710 results about "Impedance spectrum" patented technology

The invention discloses a lithium ion battery internal short circuit fault detection method based on time-frequency fusion, and the method comprises the steps: firstly constructing a fractional order equivalent circuit model fused with an electrochemical aging mechanism, and simulating the paths of conductivity reduction, active material loss and lithium inventory reduction in combination with an aging empirical formula; joint modeling of the aging process and the random internal short circuit is achieved, and multi-cycle voltage and current and electrochemical impedance spectroscopy data are obtained; secondly, extracting time domain features by using a time domain attention enhanced long-short-term memory network, and analyzing frequency domain information by using a multi-scale frequency sensing convolutional neural network; and then weighting and screening two types of modal features through a dynamic gating fusion module, introducing a cross attention mechanism to establish dependency mapping between time-frequency domain features, and finally outputting an internal short circuit fault detection result. The method can solve the problems that in the lithium ion battery aging process, due to lithium dendrite growth, the internal short circuit early fault is high in concealment, and single time-frequency characteristics are difficult to detect, and early high-precision recognition of the internal short circuit fault can be achieved.

The invention relates to the technical field of electromagnetic relay control, in particular to an electromagnetic relay control system, which comprises a relay execution unit, a contact state monitoring unit and an intelligent viscosity elimination control unit, and is characterized in that the contact state monitoring unit acquires quantum tunneling effect impedance spectroscopy and acoustic emission energy entropy change signals in real time; the intelligent viscosity-eliminating control unit analyzes signals through a fusion welding risk multi-dimensional evaluator, triggers a three-stage control sequence, firstly starts a magnetostriction high-frequency oscillator to inject an inverted eddy current array, activates a hysteresis loop restorer to apply a gradient demagnetization potential field if the fusion welding risk multi-dimensional evaluator is not recovered, and finally, recovers the fusion welding risk multi-dimensional evaluator; when an acoustic emission signal is abnormal, a chaotic encryption message is generated through the fault feature topology generator and is linked with the magnetic solitary wave breaking device, ultrasonic frequency mechanical energy can be captured and converted into regenerative current, an adhesion evolution path is reconstructed after diagnosis, the problems of contact adhesion risk identification lagging and lack of multi-physics field cooperative control in the prior art are solved, and the reliability of the contact adhesion risk identification is improved. And the adhesion early warning success rate and the removal efficiency are improved.

The invention discloses a precise positioning method for a leakage fault source of a low-voltage distribution network, which belongs to the technical field of power system fault diagnosis and comprises the following steps: acquiring and calculating the voltage unbalance degree and the zero-sequence current value at a total outgoing line of a distribution transformer, generating a primary leakage trigger signal based on a voltage safety threshold and a current safety threshold, and determining the leakage fault source of the low-voltage distribution network. Injecting a characteristic signal with a preset frequency into the line, monitoring the response in the zero sequence loop, and calculating and generating a reference fault path impedance spectrum; and according to the switch topology of the line, sequential opening operation and closing operation are executed to calculate a real-time fault path impedance spectrum, whether impedance spectrum jump exists is judged, a fault branch indication signal is identified and generated, multi-source synchronous data is used for verification, and final fault positioning information is output. Impedance spectrum analysis is carried out by injecting characteristic signals, differential comparison is carried out by combining intelligent switch sequential operation, multi-source synchronous data is utilized to carry out multi-evidence chain verification, and high-precision and high-reliability positioning of an electric leakage fault source can be realized.

The invention provides a battery health state evaluation method, device and equipment and a medium, and the method comprises the steps: collecting multi-source parameters of a power battery in a charge-discharge cycle process, the multi-source parameters comprising voltage, current, temperature and electrochemical impedance spectroscopy; performing feature engineering processing on the multi-source parameters based on a battery aging mechanism, and extracting key feature parameters; the key characteristic parameters are input into a multi-physics field coupling model to simulate thermoelectric coupling behaviors of the battery under a dynamic load, lithium ion concentration distribution and temperature distribution in the battery are obtained, and the multi-physics field coupling model is used for representing a coupling relation between an electrochemical field and a thermal field of the battery; and fusing the key characteristic parameters with data output by the multi-physics field coupling model, and determining a health state evaluation result of the power battery. According to the invention, the accuracy of power battery health state evaluation is improved.

