733 results about "Circuit models" patented technology

The invention belongs to the technical field of thermal circuit model construction, and particularly relates to a high-voltage power cable intermediate connection thermal circuit fault modeling analysis method and device, and the method comprises the steps: building a high-voltage power cable intermediate connection thermal circuit fault circuit model through analyzing a cable intermediate connection temperature inversion principle; the method comprises the following steps: establishing a geometric model for multi-physics field analysis of the intermediate connection of the high-voltage power cable by utilizing Comsol finite element simulation software, setting material parameters of each component, and setting field domain parameters; an electromagnetic field module is added, boundary conditions of electromagnetic field analysis are set, and a cable intermediate connection electromagnetic field simulation model is obtained; adding a solid heat transfer module to obtain a solid temperature field simulation model; obtaining an electromagnetic-thermal coupling model, and solving to obtain the temperature, current and loss of the cable middle connection wire core and the outer surface in different insulation states. According to the method, the cable intermediate connection fault problem can be found and predicted, and the reliability and the safety of the power cable are improved.

The invention relates to the technical field of battery state monitoring, and discloses a sightseeing vehicle battery state monitoring method, device and equipment and a storage medium, and the method comprises the steps: collecting the voltage, current and temperature data of a sightseeing vehicle battery, and carrying out the preprocessing, and obtaining a battery operation parameter data set; constructing a battery equivalent circuit model, and performing global and local two-stage optimization to obtain an optimal parameter set of the battery equivalent circuit model; constructing a state equation and an observation equation, and carrying out initialization setting on a covariance matrix of the triple forgetting factor adaptive extended Kalman filter to obtain a battery state observation model; priori state estimation is obtained through time updating operation, posterior state estimation is obtained through measurement updating operation, hierarchical estimation is carried out on the charge state and the polarization voltage of the battery, and the state characteristic quantity of the battery is obtained; according to the method, the reliability and the safety of the battery management system of the sightseeing vehicle are improved.

The invention relates to the technical field of battery model construction, in particular to a construction method and system of a lithium ion battery equivalent circuit model and a medium. The method comprises the following steps: collecting initial battery electrochemical parameters, obtaining ion migration characteristic data through charge density gradient decoupling, further reconstructing a polarization potential field to generate a lithium ion battery charge-discharge curve, performing potential migration analysis on the curve, mapping the curve into time domain charge mapping data, and calculating the time domain charge mapping data according to the time domain charge mapping data. Voltage distribution data are captured through transient voltage, circuit topology is reconstructed, circuit temperature distribution data are obtained, electric field-temperature field cross locking is carried out to determine a temperature influence coefficient, an initial equivalent circuit model is corrected based on the temperature influence coefficient, charging and discharging simulation is carried out on the corrected model, and aging factors are embedded. And finally generating an equivalent circuit model of the lithium ion battery. The method for constructing the equivalent circuit model of the lithium ion battery is more reliable and more intelligent.

The invention belongs to the technical field of battery management, and relates to a battery equivalent circuit model parameter identification method and system based on particle swarm optimization, and the method comprises the steps: obtaining the dynamic test data of a battery; an OCV-SOC relation is obtained; calculating a real-time SOC sequence and performing interpolation to obtain a search OCV sequence; defining a second-order RC equivalent circuit model; constructing an objective function based on an error between prediction of the OCV sequence and search of the OCV sequence; and searching an optimal model parameter by adopting a particle swarm optimization algorithm and taking minimization of the target function as a target. By optimizing the matching degree of predicting the OCV and searching the OCV instead of directly fitting the terminal voltage, the sensitivity and accuracy of parameter identification on the dynamic characteristics of the battery are improved, and efficient and accurate identification on the parameters of the second-order RC model is realized in combination with the global optimization capacity and robustness design of PSO (Particle Swarm Optimization).

