1576 results about "Equivalent circuit" patented technology

Disclosed in the present invention are a method and system for small-signal stability analysis of a power plant containing grid-forming converters. The method comprises: establishing a grid-following converter impedance model; establishing a grid-forming converter impedance model; constructing a new energy power plant grid-connected system model containing grid-following converters and grid-forming converters; establishing a simplified equivalent circuit of a power plant grid-connected system; establishing a small-signal stability Nyquist criterion for a grid-connected new energy power plant containing grid-forming converters; and using a Nyquist plot to analyze the small-signal stability characteristics of the power plant grid-connected system. According to the present invention, the problem in the prior art of lacking quantitative and effective analysis of small-signal stability in new energy power plants containing grid-following converters and grid-forming converters is solved, and establishing a small-signal stability criterion for the power plants on the basis of established small-signal models enables quantitative analysis of the small-signal stability characteristics of a new energy power plant containing grid-forming converters under low grid strength conditions, and compared with conventional impedance modeling methods for new energy power plants, the impact of grid-forming converter integration on the small-signal stability of the new energy power plants is better reflected.

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 an agricultural biomass characteristic intelligent detection method, system and device based on multi-frequency conductance coupling and a medium, and the method comprises the following steps: applying an electric excitation signal to an agricultural biomass sample, and synchronously collecting multi-physics coupling response data; based on the multi-physics field coupling response data, constructing a multi-scale equivalent circuit model comprising a resonance unit, a constant phase unit and a diffusion impedance unit; synchronously optimizing a resonance unit parameter, a constant phase unit parameter and an impedance unit parameter of the multi-scale equivalent circuit model through a Bayesian joint inversion algorithm to obtain an optimal parameter combination; and according to the optimal parameter combination, calculating a preliminary detection result of biomass components containing cellulose crystallinity, lignin crosslinking degree and water content, combining the collected environment temperature and humidity sensing data to implement dynamic compensation, and outputting a final detection result. Therefore, the detection precision, the environment robustness and the operation reliability are synergistically improved in three aspects of hardware design, model construction and algorithm optimization.

The invention provides a multi-dimensional grid-connected test system for a photovoltaic string inverter, and the system comprises a power grid simulation module which is used for constructing a power grid simulation environment based on a multi-dimensional coupling mechanism of voltage fluctuation, frequency deviation and harmonic distortion; the photovoltaic array simulation module is used for constructing IV characteristic dynamic deduction models of different irradiance and temperature gradient effects based on a photovoltaic array equivalent circuit physical model to realize a natural simulation environment; the loading module is used for loading the power grid simulation environment and the natural simulation environment to the photovoltaic string inverter to be tested; the data acquisition module is used for monitoring running state data of the photovoltaic string type inverter in real time and constructing a running state data set containing multi-physical-quantity coupling characteristics; and the diagnosis module is used for inputting the running state data set into the trained LSTM neural network model to obtain a test result of the photovoltaic string inverter. According to the invention, the efficiency and convenience of the grid-connected test of the inverter can be improved, and the accuracy and reliability of the grid-connected performance of the inverter are ensured.

The invention discloses a harbor shore power system oscillation damping suppression method based on heuristic probability optimization. According to the method, sliding window preprocessing is carried out on an alternating current bus side current time domain oscillation signal, modal decomposition is carried out based on a Prony algorithm, and modal energy is calculated to judge an oscillation mode; the discriminated oscillation modes are aggregated and mapped into equivalent circuit elements, a corresponding three-order circuit state matrix is constructed, and the damping ratio of each mode is determined according to the characteristic value of the matrix; taking a damping ratio as an evaluation index, introducing an influence factor to construct a multi-objective optimization function, parameterizing the parallel adjustable impedance, and limiting an adjustable range; and searching the control parameters by adopting a heuristic probability optimization strategy to obtain final damping control parameters, and downloading the final damping control parameters to the parallel adjustable impedance device to realize online dynamic adjustment. According to the method, multi-modal identification, physical magnitude mapping and online adaptive optimization can be realized, and the suppression capability and the operation stability of the shore power system on sub / super synchronous oscillation are improved.