The invention belongs to the crossing field of artificial intelligence and process control, particularly relates to an intelligent coupling control strategy for chlorine production through seawater electrolysis based on digital twinning, and aims to solve the problems of response lag, weak disturbance suppression and lack of electrode aging early warning in a traditional control method. According to the strategy, a high-fidelity digital twin fusing electrochemistry, fluid and thermodynamics is constructed, characteristics of current, temperature, impedance spectroscopy and the like are collected and fused at high frequency through a multi-source sensor, a state space model driven by a deep recurrent neural network is established, and current efficiency and electrode aging coupling evolution recognition is achieved; when salinization or flow mutation is detected, the twinborn body predicts and dynamically calibrates the current density and the voltage set value in advance, and the safety process window is synchronously scaled. According to the strategy, the chlorine gas yield fluctuation is reduced by 60%, the energy consumption standard deviation is reduced by 45%, the fault early warning is advanced by 2-5 hours, the fault-free operation time of the system is prolonged by 50%, and high-precision, self-adaptive and preventive intelligent control of the electrolysis process is realized.

The invention provides a ground wire monitoring method and system, and relates to the technical field of ground wire monitoring. The method comprises the following steps: acquiring a voltage signal of an injection point and a current signal of a grounding loop; preprocessing the signal to obtain a preprocessed signal; according to the preprocessed signals, impedance frequency spectrums of the grounding loop under different frequencies are obtained through calculation, and key feature parameters in the impedance frequency spectrums are extracted; environment parameters and operation state data of the power equipment are collected and fused with the key feature parameters, and fused data are obtained; adjusting a judgment threshold value or a reference baseline corresponding to the key feature parameters by using the fused data; and judging the current grounding loop state by using the adjusted judgment threshold value or reference baseline. According to the method, based on impedance spectrum analysis, electromagnetic interference is overcome through multi-stage signal processing, robust feature extraction and multi-dimensional data fusion analysis, and the effects of adapting to a dynamic baseline and distinguishing different electric leakage types are achieved.

The invention relates to the technical field of lithium ion battery testing, and discloses a lithium ion battery life loss evaluation method and device, a medium and equipment, and the method comprises the following steps: S1, collecting multi-modal dynamic data of a lithium ion battery in a charge-discharge cycle process; s2, performing time-frequency domain conjoint analysis on the multi-modal dynamic data, and extracting a battery aging sensitive feature set; s3, constructing a multi-scale coupling model of battery life loss; by constructing a multi-modal data fusion mechanism and a dynamic feature extraction system, during lithium ion battery life loss evaluation, change trends of electrochemical impedance spectroscopy and heat distribution key parameters are captured in real time based on time-frequency domain conjoint analysis, sensor signal distortion and drift problems can be identified, the extraction precision of aging sensitive features is improved, and the accuracy of lithium ion battery life loss evaluation is improved. The problem of characteristic errors caused by signal interference in traditional evaluation is solved, and the accuracy and reliability of life loss evaluation are ensured.

The invention discloses an online EIS battery pack performance parameter estimation algorithm, and relates to the technical field of battery management, and the algorithm comprises the steps: generating a basic frequency conversion excitation signal through a digital signal generator, and loading the basic frequency conversion excitation signal to a working battery pack through a self-adaptive frequency sweeping strategy; acquiring a response signal, analyzing an impedance real part and an imaginary part of the battery pack at each frequency point through a digital orthogonal synchronous demodulation technology, and constructing an electrochemical impedance spectrum; extracting multi-dimensional health features from the electrochemical impedance spectrum, inputting the multi-dimensional health features into a fusion deep learning model, and estimating the state of charge and the state of health of the battery; and generating a system optimal control signal based on the estimated state of charge and state of health. According to the algorithm, portable, online and real-time detection of the performance parameters of the battery system in the working state is realized, and the application scene limitation of traditional EIS equipment is broken through; and through the optimized signal processing and intelligent algorithm, the detection stability and response speed are improved.