The invention provides an electromagnetic compatibility test method and system for PCB design, a PCB comprises a schematic circuit diagram and a structural model, and the method comprises the following steps: extracting high-frequency signal characteristics in the schematic circuit diagram to obtain an electromagnetic simulation parameter set; performing multi-physical field coupling modeling according to the electromagnetic simulation parameter set and the structure model to obtain an electromagnetic field-circuit model; performing frequency-time domain hybrid excitation loading on the electromagnetic field-circuit model to obtain an electromagnetic noise distribution diagram; performing gradient descent optimization on layout parameters of the structure model according to the electromagnetic noise distribution diagram to obtain an anti-interference layout scheme; and performing multi-working-condition Monte Carlo simulation and residual error calibration on the anti-interference layout scheme to generate a correction guidance library.

The invention discloses a harmonic traceability method based on a harmonic power direction of an electric power system, which belongs to the technical field of electric power quality of the electric power system and comprises the following steps of: constructing matrixes of fundamental waves and harmonic signals, initializing active and reactive power deviation values of nodes, and adopting a decoupling algorithm combined with a Jacobian matrix iteration method to carry out harmonic traceability. And sequentially calculating the fundamental wave voltage and each harmonic current, and finally obtaining the power flow direction and judging the harmonic source attribute. When harmonic power flows from a load to a power grid, the node is identified as a harmonic source; and when the harmonic power flows to the load from the power grid, identifying the node as a harmonic receiving point. An equivalent circuit model is used for separating harmonic influences of a linear load and a non-linear load, and a real-time monitoring technology is combined to realize dynamic tracking and accurate positioning of a harmonic source. The method is low in calculation complexity, excellent in convergence performance and suitable for a modern power distribution network scene where distributed energy and power electronic equipment are widely connected, the harmonic suppression efficiency is remarkably improved, and the safety and stability of power grid operation are ensured.

The invention discloses a method and a device for improving positive and negative recognition accuracy of a test strip and a storage medium. The method comprises the following steps: acquiring image data of C-line and T-line areas of a test strip by using a multispectral camera; performing feature extraction and optimization processing on the acquired multispectral image; the abstraction detection process is a logic circuit model, and a node feature matrix is constructed; randomly injecting a fault into the model, simulating an environment problem, and generating a test vector; training a graph convolutional neural network model by using the failure response data, and adding cavity convolution; the trained model is applied to analyze real-time data, predict faults and evaluate color changes; if the detection is abnormal, accurately distinguishing red types by using a color difference matrix and time sequence analysis; and calculating the confidence coefficient based on the optimized features and the high-precision color information, and determining an object frame. By implementing the method provided by the invention, the problems of low accuracy, weak anti-interference capability and lack of effective fault simulation in the existing test strip detection technology can be solved.

The invention relates to the technical field of batteries, and discloses a battery charge state estimation method and device, equipment and a storage medium. The method comprises the following steps: constructing a fractional order equivalent circuit model of a to-be-tested battery; constructing a first state equation set according to the fractional order equivalent circuit model, and discretizing the first state equation set to obtain a second state equation set; performing parameter identification on the fractional order equivalent circuit model by adopting a particle swarm optimization algorithm; and estimating the state of charge of the to-be-tested battery by adopting a self-adaptive extended Kalman filtering algorithm according to the second state equation set after the parameters are identified. According to the method, the equivalent circuit model is constructed by adopting the fractional order model, the fractional order model can better reflect the nonlinear characteristic of the battery, so that the precision of the circuit model is improved, and on the basis of the established equivalent circuit model, the state of charge is estimated in combination with the adaptive fractional order extended Kalman filtering algorithm, so that the accuracy of the circuit model is improved. Therefore, the accuracy of state-of-charge estimation can be improved.

A method for estimating current-dependent non-linear equivalent circuit model (ECM) parameters of a battery may include measuring a battery voltage across terminals of the battery and a battery current drawn from the battery, modelling behavior of the battery with an impedance model having impedance model parameters, dynamically analyzing the battery current drawn from the battery by a load, dynamically determining safe operating limits for an augmented current for augmenting the current drawn by the load, based on analysis of the battery current and the safe operating limits, determining the augmented current, generating the augmented current to be drawn from the battery, and estimating the impedance model parameters when the augmented current is drawn from the battery.

