation reference quantities are generated based on the current target frequency. Obtain the nominal control reference value used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and superimpose the small signal disturbance reference value onto the nominal control reference value to obtain a unified control reference value; The grid-type energy storage converter is modulated and controlled according to the unified control reference quantity. After the small signal disturbance is transmitted to the battery side through the AC / DC power coupling of the grid-type energy storage converter, the battery terminal voltage and battery current on the battery side are synchronously sampled. The voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the sampled battery terminal voltage data and battery current data. Based on the ratio between the voltage frequency domain response component and the current frequency domain response component, the battery complex impedance corresponding to the current target frequency is determined, and the battery complex impedance determination process is repeated for each target frequency. Each target frequency is associated with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

[0007] In one example, the step of determining multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and generating corresponding small-signal perturbation reference quantities based on the current target frequencies, includes: Based on the electrochemical process to be covered by the impedance spectrum of the battery under test, determine the start and end frequencies of the measurement frequency band; The number of target frequencies and the frequency interval method are determined according to the purpose of impedance spectrum measurement, and a target frequency set consisting of the multiple target frequencies is generated between the starting frequency and the ending frequency. The perturbation injection sequence, angular frequency, perturbation amplitude, and perturbation phase of each target frequency are determined based on the target frequency set. The current target frequency is determined from the target frequency set according to the perturbation injection order, and the small signal perturbation reference quantity is generated based on the target angular frequency, target perturbation amplitude, and target perturbation phase corresponding to the current target frequency.

[0008] In one example, the acquisition of the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency, and phase under the current operating state, and the superposition of the small-signal disturbance reference quantity onto the nominal control reference quantity to obtain a unified control reference quantity, includes: Obtain the active power reference value, reactive power reference value, measured active power, and measured reactive power of the grid-type energy storage converter; Based on the active power reference value, the reactive power reference value, the measured active power and the measured reactive power, and in conjunction with the grid control parameters, the internal angular frequency, phase angle and fundamental voltage reference of the grid-type energy storage converter are determined. The nominal control reference value is generated based on the internal angular frequency, the phase angle, and the fundamental voltage reference value. According to the preset disturbance injection channel, the small signal disturbance reference quantity is superimposed on the nominal control reference quantity to obtain the unified control reference quantity.

[0009] In one example, the modulation control of the grid-type energy storage converter based on the unified control reference value, so that the small-signal disturbance is transmitted to the battery side via AC / DC power coupling of the grid-type energy storage converter, synchronously samples the battery terminal voltage and battery current on the battery side, and extracts the voltage frequency domain response component and the current frequency domain response component, including: Based on the unified control reference quantity, a modulation signal is generated for controlling the power switching devices in the grid-type energy storage converter; The modulation signal is used to control the grid-type energy storage converter to perform AC-DC power conversion, so that the AC side generates a power oscillation component corresponding to the current target frequency, and the power oscillation component is transmitted to the battery side through AC-DC power coupling; The injection start time of the small signal disturbance reference quantity and the current target frequency are obtained, and the battery terminal voltage and the battery current are sampled synchronously. Based on the injection start time, a steady-state data window is determined from the sampled battery terminal voltage data and battery current data, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the steady-state data window.

[0010] In one example, determining a steady-state data window from the sampled battery terminal voltage data and battery current data includes: Based on the injection start time, the transient data after the injection of the small signal disturbance reference quantity is removed from the battery terminal voltage data and the battery current data; The steady-state data window is formed by selecting a preset number of complete cycles of data containing the current target frequency after the transient data.

[0011] In one example, the process of determining the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component, and repeating the battery complex impedance determination process for each target frequency to correlate each target frequency with the corresponding battery complex impedance, thereby obtaining the battery online impedance spectrum, includes: Calculate the battery complex impedance corresponding to the current target frequency based on the complex ratio between the voltage frequency domain response component and the current frequency domain response component corresponding to the current target frequency; The current target frequency is associated with and stored with the corresponding battery complex impedance to form a current frequency-complex impedance data pair; According to the perturbation injection order corresponding to the target frequency set, each target frequency is taken as the current target frequency in turn, and the battery complex impedance calculation process is repeated for each current target frequency to obtain the frequency-complex impedance data pair corresponding to each target frequency; The frequency-complex impedance data pairs are arranged according to the frequency order of the target frequency set to obtain the online impedance spectrum of the battery.

[0012] In one example, after obtaining the online impedance spectrum of the battery, the process further includes: Based on the impedance spectrum bands to which each target frequency belongs, the online impedance spectrum of the battery is divided into high-frequency region, mid-frequency region and low-frequency region; High-frequency ohmic resistance and inductance features are extracted based on the high-frequency impedance data. Interface film features, charge transfer features and Nyquist curve arc geometry features are extracted based on the high-frequency impedance data and the mid-frequency impedance data. Diffusion impedance features and low-frequency polarization trends are extracted based on the low-frequency impedance data. The extracted features are combined into a battery state feature vector according to a preset feature order. Obtain reference feature values ​​that correspond one-to-one with each feature in the battery state feature vector, and combine the reference feature values ​​into a reference feature vector according to the preset feature order; The battery state feature vector and the reference feature vector are normalized, and the feature offset of the battery state feature vector relative to the reference feature vector is determined. The battery status assessment result is determined based on the feature offset.

[0013] Secondly, the present invention also provides a battery impedance spectrum measurement system based on a grid-connected energy storage converter, the system comprising: The disturbance reference determination module is used to determine multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and to generate corresponding small signal disturbance reference quantities based on the current target frequencies. The control reference determination module is used to obtain the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and to superimpose the small signal disturbance reference quantity onto the nominal control reference quantity to obtain a unified control reference quantity. The response component determination module is used to modulate and control the grid-type energy storage converter according to the unified control reference quantity, so that the small signal disturbance is transmitted to the battery side through the AC / DC power coupling of the grid-type energy storage converter, and the battery terminal voltage and battery current on the battery side are synchronously sampled, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the sampled battery terminal voltage data and battery current data. The impedance spectrum determination module is used to determine the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component, and to repeatedly perform the battery complex impedance determination process for each target frequency, thereby associating each target frequency with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

[0014] Thirdly, the present invention also provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, the computer program being executed by the processor causing the processor to perform the steps of the battery impedance spectrum measurement method based on the grid-connected energy storage converter as described in the first aspect.

[0015] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the steps of the battery impedance spectrum measurement method based on a grid-connected energy storage converter as described in the first aspect.