The invention provides a grid-connected and off-grid seamless switching method and system for a network-constructed energy storage micro-grid, belongs to the technical field of grid-connected and off-grid switching, and realizes rapidity and stability of micro-grid mode switching through multi-stage cooperative control. The method comprises the following steps: a power grid state real-time monitoring stage: acquiring power grid short-circuit capacity, impedance angle, voltage amplitude, frequency and phase parameters through impedance spectrum analysis and phase-locked loop cooperative detection; a pre-synchronization-hybrid control-dynamic damping three-stage switching stage; a steady state maintaining stage: maintaining a system damping ratio gt through a multi-target cooperative controller; and in the whole switching process, the bus voltage fluctuation is less than or equal to 2%, and the frequency deviation is less than or equal to 0.1 Hz. According to the method, MPC pre-synchronization, hybrid control of dynamic weight, virtual impedance adaptive compensation and multi-target collaborative optimization are controlled through model prediction, so that the problems are solved, seamless switching is realized, and the quality of electric energy is improved.

The invention discloses a Fourier transform and S transform combined battery impedance spectroscopy measurement method and device, and aims to improve the precision, speed and reliability of impedance measurement of a battery energy storage system. According to the method, a multi-frequency component excitation signal is generated through a controllable current source, and current and voltage response signals of a battery are synchronously acquired and are respectively input into a Fourier transform module and an S transform module for frequency domain analysis. The Fourier transform module extracts impedance spectrums of low and medium frequency bands, and the S transform module extracts impedance spectrums of medium and high frequency bands through Gaussian window time-frequency analysis. And a data fusion algorithm is adopted to perform composite processing on results of the two modules, including a direct selection method, an arithmetic average method, an amplitude and phase calibration method and a weighted average method, so that smooth transition and optimization between frequency bands are realized, and finally the electrochemical impedance spectrum is generated. Through collaborative analysis of Fourier transform and S transform, parameter optimization and a fusion algorithm, the efficiency and accuracy of impedance spectroscopy measurement are remarkably improved, and the method is suitable for rapid monitoring and diagnosis of the battery state.

The invention relates to the technical field of aircraft part processing, testing or inspection and the like, and provides an aircraft aluminum alloy plate aging evaluation method based on an equivalent circuit model, and the method comprises the following steps: collecting electrochemical impedance spectrums of samples with different exposure age limits, and extracting electrochemical impedance spectrum characteristics of the samples; establishing an equivalent circuit model comprising solution resistance, coating resistance, coating capacitance, Warburg impedance, anodic oxide film charge transfer resistance, interface capacitance, aluminum alloy matrix charge transfer resistance, interface electric double-layer capacitance, inductance and corresponding resistance of the inductance based on the characteristics, wherein the equivalent circuit model comprises the solution resistance, the coating resistance, the coating capacitance, the Warburg impedance, the anodic oxide film charge transfer resistance, the interface capacitance, the aluminum alloy matrix charge transfer resistance and the interface electric double-layer capacitance; and analyzing a resistance curve and a capacitance curve obtained by fitting the model to complete the evaluation of the corrosion and aging degree. According to the method, systematicness and accuracy of aging evaluation are improved, an electrochemical mechanism in the corrosion process can be disclosed, time correlation modeling of the aging process can be achieved, and the method is suitable for long-term service performance monitoring and service life prediction of the aviation aluminum alloy structure.

According to the power cable multi-defect nondestructive testing method and system based on the broadband impedance spectrum, impedance characteristics of a cable under different frequencies are measured, frequency domain data are converted into time domain data through inverse Fourier transform, and accurate positioning and evaluation of internal defects of the cable are achieved; the invention discloses a power cable multi-defect nondestructive testing method based on a broadband impedance spectrum. The method comprises the following steps: step 1, signal output and acquisition; the method comprises the steps that a broadband impedance spectrum tester is used for outputting a broadband sine wave voltage signal, frequency domain measurement data are collected, and the frequency domain measurement data are impedance data of a cable under different frequencies; 2, carrying out time-frequency conversion; converting the frequency domain measurement data into time domain data through inverse Fourier transform, generating a time-amplitude curve, and analyzing the electrical characteristics of the cable; 3, establishing a defect identification model; analyzing the electrical characteristics of the cable at different frequencies by using the transmission line model, and evaluating the state of the cable; step 4, defect positioning and evaluation; and 5, displaying and analyzing a result.

