33 results about "Ac impedance spectra" patented technology

The invention provides a pole piece testing method, electronic equipment and a computer readable storage medium. The method comprises the following steps: acquiring pole piece data of the battery and liquid phase conductivity of electrolyte; and performing alternating-current impedance test on the battery to obtain an alternating-current impedance spectrum of the battery. And fitting the alternating current impedance spectrum to obtain the ion impedance of the battery. And determining performance data of the pole piece according to the ion impedance, the pole piece data and the electrolyte liquid phase conductivity. And performing simulation test and experimental test on the pole piece according to the performance data to obtain simulation data and real data, comparing the simulation data with the real data, and when the difference value between the simulation data and the real data is within the error range, determining that the simulation precision meets the simulation standard. Whether the pole piece meets the design standard of the battery or not can be quickly judged, the design efficiency of the pole piece is improved, and the design robustness is enhanced.

The invention relates to the technical field of batteries, in particular to a battery charging and discharging control method and device, a battery and terminal equipment, and the method comprises the steps: obtaining an impedance real part; the impedance real part is obtained according to the alternating current impedance spectrum of the target battery under the preset excitation signal frequency; acquiring the current internal temperature of the target battery according to the impedance real part and a temperature calculation formula; querying a pre-stored maximum charge-discharge rate table according to the current charge state and the current internal temperature of the target battery to obtain a current maximum charge-discharge rate; and controlling the target battery to perform charging and discharging operation according to the current maximum charging and discharging rate. Therefore, the target battery is charged and discharged by using the accurate charge-discharge rate, battery abuse can be prevented, the service life of the battery is prolonged, and the safety of the battery is ensured.

The invention belongs to the technical field of energy storage batteries, and discloses an energy storage battery state evaluation method based on a generated impedance spectrum and a related device. The method comprises the following steps: acquiring impedance data of a to-be-evaluated energy storage battery; equivalent circuit fitting is carried out based on the impedance data of the energy storage battery to be evaluated, and equivalent element parameters are obtained; the correlation degree between the equivalent element parameters and the battery health state is calculated, and parameters with the correlation degree larger than a threshold value are selected as characteristic parameters; and inputting the characteristic parameters into a pre-established energy storage battery SOH evaluation model based on the generative impedance spectroscopy to obtain the health state of the energy storage battery to be evaluated. According to the invention, the test speed of the AC impedance spectroscopy and the interpretability of the evaluation model are considered; a full-spectrum alternating-current impedance spectrum is generated by using an adversarial neural network through a few points in different frequency ranges, so that the problems that full-spectrum testing time is long and engineering application is not facilitated are solved; and performing equivalent circuit analysis by using the generated full spectrum, and performing health state evaluation of the energy storage battery.

The embodiment of the invention discloses a high-frequency pulse self-heating method of a lithium ion battery and an electric vehicle, and the method comprises the steps: obtaining state parameters of the lithium ion battery, the state parameters comprising a first current temperature, a current charge state and a current health state of the lithium ion battery; judging whether the first current temperature is lower than a first temperature threshold value or not and whether the current charge state meets a pulse heating condition or not; when the first current temperature is lower than a first temperature threshold value and the current state of charge meets the pulse heating condition, the optimal pulse frequency and the optimal pulse current of pulse excitation are obtained based on the state parameters, the full-battery alternating-current impedance spectrum and the negative electrode pair reference alternating-current impedance spectrum; and performing internal pulse self-heating on the lithium ion battery by adopting a pulse excitation mode based on the optimal pulse frequency and the optimal pulse current. The scheme provided by the invention has the characteristics of high heating efficiency, uniform heating temperature distribution, low energy consumption and low influence on the electrical performance and service life of the battery, and can effectively avoid the risk of lithium precipitation of the negative electrode.