The invention relates to a joint estimation method for SOC and SOH of a power battery, in particular to a joint estimation method for SOC and SOH of a lithium ion power battery based on FOASEKF-EKF, comprising fractional order equivalent circuit models of two parallel fractional order CPE branches, and providing a hybrid genetic algorithm HGA fusing a differential evolution strategy and an adaptive variation mechanism. Accurate estimation of SOC and terminal voltage under a fast time scale is realized by introducing a sliding-mode observer and an FOASEKF, periodic online correction is performed on model parameters and battery capacity based on an EKF under a slow time scale, and high-precision and high-robustness battery SOC and SOH joint estimation is realized. The method is suitable for complex industrial environments such as electric automobiles and rail transit, does not need to set a large number of hyper-parameters, does not excessively depend on the quality and quantity of data, has good interpretability, adaptability and engineering practicability, can still achieve high-precision cooperative estimation of SOC and SOH especially under the working conditions of frequent start and stop and unsteady operation, and has good application prospects. And misjudgment and drift estimation risks are obviously reduced.

Provided in the present application are a balanced charging method and apparatus for a battery pack, and a computer program product. Charging current control consists of two stages, i.e., a "pulse square-wave excitation" stage and a "multi-stage current-reduction charging" stage. During the pulse square-wave excitation stage, the parameter identification of an equivalent circuit model and the joint estimation of state variables are realized, thereby providing reliable battery parameters for a subsequent balancing process. During the multi-stage current-reduction charging stage, a flyback converter is used to control a balanced current of each battery cell, and the battery cells remain in a charging state throughout a balancing process, thereby effectively mitigating the impact of a hysteresis voltage.

The present disclosure provides a fault measurement impedance calculation method and device for a hybrid grid-following / grid-forming wind power system. The method comprises: acquiring characteristics of a grid-following converter and a grid-forming converter, and corresponding low-voltage ride-through control strategies; establishing an equivalent circuit corresponding to a fault state; performing simplified analysis on a hybrid wind power system to obtain an equivalent network diagram; obtaining a branch circuit diagram under individual action of each power excitation; obtaining short-circuit currents and grid-connected point voltages on two sides of the system corresponding to the individual action of each power excitation; performing superimposition to obtain a total short-circuit current and a total grid-connected point voltage at the two sides of the hybrid wind power system; and obtaining a measurement impedance at a protection installation point on a new energy side. In the method, a measurement impedance value at a protection installation point of a hybrid wind power system after a fault occurs can be accurately calculated, so that the setting calculation of distance protection is ensured, so as to accurately reflect fault characteristic information of a hybrid AC system, thereby providing a basis for the distance protection applicability research of the hybrid wind power system, and thus ensuring the safe and stable operation of new energy systems.

The invention discloses a broadband wave-absorbing material based on an MAX-phase metasurface structure and an impedance matching optimization method of the broadband wave-absorbing material. The wave-absorbing material comprises an MAX-phase ceramic substrate and periodic metasurface structures which are arranged on the surface of the MAX-phase ceramic substrate in an array mode and composed of conductive resonance units. The resonance units are isolated through gaps, an equivalent R1L1C1 series resonance circuit is formed in an electromagnetic field, and a base body is equivalent to a parallel resistor R2. By establishing an equivalent circuit model and optimizing parameters R1, L1, C1 and R2, impedance matching of the wave-absorbing material in a target frequency band can be regulated and controlled, so that the wave-absorbing material at least has an absorption peak of which the reflection loss is less than-10 dB. According to the optimization method, electromagnetic simulation and circuit simulation are combined, optimized circuit parameters are reversely mapped into structure geometric parameters, material preparation is guided, and accurate design and broadband absorption of the wave absorbing performance are achieved.