[0016] As can be seen from the above technical solution, this invention first determines multiple target frequencies based on the measurement frequency band of the impedance spectrum to be measured, and generates a small-signal disturbance reference quantity for the current target frequency. Then, this disturbance reference quantity is superimposed with the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency, and phase, thus embedding the impedance measurement excitation into the grid control process. Subsequently, the disturbance is transmitted to the battery side using the AC / DC power coupling of the converter, and the battery terminal voltage and battery current are synchronously sampled. The voltage and current frequency domain response components corresponding to the target frequencies are extracted, and the battery complex impedance at each target frequency is calculated and the online impedance spectrum is reconstructed. Therefore, since the small-signal disturbance and the nominal control reference quantity used to maintain grid operation are uniformly incorporated into the control command, rather than being applied separately from the grid control, the impact of impedance measurement disturbance on AC side voltage support, frequency maintenance, and power regulation can be reduced. This improves the problem of inconsistency between traditional online impedance measurement methods and grid control objectives, and provides a continuous and timely impedance spectrum data basis for energy storage battery operation status monitoring and health assessment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an application environment diagram of a battery impedance spectrum measurement method based on a grid-connected energy storage converter provided in an embodiment of the present invention; Figure 2 A flowchart of a battery impedance spectrum measurement method based on a grid-connected energy storage converter is provided for an embodiment of the present invention; Figure 3 This is a schematic diagram of the characteristic regions of the battery impedance spectrum. Figure 4 This is a schematic diagram of the battery impedance equivalent circuit and frequency domain decomposition. Figure 5 Inject the overall control block diagram into the small signal; Figure 6 This is a schematic diagram of the online impedance measurement principle of a grid-type energy storage converter battery based on embedded perturbation injection. Figure 7 Nyquist plot of measured impedance of battery in the 1Hz–10kHz frequency band; Figure 8a Bode plot of impedance amplitude versus frequency in the 1Hz–10kHz frequency band; Figure 8b Bode plot of impedance phase angle as a function of frequency in the 1Hz–10kHz frequency band; Figure 9 A schematic diagram of a battery impedance spectrum measurement system based on a grid-connected energy storage converter provided in an embodiment of the present invention; Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] The battery impedance spectrum measurement method based on grid-connected energy storage converters provided in this application can be applied to, for example... Figure 1In the application environment shown, terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102 or placed on a cloud or other network server. Terminal 101 or server 102 executes a battery impedance spectrum measurement method based on a grid-connected energy storage converter. This method includes: determining multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and generating corresponding small-signal disturbance reference quantities based on the current target frequencies; acquiring the nominal control reference quantities used by the grid-connected energy storage converter to maintain the AC side voltage amplitude, frequency, and phase under the current operating state; superimposing the small-signal disturbance reference quantities onto the nominal control reference quantities to obtain a unified control reference quantity; and performing modulation control on the grid-connected energy storage converter based on the unified control reference quantity. After the small-signal disturbance is transmitted to the battery side via AC / DC power coupling of the grid-type energy storage converter, the battery terminal voltage and battery current are synchronously sampled. From the sampled battery terminal voltage and battery current data, the voltage frequency domain response component and the current frequency domain response component corresponding to the current target frequency are extracted. Based on the ratio between the voltage frequency domain response component and the current frequency domain response component, the battery complex impedance corresponding to the current target frequency is determined. The process of determining the battery complex impedance is repeated for each target frequency. Each target frequency is correlated with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

[0021] Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, and tablets.

[0022] Server 102 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides cloud computing services.

[0023] The grid-type energy storage converter referred to in this embodiment is an energy storage power conversion device capable of actively controlling the AC output voltage based on its internally established voltage amplitude, angular frequency, and phase angle references. Unlike the grid-following converter, which relies on the external grid voltage phase for follow-up control, the grid-type energy storage converter can provide AC voltage support under grid-connected, weak grid, or islanded operation conditions, and maintain the AC operating state through active-frequency control, reactive-voltage control, virtual synchronous machine control, or combinations thereof.

[0024] In this embodiment, the battery impedance spectrum refers to a set of frequency-complex impedance data formed by determining the complex ratio between the battery voltage AC response phasors and the battery current AC response phasors at multiple target frequencies and organizing them in frequency order. This impedance spectrum can be represented by a Nyquist curve, or by impedance amplitude-frequency curves and impedance phase angle-frequency curves.

[0025] like Figure 2 As shown, this application provides a method for measuring battery impedance spectrum based on a grid-connected energy storage converter, which can be applied to... Figure 1 Taking terminal 101 or server 102 as an example, the explanation includes the following steps S1 to S4. Wherein: Step S1: Based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, determine multiple target frequencies for battery impedance identification, and generate corresponding small signal disturbance reference quantities based on the current target frequencies.

[0026] The measurement frequency band corresponding to the impedance spectrum of the battery under test refers to the frequency range from the lowest to the highest frequency to be covered in this measurement. This measurement frequency band can be determined based on the electrochemical process to be identified, the control bandwidth of the grid-type energy storage converter, the sampling frequency, and the allowable test duration.

[0027] The target frequency can be generated according to a preset frequency table. For example, multiple target frequencies can be formed by selecting frequency points at 1, 2, and 5 times the frequency band every ten octaves. The more target frequencies there are, the higher the impedance spectrum resolution, but the measurement time also increases accordingly. Therefore, different numbers of frequency points can be set according to different purposes such as rapid monitoring, fine diagnosis, or model parameter fitting. At the same time, a corresponding small-signal disturbance reference quantity is generated based on the current target frequency. This small-signal disturbance reference quantity is a disturbance quantity with a small amplitude relative to the nominal control quantity of the grid-type energy storage converter and the DC operating point of the battery.

[0028] Step S2: Obtain the nominal control reference quantities used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and superimpose the small signal disturbance reference quantities onto the nominal control reference quantities to obtain a unified control reference quantity.

[0029] The nominal control reference quantity refers to the control reference quantity generated by the grid-type energy storage converter to maintain its normal grid-connection function when impedance measurement is not performed. This nominal control reference quantity may include internal angular frequency reference quantity, phase angle reference quantity, AC side voltage amplitude reference quantity, and dq axis or three-phase voltage reference quantity formed by the above reference quantities.

[0030] The small-signal disturbance reference quantity does not replace the nominal control reference quantity, but is superimposed on the nominal control reference quantity as an auxiliary component to form a unified control reference quantity.

[0031] Step S3: Modulate and control the grid-type energy storage converter according to the unified control reference quantity, so that the small signal disturbance is transmitted to the battery side through the AC and DC power coupling of the grid-type energy storage converter. Then, synchronously sample the battery terminal voltage and battery current on the battery side, and extract the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency from the sampled battery terminal voltage data and battery current data.

[0032] The unified control reference quantity, after coordinate transformation, amplitude limiting, and modulation calculation, forms the pulse width modulation (PWM) signal corresponding to each power switching device in the grid-type energy storage converter. This PWM signal controls the on / off switching of the switching devices, introducing small-signal disturbances into the power fluctuations on the AC and DC sides. Due to the power coupling relationship between the AC and DC sides of the grid-type energy storage converter, small-signal disturbances on the AC side will be transmitted to the DC bus side, causing small-amplitude voltage and current fluctuations at the operating point of the battery under test. After synchronous sampling is completed, the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency can be extracted by discrete Fourier transform, eliminating interference from other frequency noise and DC components to ensure the accuracy of the extraction results.