The invention relates to the technical field of fuel cell state evaluation, in particular to a fuel cell health state estimation method and system, and the method comprises the steps: continuously collecting the monomer polarization curve, pile AC impedance spectrum and gas flow channel pressure pulsation time sequence data of a target fuel cell in multiple operation cycles; ohm, activation and concentration polarization component decomposition are carried out on the polarization curve, a corresponding voltage loss component is extracted, correlation matching calculation is carried out on the corresponding voltage loss component and an impedance spectrum, and a polarization loss-impedance characteristic mapping relation is constructed. And extracting a pressure fluctuation mode synchronous with the polarization curve time sequence, and identifying an extra concentration difference loss component caused by the gas diffusion barrier by correlating the concentration difference polarization loss voltage. And integrating the component, the mapping relation and a reference aging model to calculate a comprehensive health state index. The multi-aging superposition state of the membrane electrode, the proton exchange membrane and the gas diffusion layer can be accurately reflected, aging inducement distinguishing is refined, and the accuracy of health state characterization is improved.

The embodiment of the invention discloses a fuel cell system fault processing method and device, and the method comprises the steps: carrying out the AC impedance spectrum test of a fuel cell, obtaining an AC impedance spectrum, building an equivalent circuit model for the reaction process of the fuel cell, carrying out the fitting of the equivalent circuit model according to the AC impedance spectrum, and obtaining the fault of the fuel cell system. Obtaining impedance data corresponding to each reaction process of the fuel cell; determining residual data between the impedance data corresponding to each reaction process of the fuel cell and the corresponding theoretical data; determining a data change trend of the impedance data according to the residual data; and performing fault diagnosis according to the data change trend to obtain a fault diagnosis result of the fuel cell. According to the fuel cell system fault processing method provided by the invention, the fault of the fuel cell can be diagnosed timely, accurately and comprehensively, the reliability and durability of the fuel cell system are improved, and the service life of the fuel cell is prolonged.

The invention discloses a fault diagnosis method, device and equipment for a fuel cell and a storage medium. The fault diagnosis method of the fuel cell comprises the following steps: analyzing fusion fault data according to an alternating current impedance spectrum of a newly added fuel cell; analyzing the reliability of the fused fault data; when the reliability of the fused fault data reaches a preset fusion threshold value, using the fused fault data to train a preset fault diagnosis model; and diagnosing the fault type of the fuel cell through the trained fault diagnosis model. According to the technical scheme of the invention, the fault diagnosis model can be continuously adjusted according to the fused fault data, so that the fault diagnosis model can be adaptively adjusted according to the aging of the fuel cell and the change of the operation environment, and the accuracy of a fault diagnosis result is ensured.

The invention relates to the field of battery SOH (state of health) prediction, in particular to a neural network-based battery SOH and SOC (state of charge) joint prediction method, which comprises the following steps of: combining an alternating-current impedance spectrum of a battery, battery charging and discharging data and an LSTM (Long Short Term Memory) network, and importing the data into Z-view software for fitting to obtain parameter values of a second-order RC equivalent circuit; parameter values of the second-order RC equivalent circuit and battery charging and discharging data serve as input of the LSTM network, and errors which cannot be solved due to the fact that only a neural network is used are avoided. According to the method, high-correlation input data is screened by using a Spearman rank correlation coefficient, the LSTM network training time and difficulty are reduced, and local features are extracted by using a multi-scale convolution kernel; a self-adaptive Dropout layer is introduced, and the discard rate is set in a standard mode. According to the method, the electrochemical impedance spectrum is measured by the electrochemical analyzer in the charging and discharging process, and the battery mechanism is fully fused by utilizing diversified input, so that the prediction result is more accurate.

A parameter configuration method in a disposable electrocardio-electrode glue-to-glue alternating current impedance test comprises the following steps: (1) selecting a voltage source with an adjustable sine excitation amplitude, preparing a reference resistor R0 with an adjustable resistance value, and preparing a glue-to-glue disposable electrocardio-electrode pair as a test object; (2) connecting the selected and prepared adjustable voltage source, a reference resistor R0 and an electrode pair to be tested in series to form a test circuit; (3) repeatedly testing the alternating current impedance spectrum of the to-be-tested electrode pair for multiple times according to the pairing of one amplitude of sine excitation of the given voltage source and one resistance value of the reference resistor R0, and calculating a repeatability index; (4) changing pairs of the sine excitation amplitude of enough voltage sources and the resistance value of the reference resistor R0, repeatedly testing the alternating-current impedance spectrum of the electrode pair for multiple times under each pair, and calculating a repeatability index value of the alternating-current impedance spectrum; and (5) comparing the repeatability index values to obtain optimal pairing.