The invention discloses an intelligent wearing health monitoring method and system based on biological impedance analysis, and relates to the technical field of biomedical engineering. The method comprises the following steps: constructing an original impedance spectrum of a biological tissue, and synchronously collecting an original impedance signal; a two-channel impedance model is constructed, and quantitative evaluation of the electrode contact quality is achieved; constructing a time-varying transfer function to obtain a de-noising impedance time-frequency signal; establishing a Cole impedance model, extracting characteristic parameters through a tensor decomposition method, and constructing a dynamic tissue parameter matrix; physiological feature vectors are generated through a multi-layer perceptron; constructing a metabolic impedance coupling differential equation to obtain a body component estimation vector, and realizing dynamic tissue parameter weight distribution and sensitivity adjustment; and carrying out grading evaluation on the calibrated body component vector. The stability and adaptability of the system are improved by optimizing impedance measurement, constructing a high-dimensional tissue parameter model, dynamically estimating body components, enhancing the interpretability of health assessment, cooperatively processing physiological state parameters and fusing multi-source information.

A method and apparatus for frequency domain diagnosis of a power cable defect on the basis of a cross-interconnection box structure. The method comprises: by means of a wiring terminal intersecting a three-phase shielding layer of a cross-interconnection box, injecting a broadband signal, and obtaining a time domain result (S101); according to the time domain result being mapped into a frequency domain, performing analysis, and obtaining impedance spectrum results of a left end and a right end of an injection cross-interconnection box (S102); and, according to the impedance spectrum results, diagnosing hidden danger defects of an outer sheath and a main insulation in a three-phase cable (S103). The present disclosure solves the problem in the related technology that traveling wave reflection method diagnosis strategies cannot avoid direct connection to a cable core wire when identifying a main insulation fault in a cable, which limits the application scenarios of a traveling wave injection method to only being applicable to inspection before a cable has been put into operation and cable defect assessment after a cable fault has occurred. Additionally, the present disclosure solves the problems of high device requirements and testing costs, leading to the inability to meet daily operation and maintenance inspection requirements of cables and various test scenarios.

The invention discloses a power cable insulation state evaluation method and system based on a broadband impedance spectrum, relates to the technical field of cable insulation, and is used for solving the problem that a defect grading result deviates from a real aging process of a cable. The method comprises the following steps: extracting broadband reflection data, calling a corresponding insulation aging type, converting a phase sequence in the broadband reflection data into a phase deviation coefficient for region screening, extracting a reflection peak value based on a reflection coefficient amplitude sequence, calling a corresponding impedance variation reference according to the insulation aging type, and performing region screening. The method comprises the following steps: generating impedance variation characteristics in combination with a reflection coefficient peak value, judging whether a defect grading mechanism is entered, detecting discharge pulse count and insulation recovery time of a marked division region, generating marked division defect grades according to a detection result, and distinguishing impedance variation modes corresponding to different aging forms in judgment. And the defect grading result better conforms to the actual aging process of the cable.

The invention provides an intelligent battery sorting method integrating impedance characteristics and deep learning. The method comprises the following steps: acquiring battery impedance data through an electrochemical workstation, drawing an electrochemical impedance spectroscopy (EIS), and extracting impedance characteristics of a medium-frequency region; a 25-dimensional impedance coupling feature space is innovatively constructed, a dual-network differentiated feature selection strategy (IC-GRU) is adopted, a main network selects 12 features with the highest correlation, a boundary expert network selects 10 features with the highest correlation and additionally constructs 5 boundary sensitive features, and finally, the main network selects 12 features with the highest correlation. And establishing an impedance coupling sensing gating circulation unit network to realize accurate prediction of the state of health (SOH). And performing four-stage sorting on the SOH result predicted by the IC-GRU through a random forest algorithm (RF). According to the method, more accurate SOH prediction is realized through deep learning guided by a physical mechanism, the battery pack health state sorting precision and consistency are improved, and an intelligent solution is provided for new energy automobile battery life management.