[0033] Step S4: Determine the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component. Repeat the battery complex impedance determination process for each target frequency, and associate each target frequency with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

[0034] The voltage frequency domain response component is the complex phasor corresponding to the battery terminal voltage fluctuation at the current target frequency, and the current frequency domain response component is the complex phasor corresponding to the battery current fluctuation at the same target frequency. Dividing the voltage frequency domain response component by the current frequency domain response component yields the real and imaginary parts of the battery complex impedance at that frequency, completing the impedance calculation at a single frequency point. The above disturbance injection, response sampling component extraction, and impedance calculation processes are sequentially performed for all preset target frequencies to obtain the complex impedance result corresponding to each target frequency. After organizing all frequencies and their corresponding complex impedances in frequency order, a complete online impedance spectrum of the battery can be obtained. No additional dedicated impedance measurement hardware is required; the measurement can be completed using the existing control path and sampling loop of the grid-connected energy storage converter, enabling online impedance measurement during battery operation.

[0035] It should be noted that this application first determines multiple target frequencies based on the measurement frequency band of the impedance spectrum to be measured, and generates a small-signal disturbance reference quantity for the current target frequency. Then, this disturbance reference quantity is superimposed with the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency, and phase, so that the impedance measurement excitation is embedded in the grid control process. Subsequently, the disturbance is transmitted to the battery side using the AC / DC power coupling of the converter, and the battery terminal voltage and battery current are sampled synchronously. The voltage and current frequency domain response components corresponding to the target frequencies are extracted, and then the battery complex impedance at each target frequency is calculated and the online impedance spectrum is reconstructed. Thus, since the small-signal disturbance and the nominal control reference quantity used to maintain grid operation are uniformly incorporated into the control command, rather than being applied separately from the grid control, the impact of impedance measurement disturbance on AC side voltage support, frequency maintenance, and power regulation can be reduced. This improves the problem of inconsistency between traditional online impedance measurement methods and grid control objectives, and provides a continuous and timely impedance spectrum data basis for energy storage battery operating status monitoring and health assessment.

[0036] In some embodiments, based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, multiple target frequencies for battery impedance identification are determined, and a corresponding small-signal perturbation reference quantity is generated based on the current target frequency. This includes: determining the start frequency and end frequency of the measurement frequency band based on the electrochemical process to be covered by the impedance spectrum of the battery under test; determining the number of target frequencies and the frequency interval method based on the purpose of impedance spectrum measurement, and generating a target frequency set consisting of multiple target frequencies between the start frequency and the end frequency; determining the perturbation injection order, angular frequency, perturbation amplitude, and perturbation phase of each target frequency based on the target frequency set; determining the current target frequency from the target frequency set according to the perturbation injection order, and generating a small-signal perturbation reference quantity based on the target angular frequency, target perturbation amplitude, and target perturbation phase corresponding to the current target frequency.

[0037] Battery impedance spectra can typically be divided into ultra-high frequency (UHF) or high frequency regions, mid-high frequency interface film regions, mid-frequency charge transfer regions, and low-frequency diffusion regions. Different frequency bands reflect different internal battery processes. For example, the real intercept at the high-frequency end is mainly related to the ohmic internal resistance formed by the electrolyte, electrodes, current collectors, and connecting components; the imaginary part of the UHF impedance can reflect the inductive effects generated by the connecting lines, battery tabs, and measurement circuits; the mid-high frequency arc can reflect processes related to the solid electrolyte interface film; the mid-frequency arc can reflect the charge transfer process at the electrode-electrolyte interface; and the low-frequency oblique line or tail trend can reflect lithium-ion diffusion and concentration polarization processes.

[0038] Therefore, based on the electrochemical process to be covered by the battery impedance spectrum, the starting frequency f is determined. min and the termination frequency f maxThe number of frequency points N and the frequency spacing method are determined according to the diagnostic purpose; when performing rapid state monitoring, at least one representative frequency point is selected from the high-frequency ohmic region, the mid-frequency charge transfer region, and the low-frequency diffusion region; when performing complete impedance spectrum reconstruction, at f min to f max Generate a target frequency set by using logarithmic intervals or a preset frequency table. This is then converted into a target angular frequency set Ω = ω1, ω2, ..., ω N ,in The perturbation injection sequence, single-frequency injection duration, steady-state sampling window length, perturbation amplitude, and perturbation phase corresponding to each frequency point are generated based on the target frequency set.

[0039] The perturbation injection sequence can be executed in descending order of the target frequency, ascending order of the target frequency, or any pre-set order. To reduce the impact of low-frequency measurement time on changes in battery operating state, high-frequency and mid-frequency measurements can be performed first, followed by a longer-duration low-frequency measurement. The steady-state sampling window length can be determined according to the integer number of cycles of the target frequency. ,in, The number of cycles at the target frequency. For the first Target frequency. Disturbance amplitude A k It can be set separately for different frequencies. This is because the inverter control channel, battery impedance, and measurement noise all vary with frequency. If the same amplitude is used for all frequencies, it may cause some frequencies to have an insufficiently weak response, while other frequencies may cause excessive AC side disturbances.

[0040] The small-signal disturbance reference quantity can be a voltage disturbance reference quantity, or it can be converted into an auxiliary disturbance reference quantity for current, power, or other internal control variables depending on the control architecture. In this embodiment, it is preferred to set it as the disturbance voltage quantity in the internal voltage reference channel so as not to change the main control objective of the network control. The current target frequency is determined from the target frequency set according to the disturbance injection order, and the target angular frequency, target disturbance amplitude, and target disturbance phase corresponding to the current target frequency are determined. Then, the small-signal disturbance reference quantity is generated as follows: ; in, This is the small-signal perturbation reference value corresponding to the kth target frequency; This represents the perturbation phase of the k-th target.

[0041] In some embodiments, the nominal control reference quantities used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency, and phase under the current operating state are obtained, and the small-signal disturbance reference quantities are superimposed on the nominal control reference quantities to obtain a unified control reference quantity. This includes: obtaining the active power reference value, reactive power reference value, measured active power, and measured reactive power of the grid-type energy storage converter; determining the internal angular frequency, phase angle, and fundamental voltage reference quantities of the grid-type energy storage converter based on the active power reference value, reactive power reference value, measured active power, and measured reactive power, combined with the grid control parameters; generating the nominal control reference quantity based on the internal angular frequency, phase angle, and fundamental voltage reference quantities; and superimposing the small-signal disturbance reference quantities on the nominal control reference quantity according to a preset disturbance injection channel to obtain a unified control reference quantity.

[0042] The small-signal disturbance reference quantity does not replace the nominal control reference quantity, but is superimposed on the nominal control reference quantity as an auxiliary component. Specifically, the nominal control reference quantity used to maintain the AC side voltage amplitude, frequency, and phase is generated based on the active power reference value, reactive power reference value, measured active power, and measured reactive power, combined with the droop coefficient and virtual inertia parameter in the grid control parameters. Generally, based on the active power reference value, reactive power reference value, measured active power, and measured reactive power, combined with the grid control parameters, the internal angular frequency, phase angle, and fundamental voltage reference values ​​of the grid-type energy storage converter are determined, specifically as follows:

[0043] in, This represents the angular frequency of the converter's output voltage. Indicates the rated angular frequency; Indicates the active-frequency droop factor; This indicates the actual output active power; This represents the reference value for active power. Indicates the output voltage amplitude of the converter; Indicates the rated voltage amplitude; This represents the reactive power-voltage droop coefficient; This indicates the actual output reactive power; This indicates the reference value for reactive power.