The invention relates to the technical field of in-vitro degradation, in particular to an in-vitro degradation monitoring method. The method comprises the following steps: S1, selecting a degradable magnesium alloy stent sample containing a composite coating as a research object, and carrying out cleaning and coating treatment; s2, monitoring the change of the concentration of precipitated magnesium ions by using an inductively coupled plasma mass spectrometer; s3, detecting corrosion-resistant resistance, corrosion-resistant voltage and corrosion-resistant current density by using an electrochemical workstation; s4, observing the change trend of the surface morphology and the coating thickness by using OM and SEM; and S5, monitoring the degradation and molecular weight change trend of the coating polymer by using an infrared and viscosity method. Through cleaning and coating treatment, the cleanness of the surface of the sample and the uniformity of the coating are ensured, and a reliable starting point is provided for subsequent experiments. The degradation rate of the magnesium alloy stent is evaluated by monitoring the concentration change of magnesium ions in the simulated body fluid. The kinetics and corrosion mechanism of the corrosion reaction are analyzed through the polarization curve and the alternating-current impedance spectrum data.

The invention provides a decommissioned battery detection method and device, a battery management system and a storage medium, and the method comprises the steps: obtaining multi-source internal characteristic data of a to-be-detected decommissioned battery, the internal characteristic data comprising at least one of an AC impedance spectrum, pulse characteristic data and a constant-current discharge curve; inputting the multi-source internal characteristic data into a battery health state evaluation model, and obtaining a health state evaluation result of the retired battery output by the battery health state evaluation model; wherein the battery health state evaluation model is a model formed by fusing a physical model based on an electrochemical mechanism and a machine learning model. According to the invention, through fusion of an electrochemical mechanism and machine learning, the detection accuracy of the health state of the retired battery is improved.

The invention discloses a characterization method for the transference number of lithium ions in a lithium ion electrolyte, and relates to the technical field of lithium batteries, and the method comprises the following steps: firstly, preparing aluminum lithium alloy powder into slurry, coating the surface of an aluminum foil with the slurry, drying, and cutting to prepare an aluminum lithium pole piece; sequentially placing an aluminum-lithium pole piece, a diaphragm and an aluminum-lithium pole piece on a pole piece fixing table, and dropwise adding electrolyte before and after placing a layer of diaphragm every time; then a circular sealing ring is placed, a sealing ring is pressed down, and a positive electrode pressing ring is covered and is tightened and fixed through a stud; connecting the two ends of the assembled device through an electrode lead to enable the device to be short-circuited, and standing for 6 hours to enable the open-circuit voltage of the device to be balanced to 0V; an electrochemical workstation is used for testing the alternating-current impedance spectrum of the device, and a pre-polarization impedance diagram of the device is obtained; according to the method, the lithium ion transference number of the electrolyte can be simply and quickly analyzed, the performance difference of the lithium ion transmission efficiency of the electrolyte with different formulas can be accurately reflected, and a basis is provided for formula optimization of the electrolyte.

The invention relates to the technical field of non-invasive bioelectricity detection, in particular to a non-invasive bioelectricity signal detection method based on a flexible sensing technology, and the method comprises the steps: collecting a myoelectricity original signal of a target area through a flexible electrode; synchronously acquiring a skin micro-deformation amplitude parameter captured by a high-frequency micro-strain sensor, an interface impedance change rate parameter generated by dynamic scanning of an alternating-current impedance spectrum, and an electrode contact pressure attenuation parameter quantified by a distributed thin film pressure sensor array; the three types of parameters are input into a dynamic coupling analysis model, a real-time contact pressure compensation instruction is generated through a pressure compensation algorithm, a signal amplification gain adjustment instruction is generated through a gain adaptive algorithm, a periodic pressure maintaining instruction is generated through a pressure attenuation suppression algorithm, and a miniature pressure actuator and a programmable amplifier are driven according to the instructions; the alignment time sequence ensures that adjustment is completed before the peak period of the electromyographic signals, the electromyographic signals with the optimized signal-to-noise ratio are output, and detection accuracy and wearing comfort are both considered.