The invention discloses a lithium battery solid electrolyte interface film forming quality evaluation method. The method comprises the following steps: in a lithium battery formation stage or a circulation process, applying an alternating current disturbance signal with an amplitude of 1-20mV, and collecting full-band electrochemical impedance spectroscopy data in real time; a relaxation time distribution method is adopted to decouple the electrochemical impedance spectrum of the intermediate frequency region; constructing an equivalent circuit model containing SEI film characteristics, and fitting the decoupled electrochemical impedance spectrum curve by the equivalent circuit model; the compactness index of the SEI film is calculated according to the SEI film resistance and the film capacitance, and whether the compactness of the SEI film reaches the standard or not is judged according to the compactness index; and calculating a lithium ion diffusion coefficient by combining the charge transfer resistance and the Warburg diffusion impedance, and evaluating the SEI membrane ion transmission efficiency. According to the invention, non-destructive monitoring is supported, quantitative evaluation of SEI membrane compactness, ionic conductivity and short circuit faults in the module can be realized, and the cycle life and safety of the lithium battery are improved.

The invention discloses an electrochemical impedance spectroscopy detection method and system and related equipment. The electrochemical impedance spectroscopy detection system comprises: a battery pack comprising a plurality of cells; the battery cell management module is connected with the plurality of battery cells and is used for acquiring response voltage of the battery pack and performing discrete Fourier transform on the excitation current and the response voltage to obtain an electrochemical impedance spectrum of the battery pack under the target excitation frequency; the battery management module is connected with the excitation source module and used for sending the target excitation frequency to the excitation source module; and the excitation source module is used for generating excitation current according to the target excitation frequency sent by the battery management module.

The invention discloses a battery internal defect detection method, system, medium and equipment, and the method comprises the steps: preparing battery samples with different defects; performing an electrochemical impedance spectroscopy test on the battery sample under the same temperature environment, and establishing an impedance spectroscopy database of the battery in a normal state and a defect full charge state under a normal temperature working condition; calculating charge transfer impedance, solid electrolyte interfacial film impedance and relaxation time of a corresponding characteristic peak in the impedance spectrum data through the relaxation time distribution curve area, and analyzing the charge transfer impedance, the solid electrolyte interfacial film impedance and the relaxation time of the corresponding characteristic peak; constructing a battery internal defect identification model to accurately identify whether the battery has internal defects or not; performing relaxation time distribution quantification at a constant temperature to obtain charge transfer impedance, solid electrolyte interfacial film impedance and relaxation time of a corresponding characteristic peak; and importing the charge transfer impedance, the solid electrolyte interfacial film impedance and the relaxation time of the corresponding characteristic peak into the battery internal defect identification model to obtain a diagnosis result of whether the defect exists in the single battery or not.

The invention specifically relates to a standardized fuse fault monitoring and diagnosis system, and relates to the technical field of power system protection equipment monitoring. A signal processing and impedance spectrum calculation module; an intelligent diagnosis and state evaluation module; and a benchmark management and personalized tracking module. According to the invention, controllable micro test signals are actively injected to obtain frequency domain impedance fingerprints, and accurate capture of microscopic degradation is realized; non-intrusive coupling and signal injection are adopted, the topology of a main loop does not need to be changed, the inherent protection characteristic of the fuse is guaranteed, and power frequency interference can be penetrated; the recognition amount of budding faults such as contact oxidation and melt corrosion is improved in advance, and power failure accidents caused by fault expansion are avoided.

The invention belongs to the technical field of echelon recycling of retired lead-acid storage batteries, and particularly relates to a lead-acid storage battery capacity consistency screening method based on electrochemical impedance spectroscopy characteristic parameters. The method comprises the following steps: by taking 104 power grid decommissioned GFM series valve-regulated sealed lead-acid storage batteries as objects, firstly, measuring an electrochemical impedance spectrum in a range of 0.01 Hz-1 kHz by utilizing a Coster CS2350H electrochemical workstation, acquiring data by injecting a tiny voltage signal, and calculating impedance through Fourier transform; and then the actual residual capacity is measured through a specific charging and discharging process by using charging and discharging testing equipment. According to a measured impedance spectrum curve, after effectiveness is detected through KK transformation, part of frequency band data is removed, LR (CR) (QR) is selected to establish an equivalent circuit model, impedance spectrum fitting is carried out to determine capacity consistency screening characteristic parameters, finally 24 single batteries with good capacity consistency are screened out from 104 batteries to be recombined and reused, the difference between the maximum capacity and the minimum capacity of the selected batteries is only 48Ah, and the maximum capacity and the minimum capacity of the selected batteries are only 48Ah. And an effective way is provided for improving the screening efficiency and resource reutilization of the retired lead-acid storage battery.