The invention provides a general electromechanical transient modeling method and system for a network-building converter, and relates to the technical field of electromechanical transient modeling, and the method comprises the steps: simplifying the electromagnetic transient models of network-building converters of different topologies into a grid-connected equivalent circuit of an electromechanical transient time scale; uniformly representing by using an internal potential series reactance model controlled by a power outer ring so as to establish an electromechanical transient general grid-connected interface model of the grid-forming converter; combining mathematical transformation of active power control with a reactive power control mode to form a general power outer loop control model of the network construction type converter; through a method based on internal potential reconstruction, reconstructing a new internal potential satisfying a current limiting constraint, and establishing a general current limiting model suitable for a network construction type electromechanical transient model; according to the method, various topological structures, various power outer loop control and various current limiting strategies can be simulated, flexible use of models in large-scale power system simulation is facilitated, and the complexity of model development and maintenance is reduced.

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.

The invention provides a lithium ion battery health state estimation method and system based on a dual-drive interpretable integrated model, and belongs to the field of lithium ion battery health state estimation. The problems that an existing lithium battery health state monitoring method is single in feature source, insufficient in model generalization ability and poor in interpretability are solved. According to the method, based on an incremental capacity curve and a first-order RC equivalent circuit model, IC peak value features and ohmic internal resistance features are extracted, and a multi-source health feature space is constructed in combination with voltage statistical features; an integrated learning model based on Stacking is established, three basic models of a random forest, kernel ridge regression and an interpretable enhancement machine are integrated, and collaborative optimization of model hyper-parameters is realized by adopting a tree structure-based Bayesian optimization algorithm.

The invention relates to the technical field of battery health management, in particular to a series battery high-precision electric quantity monitoring method and system based on an adaptive algorithm, and the method comprises the steps: obtaining multi-dimensional parameter data of a series battery pack; operating a main state estimator based on an electrothermal coupling equivalent circuit model, and performing online estimation according to the multi-dimensional parameter data to obtain a baseline state-of-charge value; predicting an estimation error of the baseline state-of-charge value based on the multi-dimensional parameter data by adopting a probability error prediction model, and outputting error probability distribution; generating a final high-fidelity state-of-charge estimation value by using the error probability distribution through a dual-channel self-adaptive collaborative correction process; and constructing and driving a battery protection model by using the final high-fidelity state-of-charge estimation value and the multi-dimensional parameter data, and outputting a safety control instruction for controlling and protecting the series battery pack. According to the invention, accurate monitoring and active safety protection of electric quantity are realized by using a self-adaptive algorithm.

The invention discloses a low-complexity, high-precision and high-robustness battery state of charge estimation method and system, relates to the field of battery state of charge estimation, and aims to solve the problems of high cost, to-be-improved precision, poor robustness and the like of the existing battery state of charge estimation technology. According to the technical key points, firstly, a second-order equivalent circuit model is established through an off-line experiment, an off-line parameter identification means is adopted, the magnitude difference between to-be-identified model parameters and fitting voltage is reduced, and the fitting precision is improved; and fitting the relationship between the model parameters obtained by the off-line parameter identification and the SOC, and fitting an OCV-SOC relationship curve by using the third-order Gaussian after the fitting points are added. A battery end voltage and a current value measured by a sensor in real time are input into an ECM model for calculating an OCV value, sliding window filtering of variable weight distribution is carried out on the calculated OCV value to smooth a curve and reduce errors, a filtered result is fitted through an OCV-SOC relation curve to obtain an SOC value, and the SOC value is used as an observation value of subsequent Kalman filtering. A predicted value is calculated by using an ampere-hour integral method, and a current model parameter is fitted by using the priori value in combination with a relationship between the model parameter and the SOC. And finally, Kalman filtering is carried out on the two to obtain a posterior SOC value.

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.