The invention discloses a parallel detection system for a battery alternating current impedance spectrum. The parallel detection system comprises a microcontroller, a plurality of impedance detection chips and a plurality of current control sub-circuits, the current control sub-circuit and the battery to be detected form an excitation loop, and the impedance detection chip is in signal connection with the current control sub-circuit; the plurality of impedance detection chips are sequentially connected in series in a differential communication manner through the daisy chain topology; the first impedance detection chip is in serial communication connection with the microcontroller. On the other hand, the invention discloses a parallel detection method for the alternating-current impedance spectrum of the battery. The parallel detection method comprises the steps of circuit initialization, parameter configuration, synchronous excitation starting, battery response signal collection, same-frequency signal component extraction, complex impedance calculation, data summarization and alternating-current impedance spectrum generation. The frequency division multiplexing (FDM) technology is adopted, excitation and detection of multiple frequency points are carried out at the same time, the EIS measurement time is shortened from the minute level to the second level or even the millisecond level, and the method is particularly suitable for rapid full detection of a battery production line.

The invention relates to a lithium battery-based cell grouping optimization method and related equipment, and the method comprises the following steps: carrying out the charge-discharge cycle test of a cell group of a lithium battery through a preset charge-discharge system, and obtaining the performance feature data of the cell group; carrying out alternating current impedance spectroscopy analysis on the battery cell group based on the performance characteristic data to obtain impedance spectroscopy characteristic data of the battery cell group; performing complex plane impedance mapping on the impedance spectrum characteristic data to obtain a complex impedance characteristic region of the battery cell group; and determining a cell grouping scheme based on the complex impedance characteristic region, and carrying out multi-target Pareto distribution optimization on the cell group based on the cell grouping scheme to obtain a cell optimization grouping result, thereby solving the problem that the traditional lithium battery cell grouping method is often based on a simple voltage or capacity matching principle, so that the matching efficiency is high. And the influence of a complicated physical and chemical process in the battery cell on the overall performance of the battery cannot be fully considered.

The application relates to a battery parameter measurement method, device, equipment, medium and program product. The method comprises the following steps: acquiring an alternating current impedance spectrum of a proton exchange membrane fuel cell by using a floating ground measurement method of an electrochemical measuring instrument; fitting the impedance of an equivalent circuit with the alternating current impedance spectrum of the proton exchange membrane fuel cell to determine a target impedance of the equivalent circuit; and calculating the parameters of the battery according to target circuit parameters corresponding to the target impedance of the equivalent circuit. The method can acquire the complete alternating current impedance spectrum of the proton exchange membrane fuel cell, can avoid potential interference between the electrochemical measuring instrument and the proton exchange membrane fuel cell, and improves the accuracy of the proton exchange membrane fuel cell parameter measurement.

The invention relates to the technical field of constructional engineering, and discloses a concrete structure intelligent maintenance method based on multi-point impedance sensing. The invention aims to solve the problems that the existing concrete curing technology depends on experience and cannot sense the spatial non-uniformity of the internal state of the structure in real time, so that the curing measures are blind and the structure quality homogeneity is poor. According to the invention, a plurality of impedance sensors integrated with temperature sensors are arranged in a concrete structure, and AC impedance spectrum data and temperature data at different positions of the structure are synchronously acquired; using a pre-constructed correlation model to solve the current performance index of each monitoring position in real time according to the electrical data subjected to temperature compensation correction; and comparing the calculated performance index with a preset maintenance target, and generating a control instruction to drive a maintenance execution mechanism to carry out partitioned and differentiated maintenance operation on the structure.