[0044] The d-axis and q-axis voltage reference commands are generated by using the internal angular frequency, phase angle, and fundamental voltage reference of the grid-type energy storage converter. After coordinate transformation, the nominal voltage control reference in the three-phase stationary coordinate system is obtained, which serves as the basic control command for the grid-type converter to maintain steady-state operation on the AC side, i.e., the nominal control reference. Subsequently, small signal disturbances are superimposed on the nominal control reference according to the preset channel, and finally a unified control reference for modulation is formed.

[0045] The disturbance injection channel can be a d-axis voltage reference channel, a q-axis voltage reference channel, or a combined dq-axis voltage reference channel. Then, the unified dq-axis voltage reference quantity is converted into a three-phase voltage reference quantity through an inverse Park transform, and then fed into the pulse width modulation stage. Thus, depending on the injection channel, the disturbance injection can be... Configured as Axis disturbance , Axis disturbance The shaft combination disturbance is then superimposed on the nominal control reference at the voltage reference synthesis node to obtain a unified control reference: .

[0046] In some embodiments, the grid-type energy storage converter is modulated and controlled according to a unified control reference quantity. After a small-signal disturbance is transmitted to the battery side via AC / DC power coupling of the grid-type energy storage converter, the battery terminal voltage and battery current on the battery side are synchronously sampled, and the voltage frequency domain response component and the current frequency domain response component are extracted. This includes: generating a modulation signal for controlling the power switching devices in the grid-type energy storage converter according to the unified control reference quantity; using the modulation signal to control the grid-type energy storage converter to perform AC / DC power conversion, so that the AC side generates a power oscillation component corresponding to the current target frequency, and transmitting the power oscillation component to the battery side through AC / DC power coupling; obtaining the injection start time and the current target frequency of the small-signal disturbance reference quantity, and synchronously sampling the battery terminal voltage and battery current; determining a steady-state data window from the sampled battery terminal voltage data and battery current data according to the injection start time, and extracting the voltage frequency domain response component and the current frequency domain response component corresponding to the current target frequency from the steady-state data window.

[0047] Among them, small-signal disturbances are injected into the voltage synthesis stage or dq-axis voltage reference channel of the grid-type energy storage converter, and satisfy the following conditions: ,in The fundamental voltage component generated by the grid control. The disturbance voltage component is used for impedance identification so that impedance measurement is embedded as an auxiliary voltage channel into the main control architecture.

[0048] After disturbance injection, the small-signal disturbance causes an oscillating component related to the current target frequency in the AC-side voltage, current, or instantaneous power. The disturbance power component on the AC side can be transferred to the DC side via the converter, causing a target frequency response in the battery terminal voltage and current. That is, the oscillating power component is transferred to the DC side via AC / DC energy coupling and excites the battery, causing an AC response component at the target frequency to appear in the battery-side voltage and current; wherein, the AC / DC sides satisfy… .

[0049] Record the injection start time t when the small signal disturbance begins to be injected. 0,k Current target frequency f k Target angular frequency ω k and perturbation phase The above information can serve as a time reference for subsequent transient rejection, steady-state window positioning, and synchronous demodulation. When a small-signal disturbance is first injected, the dynamics of the network control loop, AC filter, DC bus, and battery have not yet entered a periodic steady state, and the sampled data at this time includes the startup transient. If this part of the data is directly used for frequency domain calculation, it will lead to spectral leakage outside the target frequency and reduce the accuracy of impedance estimation.

[0050] Therefore, it is necessary to automatically determine whether a steady state has been reached based on the periodic stability of the voltage and current response amplitudes. The steady-state data window should simultaneously apply to both battery terminal voltage and battery current data, using the same start and end times. This ensures that the subsequently obtained voltage and current frequency domain response components have consistent time and phase references. Specifically, the steady-state data window is determined from the sampled battery terminal voltage and battery current data based on the injection start time.

[0051] Furthermore, a steady-state data window is determined from the sampled battery terminal voltage data and battery current data, including: removing transient data after the injection starts from the battery terminal voltage data and battery current data based on the injection start time; and selecting data containing a preset number of complete cycles of the current target frequency after the transient data to form a steady-state data window.

[0052] Where the sampling frequency allows, it is preferable to make the number of sampling points at the current target frequency and the number of sampling points corresponding to the target period an integer relationship, so as to reduce the spectrum leakage caused by truncation.

[0053] Subsequently, the voltage frequency domain response component and the current frequency domain response component corresponding to the current target frequency are extracted from the steady-state data window.

[0054] Specifically, for the target frequency set The first in Target frequency Generate the corresponding angular frequency The small signal is disturbed and injected; the battery voltage is simultaneously acquired on the battery side. and battery current Based on the injection start time Remove the transient segment and select a segment of length from the steady-state segment. The data window, in which The target frequency is the number of cycles; the data window is averaged to remove the DC component, yielding the AC response voltage. and AC response current Fourier transform, orthogonal demodulation, or sine fitting methods are used in... Extracting voltage frequency domain response components and current frequency domain response components .

[0055] Generally, the average battery terminal voltage and average battery current in the steady-state data window are calculated separately. Subtracting the corresponding average value from each sampled value yields the AC response voltage and AC response current data. The averaging process removes the battery's DC operating voltage and DC charging / discharging current, ensuring that subsequent frequency domain analysis focuses primarily on the AC response caused by small-signal disturbances. When using Fourier transform, the AC response voltage and current data can be weighted using the same window function before extracting the complex frequency domain component of the current target frequency.

[0056] When using synchronous quadrature demodulation, the AC response data can be multiplied by the sinusoidal and cosine reference signals corresponding to the target frequency and then averaged within a window. This constructs the complex frequency domain response components for voltage and current. When using sinusoidal fitting, the AC response voltage and AC response current can be fitted separately, and the corresponding complex frequency domain response components can be constructed based on the fitting coefficients.

[0057] In some embodiments, the battery complex impedance corresponding to the current target frequency is determined based on the ratio between the voltage frequency domain response component and the current frequency domain response component. The process of determining the battery complex impedance is repeated for each target frequency, and each target frequency is associated with its corresponding battery complex impedance to obtain the battery online impedance spectrum. This includes: calculating the battery complex impedance corresponding to the current target frequency based on the complex ratio between the voltage frequency domain response component and the current frequency domain response component; associating and storing the current target frequency with its corresponding battery complex impedance to form a current frequency-complex impedance data pair; sequentially using each target frequency as the current target frequency according to the perturbation injection order corresponding to the target frequency set, and repeating the battery complex impedance calculation process for each current target frequency to obtain the frequency-complex impedance data pair corresponding to each target frequency; and arranging each frequency-complex impedance data pair according to the frequency order of the target frequency set to obtain the battery online impedance spectrum.