In an example, an electrochemical monitoring system for determining one or more parameters of interest of an electrochemical cell can include measurement circuitry, which can be configured to obtain, for a plurality of specified alternating current (AC) frequencies: (1) a first AC voltage measurement across nodes which can be coupleable to the electrochemical cell, and (2) a second AC voltage measurement across a sensing impedance which can be elicited in response to the AC stimulus. The sensing impedance can be coupled in series with the electrochemical cell. The electrochemical monitoring system can also include a controller circuit, which can be configured to jointly estimate model parameters corresponding to an equivalent circuit model (ECM) of a combination of the electrochemical cell and the sensing impedance, such as using the first and second AC voltage measurements for the plurality of specified AC frequencies.

The invention belongs to the field of electrical variable measurement, and particularly relates to a single battery equalization management method for a lithium battery BMS (Battery Management System) protection board, which comprises the following steps of: acquiring voltage, temperature, total current and cycle index of each single battery in real time; based on a second-order equivalent circuit model and an extended Kalman filtering algorithm, multi-source information is fused, and the health state and the charge state are estimated with high precision; constructing a dynamic equilibrium trigger threshold fusing the charge state standard deviation, the range and the health state attenuation factor; a bidirectional flyback or multi-winding transformer active equalization strategy is selected according to the inconsistent distribution characteristics and the temperature field, and equalization current is accurately controlled through pulse width modulation; and continuously monitoring the efficiency, the temperature rise rate and the convergence in the equalization process, and dynamically optimizing the equalization parameters by using the fuzzy logic controller until the inconsistency reaches the standard. According to the technical scheme, accurate, self-adaptive, high-efficiency and safe single battery equalization management can be realized, the service life of the battery pack is effectively prolonged, and the operation reliability of the system is improved.

The invention discloses a battery failure reason prediction method and a computer storage medium, and the method comprises the steps: outputting EIS prediction data through a time sequence model according to the data in the charging and discharging process of a battery; according to EIS prediction or actual measurement data, relaxation time characteristic peak time and corresponding intensity are obtained; constructing a candidate circuit topology in the element library according to the characteristic peak time and intensity and EIS prediction or actual measurement data, and calculating and outputting an optimal equivalent circuit model character string and a parameter set; fusing relaxation time characteristic peak time and intensity, an optimal equivalent circuit model character string, a parameter set, a structural characteristic and a current / voltage derivative characteristic, splicing into a low-dimensional vector, and constructing an electrochemical state fingerprint; carrying out embedded representation on the electrochemical state fingerprints, and recognizing typical degradation state clusters through dimension reduction and clustering; and performing failure cause semantic attribution, and outputting a failure cause category and a prediction report. According to the invention, automatic identification and output of potential failure reasons of the battery are realized.

The invention relates to an admittance matrix processing module and a power flow type parallel computing device, and the admittance matrix processing module comprises an admittance matrix flow type computing module which is used for receiving branch data, judging whether a branch contains a transformer or not according to the value of the transformation ratio of a non-standard transformer, and computing a branch equivalent circuit, mutual admittance calculation of the current node frombus to the target node tobus is completed within the interval of receiving the data of the two branches, and a calculation result is synchronously written into an admittance matrix queue; and the admittance matrix access module is used for receiving the mutual admittance value in the upper triangular form in the admittance matrix queue and writing the mutual admittance value in the upper triangular form into the memory when the write burst length of the memory is reached. According to the method, the admittance matrix value and the parallel pipeline calculation of the power flow are calculated in a dynamic streaming manner.

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 discloses an adaptive weighted physical information neural network-based monomer voltage prediction method. The method comprises the steps of constructing a sample set according to real vehicle battery multi-dimensional time domain data; establishing a physical branch output monomer voltage physical prediction vector based on an equivalent circuit model; constructing data branches based on a graph attention mechanism to extract node time sequence features to obtain a data-driven prediction vector; a residual error is calculated, a compensation module generates a correction amount, and the correction amount is superposed to a physical prediction vector to obtain a final prediction result; and constructing a multi-step loss function of physical loss and data loss, and introducing an adaptive weighting mechanism to dynamically adjust loss weight iteration optimization parameters. According to the method, the precision and stability of single voltage prediction under a complex operation condition are effectively improved, and the adaptability and generalization performance of the model are enhanced.