The present invention provides a lithium battery fast charging converter based on electrochemical impedance spectroscopy (EIS) measurement control and an adjustment method. Before charging, the initial voltage, current and temperature of a lithium battery are measured, and the lithium battery is charged on the basis of an initial state of the lithium battery; and during charging, a perturbation electrical signal formed by superimposing a direct current on a weak sine wave that does not affect the operation of the battery is sent to the lithium battery, EIS measurement and analysis of the lithium battery are performed by means of the EIS technology to obtain state information of the lithium battery, and charging parameters of the charging converter are adjusted on the basis of the state information of the lithium battery. By means of the solution provided by the present invention, the state of a lithium battery is monitored in real time by means of the EIS technology, and charging parameters are dynamically adjusted, so as to implement an efficient, fast and safe charging process.

The invention discloses a lithium battery modeling and parameter identification method based on fractional order, and particularly relates to the field of lithium battery alternating current impedance modeling. Comprising the following steps: S1, establishing an equivalent circuit model containing a fractional order element based on the alternating current impedance characteristic of the lithium battery; s2, applying alternating current excitation to the lithium battery by using a programmable current excitation unit; s3, acquiring a voltage response signal of the lithium battery, and performing filtering, amplification and analog-to-digital conversion processing on the voltage response signal to obtain high-precision alternating-current impedance spectrum data; s4, taking a mean square error between the model prediction impedance and the actually measured impedance spectrum as a fitness function; and S5, identifying parameters of the fractional order impedance model by adopting a whale optimization algorithm. By the adoption of the technical scheme, the problems that a traditional lithium battery modeling method is not high in precision and undefined in parameter physical significance are solved, and accuracy is improved.

The present application relates to the technical field of non-invasive bioelectricity detection, in particular to a non-invasive bioelectricity signal detection method based on flexible sensing technology, which collects the original myoelectricity signal of a target area through a flexible electrode, synchronously acquires the skin micro-deformation amplitude parameter captured by a high-frequency micro-strain sensor, the interface impedance change rate parameter generated by dynamic scanning of alternating current impedance spectrum, and the electrode contact pressure attenuation parameter quantified by a distributed thin film pressure sensor array; inputs the three types of parameters into a dynamic coupling analysis model, generates a real-time contact pressure compensation instruction through a pressure compensation algorithm, generates a signal amplification gain adjustment instruction through a gain adaptive algorithm, and generates a periodic pressure maintenance instruction through a pressure attenuation suppression algorithm, drives a micro pressure actuator and a programmable amplifier according to the instructions, aligns the timing to ensure that the adjustment is completed before the peak period of the myoelectricity signal, and outputs the myoelectricity signal with optimized signal-to-noise ratio, which takes into account the detection accuracy and wearing comfort.

The invention discloses a voltage-sharing electrode impedance measuring and scaling degree judging method, and belongs to the field of voltage-sharing electrode state monitoring of a converter valve cooling system of a high-voltage direct-current transmission system. According to the method, a four-probe difference method is adopted to separate current injection and voltage detection channels, and contact resistance interference is eliminated; the capacitance of the double electric layers is obtained through fitting of a chronoamperometer method and an alternating current impedance spectrum; introducing a temperature and conductivity double-compensation model to correct environmental fluctuation; and establishing a multi-parameter joint discrimination rule of standardized impedance, double-layer capacitance and conduction current. Microohm-level impedance change identification is realized, environmental interference and scaling are effectively distinguished, submillimeter-level initial scaling is stably identified, the state identification accuracy rate reaches 96% or above, online monitoring can be carried out without stopping a converter station, the detection reliability is remarkably improved, and support is provided for safe operation of the converter valve.