[0058] The complex impedance of the battery is calculated using the following formula:

[0059] in, and Target angular frequency The frequency domain response components of the battery-side voltage and current; Decompose into real part virtual part Amplitude and phase angle and the corresponding target frequency Jointly preserved; After repeating the above process, a complete online impedance spectrum dataset is obtained. The target frequency set is used to control the perturbation injection frequency point by point, determine the number of sampling window periods point by point, specify the frequency extraction frequency point by point, and serve as the frequency index for the impedance spectrum abscissa and state-sensitive feature extraction.

[0060] For example, for each target frequency in the target frequency set, the following complete process should be repeated: generate a corresponding small-signal disturbance reference quantity based on the target frequency; superimpose the small-signal disturbance reference quantity onto the nominal control reference quantity; perform modulation control based on the unified control reference quantity; wait for the current target frequency response to enter a steady state; synchronously acquire the battery terminal voltage and battery current; extract the voltage and current frequency domain response components corresponding to the current target frequency; calculate the complex impedance corresponding to the current target frequency; and perform validity judgment and save the current frequency-complex impedance data pair. After completing the current frequency, a preset switching interval can be set to attenuate the residual response of the previous frequency before switching to the next target frequency, thereby reducing the mutual influence between different target frequencies.

[0061] Subsequently, all effective frequency-complex impedance data pairs are arranged in a uniform order from low to high or from high to low according to the target frequency to form an online impedance spectrum dataset. The Nyquist curve can be plotted with the real part of the complex impedance as the x-axis and the negative value of the imaginary part of the complex impedance as the y-axis.

[0062] By plotting the logarithm of the target frequency on the x-axis and the impedance amplitude on the y-axis, a Bode amplitude-frequency curve can be drawn; by plotting the logarithm of the target frequency on the x-axis and the impedance phase angle on the y-axis, a Bode phase-frequency curve can be drawn.

[0063] The target frequency set is not only used to generate disturbances, but also serves as a unified frequency index for determining the steady-state window length, extracting the frequency domain response, calculating complex impedance, plotting curves, and extracting state features, thereby enabling a one-to-one correspondence between the data at each stage.

[0064] In some embodiments, after obtaining the battery's online impedance spectrum, the method further includes: dividing the battery's online impedance spectrum into high-frequency, mid-frequency, and low-frequency regions according to the impedance spectrum frequency band to which each target frequency belongs; extracting high-frequency ohmic resistance and inductance characteristics from the high-frequency impedance data; extracting interface film characteristics, charge transfer characteristics, and Nyquist curve arc geometric characteristics from the high-frequency and mid-frequency impedance data; extracting diffusion impedance characteristics and low-frequency polarization trends from the low-frequency impedance data; combining the extracted features into a battery state feature vector according to a preset feature order; obtaining reference feature values ​​that correspond one-to-one with each feature in the battery state feature vector; combining the reference feature values ​​into a reference feature vector according to a preset feature order; normalizing the battery state feature vector and the reference feature vector; and determining the feature offset of the battery state feature vector relative to the reference feature vector; and determining the battery state evaluation result based on the feature offset.

[0065] Specifically, after obtaining the battery's online impedance spectrum, battery status diagnosis is completed. Preferably, based on the frequency band to which each frequency point belongs in the target frequency set, the high-frequency impedance is used to extract ohmic internal resistance and high-frequency inductance characteristics, the mid-frequency impedance is used to extract SEI film impedance, charge transfer impedance, and Nyquist arc geometric characteristics, and the low-frequency impedance is used to extract diffusion impedance, polarization trend, and low-frequency slope. The extracted state-sensitive features are combined into a feature vector and compared with a reference baseline or historical feature vector. The battery status diagnosis result is output based on the feature offset.

[0066] Among them, the state-sensitive characteristics include at least the high-frequency ohmic internal resistance. Inductive component SEI film resistance SEI film constant phase element Double-layer constant phase element Charge transfer resistance Warburg diffusion impedance or One or more of the following can be achieved: the real and imaginary parts of impedance at characteristic frequencies, impedance amplitude, phase angle, geometric parameters of the Nyquist curve arc, and polarization or diffusion trends in the low-frequency region. High-frequency ohmic internal resistance The frequency point is determined by selecting a frequency point in the high-frequency ohmic region of the target frequency set or by the intercept of the high-frequency end of the Nyquist curve with the real axis; when multiple high-frequency points exist, the high-frequency band is... By averaging, linear extrapolation, or equivalent circuit fitting, we can obtain... ; Inductive component The impedance in the ultra-high frequency band within the target frequency set is determined by the variation of the imaginary part with angular frequency. Or for the ultra-high frequency band - The curve was obtained by fitting its slope. SEI film resistance and SEI film constant phase element It can be obtained by fitting an equivalent circuit through the impedance point of the corresponding frequency band of the high-frequency arc, or estimated based on the difference in the real intercepts at both ends of the high-frequency arc. And determine based on the peak frequency and shape of the arc. The amplitude coefficient and the exponential coefficient; Double-layer constant phase element and charge transfer resistance The equivalent circuit can be obtained by fitting the impedance points of the corresponding frequency band of the intermediate frequency arc, or estimated based on the difference in the real intercepts at both ends of the intermediate frequency arc. And determine based on the mid-frequency arc peak frequency, phase angle peak frequency, and arc flattening degree. parameter; Warburg diffusion impedance or The impedance point is determined by selecting impedance points in the low-frequency range within the target frequency set, and then calculating the low-frequency Nyquist tail slope, the low-frequency impedance amplitude growth rate, or... and The slope of the linear fit between the two values ​​is used to characterize the degree of diffusion restriction; The real and imaginary parts of the impedance at the characteristic frequency pass through a preset characteristic frequency. Read or interpolate at the location and Achieve; when When the frequency is not in the target frequency set, linear interpolation, logarithmic frequency interpolation, or local fitting estimation is performed based on the complex impedance of adjacent frequency points. Impedance magnitude and phase angle are respectively based on and Calculate and select the amplitude and phase angle of a single characteristic frequency point or the statistical measure of the amplitude and phase angle within a certain frequency band; The geometric parameters of the Nyquist curve circular arc are obtained by performing circle fitting or ellipse fitting on the impedance points of the high-frequency or mid-frequency circular arc. The geometric parameters include the arc diameter, radius, center coordinates, imaginary part of the peak, real intercepts at both ends of the arc, and degree of arc flattening. The polarization or diffusion trend in the low-frequency region is determined by the growth rate of the impedance amplitude in the low-frequency band as the frequency decreases, the change in the low-frequency phase angle, the slope of the Nyquist low-frequency tail, or the diffusion parameters obtained by fitting the low-frequency band.