The invention discloses a lithium battery dynamic rapid charging track generation method based on multi-state estimation and risk criterion, belongs to the technical field of electric vehicle lithium ion battery charging, and aims to solve the problem that the charging speed, the energy efficiency and the battery life are difficult to consider in the rapid charging process of a lithium ion battery in a wide temperature range. And a relatively high lithium plating safety risk exists. The method comprises the following steps: firstly, constructing an electrochemical thermal aging coupling model, and establishing a lithium plating risk criterion and risk map based on the model; then, on-line multi-state estimation is realized based on an electrothermal coupling equivalent circuit model, and a multi-objective optimization function and a safety constraint system which comprehensively consider charging time, energy efficiency and life loss are constructed; and finally, a model prediction control framework is utilized, a state estimation result and a risk criterion are fused, and an optimal charging current track is generated in a real-time rolling manner.

A circuit simulation method partitions circuits into linear and nonlinear subcircuits, obtains frequency responses of the linear portion, and applies causality-enforcing corrections to eliminate non-physical artifacts from band-limited data. The corrected responses enable construction of equivalent circuit models using voltage / current sources with passive elements, where source values update via convolution with port histories. This approach improves simulation accuracy and stability compared to direct frequency-inverse methods while maintaining compatibility with standard platforms including SPICE, PSCAD, and Simulink. Applications include power system transients, RF circuits, and high-speed digital interfaces.

The invention provides a battery power state prediction method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the data preprocessing of the working condition data of a battery, and determining the processed working condition data; constructing a battery model based on the microscopic electrochemical process, the mesoscopic equivalent circuit characteristic, the macroscopic thermal behavior and the processed working condition data; key parameters of the battery model are identified and updated based on a hierarchical online updating mechanism, so that the battery model determines internal state parameters of the battery; determining a dynamic security boundary in real time based on the internal state parameters; and by taking the dynamic safety boundary as a constraint condition, optimizing and solving the real-time available charging and discharging power of the battery through a predictive control algorithm. By constructing a multi-scale hybrid model, the precision and robustness of battery power state prediction are improved; and a hierarchical online parameter identification mechanism is adopted, so that the dynamic adaptive capacity of the model to battery aging and environment change is enhanced, and the prediction performance is ensured not to be degraded along with the use time.

The lithium battery pack health state estimation method based on data driving and equivalent circuit model fusion comprises the following steps: acquiring actual operation data of a lithium battery pack; judging positive and negative current identification charging sections, and screening effective charging sections by using SOC change and duration; extracting health factors such as capacity change rate, voltage change rate, cumulative mileage, SOC statistical characteristics and temperature statistical characteristics, and screening data driving health factors with strong correlation by adopting a Pearson's correlation coefficient; a second-order RC equivalent circuit model is constructed, model parameters are dynamically identified through FFRLS, and equivalent circuit health factors are obtained; fusing the data-driven health factors and the equivalent circuit health factors into a comprehensive feature set; and constructing a GRU-Attention model, capturing a long-term and short-term dependency relationship of data by adopting the GRU, enhancing feature expression through Attention, and outputting the predicted health state of the lithium battery pack. The method achieves the high-precision estimation of the health state of the lithium battery pack, and is suitable for the intelligent health prediction of a new energy automobile battery management system and energy storage equipment.

The invention provides a digital twin unmanned aerial vehicle circuit state monitoring method and system, and the method comprises the steps: firstly collecting a partial discharge pulse sequence of an unmanned aerial vehicle switching power supply circuit, separating environment electromagnetic noise through polarization filtering operation, and extracting real discharge pulses to generate partial discharge fingerprint data; inputting the fingerprint data into a pre-established fault search tree model, judging the type of a capacitor or inductor component through a first-stage branch node, and matching a degradation mode such as capacitance attenuation or magnetic saturation through a second-stage branch node to determine the fault type; then, corresponding component parameters of the equivalent circuit model are dynamically updated in the digital twin body, and the circuit operation state change trend is simulated; and finally, according to the state change trend, predicting the residual effective working time of the fault component and outputting a monitoring result. According to the invention, the accuracy of service life evaluation of key components in a complex electromagnetic environment is improved.