The invention belongs to the technical field of simulation calculation, and particularly relates to a metal grounding body underground water corrosion characteristic simulation calculation method, which comprises the following steps: preparing a metal grounding body sample, and preparing an electrolyte; carrying out a polarization curve and electrochemical impedance spectroscopy test, and carrying out data fitting and corrosion kinetic parameter extraction on a test result; establishing a three-dimensional finite element model of the metal grounding body under an actual environment condition based on a polarization fitting curve obtained by data fitting and the extracted corrosion kinetic parameters; and performing grid division, performing simulation calculation on corrosion rates of the metal grounding body under different environmental conditions, and further calculating corrosion rate distribution, thereby realizing corrosion rate prediction of the metal grounding body under the actual environmental condition. According to the method, electrochemical experiment testing and finite element simulation modeling are fused, and the method is suitable for conducting quantitative prediction and material comparison evaluation on the corrosion rate of the metal grounding body in the groundwater environment where different pH values and multiple corrosive anions coexist.

The invention discloses a square lithium ion battery external insulation damage detection method, system, medium and equipment, and the method comprises the steps: carrying out the electrochemical impedance spectrum measurement of a square battery with an external insulation state to be detected, and obtaining an electrochemical impedance spectrum; building an equivalent circuit based on the electrochemical impedance spectrum to obtain each characterization electrical element parameter in the equivalent circuit; high-frequency insulation resistance and interface capacitance in the equivalent circuit are extracted, and the damage condition of the outer insulation film of the square lithium ion battery is detected through parameter differences.

The invention provides a new energy station grid-connected oscillation risk assessment method and device, and relates to the field of new energy grid-connected control. The method comprises the following steps: constructing a dynamic equivalent model based on new energy station operation parameters; based on the dynamic equivalent model, obtaining impedance spectrum feature domains in different control modes; calibrating an impedance spectrum feature domain based on a semi-physical simulation platform; inputting the calibrated impedance spectrum feature domain into a grid-connected oscillation risk assessment model, and outputting oscillation damping ratio predicted values of the new energy station in different control modes based on the grid-connected oscillation risk assessment model; and constructing a self-adaptive threshold, and evaluating the grid-connected oscillation risk of the new energy station based on the magnitude relationship between the oscillation damping ratio predicted value and the self-adaptive threshold in different control modes. The method solves the problems that when different control modes are switched or external operation conditions are changed, a prediction result of a traditional method is prone to distortion, and the real oscillation risk of the new energy station is difficult to reflect accurately.

The invention discloses an early warning method for thermal runaway of an energy storage system. The early warning method comprises the following steps that a detection unit is installed on each unit of the energy storage system and connected with an upper computer; setting data processing and early warning judgment related parameters; acquiring electrochemical impedance spectroscopy data of the energy storage system in real time; performing optimization processing on the electrochemical impedance spectroscopy data by using a data filtering algorithm; and calculating an impedance change rate based on the electrochemical impedance spectrum data, and if the impedance change rate is greater than a set threshold value, sending an alarm signal and taking emergency measures. According to the thermal runaway early warning method of the energy storage system, the abnormal state of the battery, especially the early signal of thermal runaway, can be sensitively monitored through real part and phase angle changes under different frequencies, and higher-precision early warning is provided.