[0067] Among them, the reference feature values ​​corresponding to each feature in the battery state feature vector are generally obtained by calibrating the battery at the time of leaving the factory to obtain the initial feature values ​​of a brand new battery and using them as reference feature values; the average feature values ​​can also be extracted from the online impedance spectrum of healthy batteries of the same model as reference feature values; or feature values ​​extracted from the battery in its historical healthy state can be selected as reference feature values.

[0068] Specifically, the feature vector extracted from the online impedance spectrum is normalized and compared with the reference baseline. Based on the feature offset, the battery state assessment result is output using any one of the following methods: threshold determination, weighted fusion, regression mapping, or a data-driven model. In particular, an online feature vector is constructed. The online feature vector is derived from the high-frequency ohmic internal resistance extracted above. SEI membrane related parameters and Charge transfer related parameters and diffusion-related parameters or The characteristics include one or more of the following: the real and imaginary parts of the impedance at the characteristic frequency, the impedance magnitude, the phase angle, the geometric parameters of the circular arc of the Nyquist curve, and the low-frequency diffusion slope. Establish reference baseline The reference baseline is determined by offline EIS results, historical online measurement results, or calibration databases for new batteries, healthy batteries, rated SOC, and rated temperature conditions. The online feature vectors are normalized to obtain the feature offsets: ; Or obtain standardized features: ; in, and These are the mean and standard deviation of the reference sample, respectively. When using a threshold-based determination method, the offset of each state-sensitive feature is compared with a preset threshold. If... If the internal resistance exceeds the ohmic resistance threshold, the conductive path, connection status, temperature, or aging condition is considered abnormal; if If the charge transfer threshold is exceeded, the electrode interface reaction kinetics are considered to have deteriorated; if the low-frequency diffusion slope or If the offset exceeds the diffusion threshold, it is determined that the diffusion polarization is enhanced; if multiple features exceed the threshold at the same time, the output status is normal, warning or fault according to the abnormality level. When using a weighted fusion method, weights are assigned to each feature offset. And calculate the comprehensive state index: ; in, The sensitivity of the characteristics to SOC, SOH, temperature, aging, or abnormal conditions is determined; then, a comprehensive state index is used. Compared with the grading threshold, the system outputs the battery health level, abnormality level, or maintenance recommendations. When using regression mapping, the online feature vectors or normalized features Input a pre-calibrated linear regression, multinomial regression, partial least squares regression, support vector regression, or other regression model, and output the battery state variables: ; in, It is at least one of SOC, SOH, internal resistance growth rate, capacity decay rate, or health indicators. The mapping function is obtained by training or fitting from the calibration samples; When using a data-driven model approach, online impedance spectrum data or feature vectors are input into a classification model, clustering model, neural network model, random forest model, or time series prediction model, and the output is the battery state category, health score, or anomaly probability. The data-driven model can be trained using historical online impedance spectra, offline EIS calibration data, SOC labels, SOH labels, temperature labels, or fault labels. Finally, a battery status assessment result is generated based on the threshold determination result, weighted fusion index, regression mapping result, or data-driven model output result. The battery status assessment result includes at least one of the following: normal, warning, abnormal, aging aggravated, diffusion restricted, interface reaction hindered, internal resistance increased, SOC difference, or SOH decrease.

[0069] The method proposed in this application completes online impedance spectrum measurement without additional configuration of a dedicated impedance analyzer and without interrupting the normal operation of the energy storage system, while maintaining the AC side voltage support and power regulation functions of the grid-type energy storage converter during the measurement process.

[0070] To verify the online impedance spectroscopy measurement process of the method proposed in this application, the following calculation example is provided.

[0071] This example focuses on a grid-based energy storage inverter system. Functionally, the system can be divided into two layers: the first layer is the grid control layer, which maintains the normal operation of the energy storage inverter and provides AC side voltage support; the second layer is the online impedance spectrum measurement layer, which uses small-signal perturbations in the control loop to achieve battery excitation, response acquisition, and impedance spectrum reconstruction. Through the collaboration of these two layers, online battery status sensing can be completed during grid operation.

[0072] During implementation, firstly combine Figure 3 and Figure 4 Determine the target frequency point or target frequency set. Figure 3 Typical morphologies of the high-frequency ohmic region, mid-to-high-frequency interface film region, mid-frequency charge transfer region, and low-frequency diffusion region in the Nyquist impedance spectrum are presented. Figure 4 The above frequency band and equivalent circuit parameters are further given. , , , , , and or The correspondence between them. Therefore, when the goal is rapid online monitoring, it is possible to... Figure 3 and Figure 4 Representative frequencies are selected from the corresponding key frequency bands; when the goal is fine characterization, a target frequency set can be generated using a logarithmic distribution within the range of 1 Hz to 10 kHz or other defined frequency bands. To cover major electrochemical processes such as ohms, interfaces, charge transfer, and diffusion.

[0073] Subsequently combined Figure 5 A small sinusoidal disturbance is superimposed on the internal voltage reference channel or voltage synthesis stage of the grid-type energy storage converter. The grid control layer uses the power calculation module to obtain... , and after low-pass filtering , , combined , , Sag coefficient , Virtual inertial parameters and damping coefficient Generating internal angular frequencies Phase angle and fundamental voltage reference; online impedance spectrum measurement layer based on the current target frequency. generate Figure 5 In and and superimpose it onto Axis voltage reference. The disturbance amplitude is determined based on the battery-side response signal-to-noise ratio and AC-side voltage quality constraints, ensuring that it generates a identifiable response on the battery side without compromising the stability of the grid operation.

[0074] After perturbation injection, combined Figure 6 The control reference containing disturbances is applied to the three-phase bridge arm via PWM. , , This causes the three-phase current on the AC side to... , , In load or line equivalent parameters , Under this influence, corresponding oscillation components are generated. Based on AC / DC power coupling, the disturbance power fluctuation is transmitted to the DC side and excites the battery, causing... Figure 6 Battery terminal current and battery terminal voltage An AC response component corresponding to the target frequency appears. The system synchronously samples the battery-side signal and extracts the frequency domain components of the battery terminal voltage and current at the target frequency through injection start-time detection, steady-state data segmentation, DC removal processing, and Fourier transform or synchronous demodulation.

[0075] After calculating the complex impedance at each target frequency, the online impedance spectrum of the battery can be reconstructed. The real and imaginary parts of the complex impedance are used to generate... Figure 7 The Nyquist plot shown uses impedance magnitude and phase angle to generate... Figures 8a-8b The Bode plot is shown. Furthermore, the high-frequency ohmic resistance can be extracted from this online impedance spectrum. SEI film impedance Charge transfer impedance Characteristic quantities include the real and imaginary parts of impedance at characteristic frequencies, impedance amplitude, phase angle, Nyquist arc diameter, and low-frequency diffusion slope. These characteristics are compared with a baseline characteristic under reference operating conditions, and battery state assessment results can be output using thresholding, weighted fusion, regression models, or data-driven models.