The invention discloses a biconical antenna balun equivalent circuit modeling optimization method based on a multi-conductor transmission line, and belongs to the technical field of electromagnetic simulation. The method comprises the following steps: firstly, establishing a three-dimensional electromagnetic model of a biconical antenna balun based on a finite element method, and setting ports and defining boundary conditions in combination with an actual current transmission path; then, distribution parameters among conductors are extracted through a multi-conductor transmission line theory, and a Balun circuit topological structure is constructed; and finally, taking the antenna coefficient as an optimization target, carrying out iterative optimization on equivalent circuit element parameters by adopting a multi-target genetic algorithm, considering a plurality of optimization targets in a broadband range, and finally obtaining a high-precision equivalent circuit model. Through combination of electromagnetic simulation and an intelligent optimization algorithm, high-efficiency extraction of complex Balun structure distribution parameters and adaptive optimization of circuit parameters are realized, and the simulation precision of the biconical antenna is remarkably improved.

Disclosed in the present application are a method and apparatus for estimating the state of charge of a battery, and a device and a storage medium. The method comprises: by means of a Thevenin equivalent circuit model, constructing a Thevenin equivalent circuit state space model for a lithium battery; on the basis of a preset high-order polynomial, performing fitting on the state of charge and open-circuit voltage of the lithium battery, and determining a non-linear relationship curve between the state of charge and the open-circuit voltage; collecting real-time operating state data of the lithium battery, and on the basis of the real-time operating state data, using an extended Kalman filter algorithm to perform online parameter identification on the Thevenin equivalent circuit state space model, so as to obtain an estimated state variable value; and constructing an adaptive double-power sliding mode observer, and inputting the non-linear relationship curve and the estimated state variable value into the adaptive double-power sliding mode observer, so that the adaptive double-power sliding mode observer calculates an estimated state-of-charge value of the lithium battery in real time. Compared with the prior art, the technical solution of the present application can improve the accuracy of estimating the state of charge of a lithium battery.

The invention discloses a method for improving stability of a network-forming converter by considering voltage and phase transients, which solves the problem of over-current control blind areas existing at the initial stage of a fault and at the moment of clearing in a traditional single current limiting method and overcomes the defect that the stability is sharply deteriorated when a traditional strategy is used for coping with a composite fault. The method comprises the following steps: S1, obtaining a virtual synchronous machine swing equation under a synchronous rotating coordinate system and an equivalent circuit model under the action of a circular current limiter; and S2, obtaining a nonlinear relation between the output power and the power angle of the converter, and analyzing a transient stability domain of the converter during a fault period. And S3, obtaining a mixed current limiting strategy, deducing an equivalent circuit model corresponding to the strategy, and further obtaining an output power expression corresponding to the strategy. And S4, obtaining a power damping term acting on an active power control loop, further obtaining a synchronization stability improvement strategy, and deducing a closed-loop model describing the system at the moment.

The invention discloses an impedance remodeling method for a grid-connected converter, and relates to the field of fire safety, and the method comprises the steps: respectively recording a virtual impedance transfer function and a virtual admittance transfer function into a current inner loop universal controller structure under a d / q coordinate system, and obtaining a series virtual impedance control structure and a parallel virtual admittance control structure; the series virtual impedance control structure and the parallel virtual admittance control structure are subjected to time domain and frequency domain conversion to obtain a series virtual impedance Norton equivalent circuit and a parallel virtual admittance Norton equivalent circuit respectively; based on the influence of virtual impedance and virtual admittance on the converter, multiple compensation links are added in a control framework of the grid-connected converter, so that the harmonic voltage and harmonic current of a grid-connected point are reduced, and the converter operates more stably.