The invention discloses a single-hole pressure adjusting method, device and equipment for a water curtain test of an underground water-sealed cave depot and a storage medium, and relates to the technical field of geological engineering.The method comprises the steps that firstly, a rock mass acoustic impedance spectrum is collected, intrinsic mode decomposition is carried out to extract geologic feature components, and the rock mass acoustic impedance spectrum is obtained; processing the target pressure value, the current pressure value and the geologic feature component by using a pressure-opening coupling model based on acoustic feature extraction, time sequence dynamic analysis and physical constraint decoding to obtain a reference valve opening; then, a water curtain hole valve is adjusted according to the reference valve opening degree, and the pressure change acceleration is monitored in real time; calculating an opening compensation increment and a damping attenuation coefficient based on the pressure change acceleration, and further generating a target valve opening; and finally, the valve is adjusted to the target opening degree, so that the water curtain hole reaches the target pressure value. According to the invention, high-precision self-adaptive adjustment of the pressure of a single water curtain hole can be realized in the water curtain test of the underground water-sealed cave depot.

The invention discloses a battery rate adjusting method and system based on joint calculation, and the method comprises the steps: collecting real-time operation parameters of a battery, the real-time operation parameters comprising a real-time current, a real-time voltage observation value, a first electrochemical impedance spectrum, a first temperature stress and a first cycle index; obtaining an SOH value based on the first electrochemical impedance spectrum, the first cycle index and the first temperature stress; estimating based on the SOH value and the real-time current to obtain a first SOC value; correcting the first SOC value based on the real-time voltage observation value to obtain a second SOC value; and determining a first charge-discharge rate according to the SOH value and the second SOC value, and controlling the charge-discharge current of the battery according to the first charge-discharge rate. According to the method, the problems that SOC estimation is not accurate, SOH evaluation lacks dynamics, and rate control is single are solved, and intelligent and self-adaptive adjustment of charge and discharge rates of the battery in different operation states is achieved.

The invention discloses a method and a device for acquiring an electrochemical impedance spectroscopy in a segmented manner, and solves the problems of large data volume, high sampling rate, long measurement time and the like in the traditional full-band EIS (Electrochemical Impedance Spectroscopy) test. A target frequency range of an electrochemical system is divided into a plurality of sub-frequency bands according to a preset rule, and an excitation waveform and a sampling parameter are set for each frequency band, so that segmented measurement is realized. For data collected by each sub-frequency band, the system calculates frequency domain characteristics of voltage and current response through methods such as fast Fourier transform (FFT) and the like, and obtains a complex impedance spectrum of the frequency band. And resampling, splicing and fitting all the sub-frequency-band impedance data to obtain a complete wide-frequency-band impedance spectrum. The system complexity and the calculation burden are small in the collection process, and the collection process can be achieved on a single-chip microcomputer.

The invention discloses a capacitor pin health state monitoring method and system and a storage medium, and relates to the technical field of health management, and the method comprises the steps: applying a multi-frequency excitation signal to a capacitor pin for data collection, obtaining pin impedance spectrum data, and synchronously capturing a heat distribution image data set; performing multi-modal feature fusion on the pin impedance spectrum data and the heat distribution image data, extracting a degradation feature vector, predicting the service life of the pin based on the vector, and generating a residual life prediction value; health state grades are divided according to the predicted value, an automatic sorting instruction is triggered to carry out sorting identification, and a health monitoring result is generated. According to the invention, the technical problems of one-sided health state evaluation and low residual life prediction precision caused by the dependence of a single electrical or thermal parameter in a traditional monitoring method are solved, and more accurate health monitoring and life prediction of the capacitor pin are realized through multi-modal data fusion. The monitoring accuracy is improved; and the equipment maintenance and health management efficiency is optimized.

The invention discloses a battery health state detection method, device and equipment and a storage medium, which are applied to the technical field of battery health states, and align a voltage sequence and a current sequence by acquiring the voltage sequence, the current sequence, temperature distribution data and electrochemical impedance spectroscopy parameters of a to-be-detected lithium battery to obtain aligned data; the method comprises the following steps: extracting temperature distribution data to obtain gradient change characteristics, extracting electrochemical impedance spectroscopy parameters to obtain a relaxation time constant, constructing a multi-dimensional degradation index by fusing the gradient change characteristics and the relaxation time constant, and inputting aligned data and the multi-dimensional degradation index into a target integrated learning model for processing. According to the method, the estimation precision of the health state of the battery is effectively improved.