[0076] In one embodiment, the method proposed in this application performs online impedance measurement in the frequency band from 1 Hz to 10 kHz and compares the measured results with offline impedance spectrum results. Figure 7 The Nyquist trajectory is plotted from the real and imaginary parts of the complex impedance at each frequency point and used to compare the consistency between online and offline measurements. Figures 8a-8b The impedance amplitude and phase angle are calculated from the same set of complex impedance data and then plotted to compare the consistency of amplitude-frequency and phase-frequency responses between online and offline measurements. The effectiveness of the online impedance measurement method of this invention can be verified when the online and offline results are substantially consistent in terms of high-frequency intercept, mid-frequency arc, and low-frequency diffusion trend. In another embodiment, online identification is performed under conditions of 100% and 80% battery state of charge, respectively. The results show that as the SOC decreases, the real axis intercept, arc diameter, or low-frequency diffusion trend of the Nyquist curve undergoes identifiable changes, which can be used to reflect differences in battery state.

[0077] Based on the same inventive concept, this application also provides a battery impedance spectrum measurement system for implementing the battery impedance spectrum measurement method based on grid-connected energy storage converter mentioned above.

[0078] The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more battery impedance spectrum measurement system embodiments based on grid-connected energy storage converters provided below can be found in the limitations of the battery impedance spectrum measurement method based on grid-connected energy storage converters described above, and will not be repeated here.

[0079] like Figure 9 As shown in the figure, this application provides a battery impedance spectrum measurement system based on a grid-connected energy storage converter. The system includes: The disturbance reference determination module 100 is used to determine multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and to generate corresponding small signal disturbance reference quantities based on the current target frequencies. The control reference determination module 200 is used to obtain the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and to superimpose the small signal disturbance reference quantity onto the nominal control reference quantity to obtain a unified control reference quantity. The response component determination module 300 is used to modulate and control the grid-type energy storage converter according to the unified control reference quantity, so that after the small signal disturbance is transmitted to the battery side through the AC and DC power coupling of the grid-type energy storage converter, the battery terminal voltage and battery current on the battery side are synchronously sampled, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the sampled battery terminal voltage data and battery current data. The impedance spectrum determination module 400 is used to determine the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component, and to repeatedly perform the battery complex impedance determination process for each target frequency, thereby associating each target frequency with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

[0080] In some embodiments, the disturbance reference determination module 100 is configured to: Based on the electrochemical process to be covered by the impedance spectrum of the battery under test, determine the start and end frequencies of the measurement frequency band. The number of target frequencies and frequency spacing are determined according to the purpose of impedance spectrum measurement, and a target frequency set consisting of multiple target frequencies is generated between the starting frequency and the ending frequency. The perturbation injection sequence, angular frequency, perturbation amplitude, and perturbation phase for each target frequency are determined based on the target frequency set. The current target frequency is determined from the target frequency set according to the perturbation injection order, and a small-signal perturbation reference quantity is generated based on the target angular frequency, target perturbation amplitude, and target perturbation phase corresponding to the current target frequency.

[0081] In some embodiments, the control reference determination module 200 is configured to: Obtain the active power reference value, reactive power reference value, measured active power and measured reactive power of the grid-type energy storage converter; Based on the active power reference value, reactive power reference value, measured active power and measured reactive power, and combined with the grid control parameters, determine the internal angular frequency, phase angle and fundamental voltage reference value of the grid-type energy storage converter. The nominal control reference value is generated based on the internal angular frequency, phase angle, and fundamental voltage reference value. Based on the preset disturbance injection channel, the small signal disturbance reference quantity is superimposed on the nominal control reference quantity to obtain a unified control reference quantity.

[0082] In some embodiments, the response component determination module 300 is configured to: A modulation signal is generated based on a unified control reference quantity to control the power switching devices in the grid-type energy storage converter; The grid-type energy storage converter is controlled by a modulation signal to perform AC-DC power conversion, so that the AC side generates a power oscillation component corresponding to the current target frequency, and the power oscillation component is transmitted to the battery side through AC-DC power coupling; The injection start time and current target frequency of the small signal disturbance reference quantity are obtained, and the battery terminal voltage and battery current are sampled synchronously. Based on the injection start time, a steady-state data window is determined from the sampled battery terminal voltage data and battery current data, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the steady-state data window.

[0083] In some embodiments, the response component determination module 300 is configured to: Based on the injection start time, the transient data after the injection start time is removed from the battery terminal voltage data and battery current data after the small signal disturbance reference quantity is removed; After the transient data, select a preset number of complete cycles of data containing the current target frequency to form a steady-state data window.

[0084] In some embodiments, the impedance spectrum determination module 400 is used for: Calculate the complex impedance of the battery at the current target frequency based on the complex ratio between the voltage frequency domain response component and the current frequency domain response component at the current target frequency. The current target frequency is associated with the corresponding battery complex impedance and stored to form a current frequency-complex impedance data pair. According to the perturbation injection order corresponding to the target frequency set, each target frequency is taken as the current target frequency in turn, and the battery complex impedance calculation process is repeated for each current target frequency to obtain the frequency-complex impedance data pair corresponding to each target frequency. Arrange the frequency-complex impedance data pairs according to the frequency order of the target frequency set to obtain the online impedance spectrum of the battery.

[0085] In some embodiments, the system further includes a status assessment module, used for: Based on the impedance spectrum bands to which each target frequency belongs, the online impedance spectrum of the battery is divided into high-frequency region, mid-frequency region and low-frequency region; High-frequency ohmic resistance and inductance features are extracted from high-frequency impedance data. Interface film features, charge transfer features and Nyquist curve arc geometry features are extracted from high-frequency and mid-frequency impedance data. Diffusion impedance features and low-frequency polarization trends are extracted from low-frequency impedance data. The extracted features are combined into a battery state feature vector according to a preset feature order. Obtain reference feature values ​​that correspond one-to-one with each feature in the battery state feature vector, and combine the reference feature values ​​into a reference feature vector according to a preset feature order; The battery state feature vector and the reference feature vector are normalized, and the feature offset of the battery state feature vector relative to the reference feature vector is determined. The battery state assessment result is determined based on the feature offset.

[0086] like Figure 10 As shown, this application provides an electronic device. The electronic device 10 includes a memory 20 and a processor 30. The memory 20 stores a computer program. When the computer program is executed by the processor 30, the processor 30 performs the steps of the battery impedance spectrum measurement method based on the grid-connected energy storage converter as described in the above embodiment.

[0087] This application provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed, it implements the steps of the battery impedance spectrum measurement method based on a grid-connected energy storage converter as described in the above embodiments.