The present application relates to the technical field of lithium ion battery, and discloses a method for optimizing compaction density of graphite negative electrode based on relaxation time distribution analysis, which comprises the following steps: preparing dry-state graphite negative electrode base sheets with different gradient compaction densities and assembling them into button-type simulation batteries respectively; performing alternating current impedance spectrum test on the button-type simulation batteries to obtain frequency domain impedance data; using Tikhonov regularization algorithm to deconvolute the frequency domain impedance data and convert it into a relaxation time distribution spectrum diagram with time constant as the abscissa; locating the characteristic peak of a specific time constant interval in the spectrum diagram and performing integration, and extracting the absolute values of charge transfer impedance and diffusion impedance respectively; comparing the above two impedances under different compaction densities, and determining the compaction density corresponding to the common minimum value of the two as the optimal compaction density. The present application overcomes the problem of alternating current impedance polarization semicircle overlap, and quantitatively determines the compaction state in which electronic conduction and ion transport reach balance.

The application discloses a method for collecting and jointly analyzing electrochemical parameters in a corrosion process of a titanium-based material for bipolar plates, and aims at solving the defects of low data correlation in the existing single constant potential polarization and alternating current impedance under constant potential in the corrosion resistance test technology of metal bipolar plates.The method comprises the following steps: 1, placing the titanium-based material for bipolar plates in an electrolyte solution containing H2SO4 and HF, and collecting the alternating current impedance spectrum under bias by using an alternating current impedance measurement program; 2, obtaining the corrosion current density of the impedance data points; 3, drawing a graph of the effective corrosion current density and time in all bias alternating current impedance spectrum measurements; and 4, analyzing the corrosion electrochemical process by the mutation of the effective corrosion current density, the size of the capacitive arc in the Nyquist diagram and the open circuit potential curve.The corrosion resistance of the titanium-based material in the service process can be evaluated by comprehensively analyzing the evolution law of the corrosion current density, the bias impedance and the open circuit potential at the same time.

This invention discloses an online AC impedance detection system and method for large-capacity energy storage batteries, relating to the field of power electronics control. The system includes: n A parallel energy storage battery pack and n A battery management system (BMS) with online AC impedance detection capability is presented. The BMS is equipped with an onboard bidirectional Buck-Boost converter for generating AC excitation current online. The online detection method of the BMS includes: controlling the bidirectional Buck-Boost converter to track the desired excitation signal, generating an excitation current, and injecting it into the intermediate node of two battery modules; acquiring the terminal voltage and current signals of the battery modules and each individual battery cell and extracting the AC components; performing Fast Fourier Transform on the AC components to obtain the frequency domain expression; and calculating the AC impedance spectrum of the two battery modules and each individual battery cell. This method can detect the AC impedance of large-capacity energy storage batteries online and quickly diagnose and locate performance degradation and faulty batteries.

The present application provides a test method, a test circuit, a controller, and a semiconductor memory. A positive bias voltage is applied to the gate of a transistor at a preset temperature to control the mobile ionic charges in the gate oxide layer of the transistor to be away from the interface between the gate and the gate oxide layer of the transistor, and a first AC impedance spectrum of the transistor is tested when a disturbance signal is applied to the gate. A negative bias voltage is applied to the gate of the transistor at a preset temperature to control the mobile ionic charges in the gate oxide layer to move to the interface between the gate and the gate oxide layer, and a second AC impedance spectrum of the transistor is tested when a disturbance signal is applied to the gate. Compared with the equivalent circuit of the transistor under the positive bias voltage, the equivalent circuit of the transistor under the negative bias voltage has an additional series circuit of a capacitor for the mobile ionic charge and a resistor for the mobile ionic charge. Therefore, the difference between the second AC impedance spectrum and the first AC impedance spectrum lies in the influence of the mobile ionic charge, so that the characteristic frequency of the mobile ionic charge can be obtained.

The present invention discloses a battery parameter identification method, system and product, which relates to the field of new energy. The method includes performing a mixed pulse power test on a power battery, and taking the stable voltage value after a set static time as the open circuit voltage value of the current SOC, fitting the mapping relationship between different SOCs and open circuit voltage values ​​to obtain the open circuit voltage identification value, and calculating the ohmic internal resistance value according to the test data under different SOCs; superimposing an AC sine wave on the power battery on an electrochemical workstation to obtain the AC impedance spectrum of the power battery under different SOCs and building a second-order RC model, taking the ohmic internal resistance value under different SOCs as the ohmic internal resistance initial value in the second-order RC model to iteratively fit each polarization parameter, obtaining the identification value of each polarization parameter under different SOCs, and completing the battery parameter identification. The present invention can improve the parameter identification accuracy of the battery second-order RC model.