[0088] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, electronic devices, and computer storage media described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0089] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0090] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0091] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0092] In the embodiments provided by this invention, it should be understood that the disclosed systems, electronic devices, computer storage media, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0093] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0095] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods described in the various embodiments of the present invention through a computer device (which may be a personal computer, a server, or a network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0096] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for measuring battery impedance spectrum based on a grid-connected energy storage converter, characterized in that, The method includes: Based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, multiple target frequencies for battery impedance identification are determined, and corresponding small signal perturbation reference quantities are generated based on the current target frequency. Obtain the nominal control reference value used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and superimpose the small signal disturbance reference value onto the nominal control reference value to obtain a unified control reference value; The grid-type energy storage converter is modulated and controlled according to the unified control reference quantity. After the small signal disturbance is transmitted to the battery side through the AC / DC power coupling of the grid-type energy storage converter, the battery terminal voltage and battery current on the battery side are synchronously sampled. The voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the sampled battery terminal voltage data and battery current data. Based on the ratio between the voltage frequency domain response component and the current frequency domain response component, the battery complex impedance corresponding to the current target frequency is determined, and the battery complex impedance determination process is repeated for each target frequency. Each target frequency is associated with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

2. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 1, characterized in that, The step of determining multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and generating corresponding small-signal perturbation reference quantities based on the current target frequencies, includes: Based on the electrochemical process to be covered by the impedance spectrum of the battery under test, determine the start and end frequencies of the measurement frequency band; The number of target frequencies and the frequency interval method are determined according to the purpose of impedance spectrum measurement, and a target frequency set consisting of the multiple target frequencies is generated between the starting frequency and the ending frequency. The perturbation injection sequence, angular frequency, perturbation amplitude, and perturbation phase of each target frequency are determined based on the target frequency set. The current target frequency is determined from the target frequency set according to the perturbation injection order, and the small signal perturbation reference quantity is generated based on the target angular frequency, target perturbation amplitude, and target perturbation phase corresponding to the current target frequency.

3. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 1, characterized in that, The acquisition of the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency, and phase under the current operating state, and the superposition of the small-signal disturbance reference quantity to the nominal control reference quantity to obtain a unified control reference quantity, includes: Obtain the active power reference value, reactive power reference value, measured active power, and measured reactive power of the grid-type energy storage converter; Based on the active power reference value, the reactive power reference value, the measured active power and the measured reactive power, and in conjunction with the grid control parameters, the internal angular frequency, phase angle and fundamental voltage reference of the grid-type energy storage converter are determined. The nominal control reference value is generated based on the internal angular frequency, the phase angle, and the fundamental voltage reference value. According to the preset disturbance injection channel, the small signal disturbance reference quantity is superimposed on the nominal control reference quantity to obtain the unified control reference quantity.

4. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 1, characterized in that, The process involves modulating and controlling the grid-type energy storage converter according to the unified control reference value, so that the small-signal disturbance is transmitted to the battery side via AC / DC power coupling of the grid-type energy storage converter. Then, the battery terminal voltage and battery current on the battery side are synchronously sampled, and the voltage frequency domain response component and the current frequency domain response component are extracted, including: Based on the unified control reference quantity, a modulation signal is generated for controlling the power switching devices in the grid-type energy storage converter; The modulation signal is used to control the grid-type energy storage converter to perform AC-DC power conversion, so that the AC side generates a power oscillation component corresponding to the current target frequency, and the power oscillation component is transmitted to the battery side through AC-DC power coupling; The injection start time of the small signal disturbance reference quantity and the current target frequency are obtained, and the battery terminal voltage and the battery current are sampled synchronously. Based on the injection start time, a steady-state data window is determined from the sampled battery terminal voltage data and battery current data, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the steady-state data window.

5. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 4, characterized in that, Determining a steady-state data window from the sampled battery terminal voltage data and battery current data includes: Based on the injection start time, the transient data after the injection of the small signal disturbance reference quantity is removed from the battery terminal voltage data and the battery current data; The steady-state data window is formed by selecting a preset number of complete cycles of data containing the current target frequency after the transient data.

6. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 1, characterized in that, The process of determining the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component, and repeating the battery complex impedance determination process for each target frequency to correlate each target frequency with the corresponding battery complex impedance, thereby obtaining the battery online impedance spectrum, includes: Calculate the battery complex impedance corresponding to the current target frequency based on the complex ratio between the voltage frequency domain response component and the current frequency domain response component corresponding to the current target frequency; The current target frequency is associated with and stored with the corresponding battery complex impedance to form a current frequency-complex impedance data pair; According to the perturbation injection order corresponding to the target frequency set, each target frequency is taken as the current target frequency in turn, and the battery complex impedance calculation process is repeated for each current target frequency to obtain the frequency-complex impedance data pair corresponding to each target frequency; The frequency-complex impedance data pairs are arranged according to the frequency order of the target frequency set to obtain the online impedance spectrum of the battery.

7. The battery impedance spectrum measurement method based on a grid-connected energy storage converter according to claim 1, characterized in that, After obtaining the online impedance spectrum of the battery, the process further includes: Based on the impedance spectrum bands to which each target frequency belongs, the online impedance spectrum of the battery is divided into high-frequency region, mid-frequency region and low-frequency region; High-frequency ohmic resistance and inductance features are extracted based on the high-frequency impedance data. Interface film features, charge transfer features and Nyquist curve arc geometry features are extracted based on the high-frequency impedance data and the mid-frequency impedance data. Diffusion impedance features and low-frequency polarization trends are extracted based on the low-frequency impedance data. The extracted features are combined into a battery state feature vector according to a preset feature order. Obtain reference feature values ​​that correspond one-to-one with each feature in the battery state feature vector, and combine the reference feature values ​​into a reference feature vector according to the preset feature order; The battery state feature vector and the reference feature vector are normalized, and the feature offset of the battery state feature vector relative to the reference feature vector is determined. The battery status assessment result is determined based on the feature offset.

8. A battery impedance spectrum measurement system based on a grid-connected energy storage converter, characterized in that, The system includes: The disturbance reference determination module is used to determine multiple target frequencies for battery impedance identification based on the measurement frequency band corresponding to the impedance spectrum of the battery under test, and to generate corresponding small signal disturbance reference quantities based on the current target frequencies. The control reference determination module is used to obtain the nominal control reference quantity used by the grid-type energy storage converter to maintain the AC side voltage amplitude, frequency and phase under the current operating state, and to superimpose the small signal disturbance reference quantity onto the nominal control reference quantity to obtain a unified control reference quantity. The response component determination module is used to modulate and control the grid-type energy storage converter according to the unified control reference quantity, so that the small signal disturbance is transmitted to the battery side through the AC / DC power coupling of the grid-type energy storage converter, and the battery terminal voltage and battery current on the battery side are synchronously sampled, and the voltage frequency domain response component and current frequency domain response component corresponding to the current target frequency are extracted from the sampled battery terminal voltage data and battery current data. The impedance spectrum determination module is used to determine the battery complex impedance corresponding to the current target frequency based on the ratio between the voltage frequency domain response component and the current frequency domain response component, and to repeatedly perform the battery complex impedance determination process for each target frequency, thereby associating each target frequency with the corresponding battery complex impedance to obtain the battery online impedance spectrum.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the processor performs the steps of the battery impedance spectrum measurement method based on a grid-connected energy storage converter as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the steps of the battery impedance spectrum measurement method based on a grid-connected energy storage converter as described in any one of claims 1-7.

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