A parameter configuration method in a disposable electrocardio-electrode-skin contact impedance test comprises the following steps: (1) selecting a voltage source with an adjustable sine excitation amplitude, preparing a reference resistor R0 with an adjustable resistance value, preparing three disposable electrocardio-electrodes A, B and C, and equidistantly pasting the three disposable electrocardio-electrodes on the skin; (2) connecting the selected and prepared adjustable voltage source, a reference resistor R0 and an impedance between the two skin electrodes in series to form a test circuit; (3) repeatedly testing the alternating-current impedance spectrum of the to-be-tested electrode-skin contact impedance for multiple times by pairing one amplitude of sine excitation of each given voltage source with one resistance value of the reference resistor R0, and calculating a repeatability index; (4) changing pairs of sine excitation amplitudes of enough voltage sources and the resistance value of the reference resistor R0, repeatedly testing the alternating current impedance spectrum of the electrode-skin contact impedance for multiple times under each pair, and calculating a repeatability index value of the alternating current impedance spectrum; and (5) comparing the repeatability index values to obtain optimal parameter pairing.

The invention provides a diaphragm testing method and electronic equipment. The method comprises the steps that diaphragm data and electrolyte liquid phase conductivity of each battery in a tested battery pack are obtained, and the number of diaphragm layers included in each battery in the tested battery pack is different; and performing an AC impedance test on each battery to obtain an AC impedance spectrum of each battery. And obtaining the liquid phase impedance of the single-layer diaphragm according to all the alternating current impedance spectrums. And determining performance data of the diaphragm according to the liquid phase impedance of the single-layer diaphragm, the diaphragm data and the liquid phase conductivity of the electrolyte. Performing simulation test and experimental test on the diaphragm according to the performance data to obtain simulation data and real data, comparing the simulation data with the real data, and when the difference value of the simulation data and the real data is within the error range, determining that the simulation precision meets the simulation standard. The diaphragm test method can be simplified, the diaphragm test accuracy is improved, and the diaphragm model selection efficiency is improved.

The present invention discloses a method and device for measuring the AC impedance spectrum of a battery. The method obtains a battery operating waveform, determines the battery inductance, battery ohmic internal resistance, and relaxation time distribution spectrum based on the battery operating waveform, establishes a battery equivalent circuit model using at least one of the battery inductance, battery ohmic internal resistance, and relaxation time distribution spectrum, and determines the battery AC impedance spectrum based on the frequency response of the battery equivalent circuit model. It can be seen that the present invention does not require the addition of external AC excitation, and can obtain the battery AC impedance spectrum by constructing a battery equivalent circuit model using the battery operating waveform. This method not only has low hardware cost and is easy to implement, but also has a fast measurement speed for the battery AC impedance spectrum. The battery equivalent circuit model can also be used to implement online monitoring of the battery.

The invention relates to a method for evaluating the performance of a current drainage device under stray current interference. According to the method, the performance of the current drainage device is comprehensively evaluated by combining laboratory testing, field testing and analogue simulation. A volt-ampere curve and an alternating-current impedance spectrum of the current drainage device are obtained through an electrochemical workstation in a laboratory test, and intrinsic parameters such as conduction voltage, internal resistance and alternating-current impedance of the current drainage device are obtained through fitting. In the field test, direct-current and alternating-current volt-ampere curves are drawn by monitoring drainage quantity and voltage at two ends of the drainage device, performance parameters under actual working conditions are obtained, and changes of pipeline parameters before and after drainage are monitored to verify the protection effect. The simulation module establishes a circuit model according to laboratory and field data, and reproduces and analyzes abnormal volt-ampere characteristics appearing in the field test. According to the method, a closed-loop verification system from intrinsic parameters and actual performance to an internal mechanism is constructed, and comprehensive and quantitative evaluation of the performance of the drainage device is realized.