The invention discloses a power transformer winding insulation state monitoring method, a power transformer winding insulation state monitoring device, power transformer winding insulation state monitoring equipment and a medium, and relates to the technical field of power system equipment state monitoring. And an improved particle swarm optimization algorithm is adopted to inversely calculate the insulation parameters of a plurality of windings of the transformer to the ground, so that the insulation state of each winding can be accurately evaluated. Compared with a traditional monitoring method, the method has the advantages that rich information contained in the common-mode leakage current can be fully utilized, the insulation degradation conditions of different windings can be accurately distinguished, more accurate insulation state evaluation is provided, and the safe operation level of the transformer is effectively improved. Moreover, multi-stage evaluation is carried out on the insulation state through a fuzzy comprehensive evaluation method, the insulation state can be comprehensively reflected, different severity degrees of the insulation state can be distinguished, the current state can be evaluated, the degradation trend can be predicted through dynamic indexes, and a scientific basis is provided for operation and maintenance decision making.

The invention provides a high-frequency circulating current calculation method for a motor simulator cascade coupling parallel structure, and the method comprises the following steps: building an equivalent decoupling circuit model of each branch in the cascade coupling parallel structure based on the voltage relation of each branch in the motor simulator cascade coupling parallel structure, wherein the equivalent decoupling circuit of each branch comprises an equivalent voltage source and an equivalent leakage inductor which are connected in series, and the equivalent leakage inductor is determined based on self-inductance and mutual inductance of a choking coil of each branch; a plurality of duty ratio intervals are divided between 0 and 1, and the number of the duty ratio intervals is equal to the number of the branches in the cascade coupling parallel structure; and using the equivalent decoupling circuit model to calculate the high-frequency circulation of each corresponding branch when the duty ratio of the modulation signal of the motor simulator is in each duty ratio interval. According to the method provided by the invention, the high-frequency circulating current of the cascade coupling parallel structure of the motor simulator can be accurately calculated, and effective support is provided for targeted design of a high-frequency circulating current suppression scheme.

The invention discloses a field self-adaptive retired battery health state estimation method based on an EIS. The method comprises the following steps: firstly, extracting electrochemical impedance spectroscopy data of a retired aged battery; and then a fractional order battery equivalent circuit model is constructed, and the characterization capability of dynamic degradation of an electrode interface is enhanced through a constant phase element. Fractional order battery equivalent circuit model parameters are extracted from electrochemical impedance spectroscopy data based on nonlinear least square fitting, Pearson correlation analysis is adopted to screen parameters having a significant relationship with SOH, then a recursive feature elimination method is used for further screening, and an optimal parameter subset strongly associated with the state of health is extracted from a high-dimensional parameter set. And finally, constructing a decommissioned battery state-of-health estimation method of a field adaptive method, modeling the influence of different operation conditions on battery aging through knowledge migration, and realizing cross-working-condition decommissioned battery state-of-health estimation with both physical interpretability and working condition robustness.

The invention relates to the related technical field of distribution transformer insulation aging, in particular to a frequency domain diagnosis method, system and device for distribution transformer insulation aging and a medium, and the method comprises the steps: carrying out the frequency response test of a to-be-tested transformer, and obtaining a first frequency response curve; performing a frequency response simulation test on a transformer equivalent circuit model pre-constructed based on the to-be-tested transformer to obtain a second frequency response curve; constructing a target function based on the deviation of the first frequency response curve and the second frequency response curve; taking element parameters in the equivalent circuit model of the transformer as position vectors, taking the objective function as a fitness function, and adopting a multi-objective particle swarm algorithm to solve the element parameters to obtain optimal values of the element parameters; respectively comparing the optimal values of the element parameters with corresponding normal values to obtain insulation aging degrees; according to the method, the insulation aging degree can be obtained by comparing the element parameters obtained through optimization with the normal unaged element parameters.

A system for estimating current-dependent non-linear equivalent circuit model (ECM) parameters of a battery may include measurement circuitry for measuring a battery voltage across terminals of the battery and a battery current drawn from the battery. The system may also include an impedance model having impedance model parameters, the impedance model for modelling behavior of the battery. The system may further include an augmented stimulus signal generator configured to dynamically analyze the battery current drawn from the battery by a load, based on analysis of the battery current, determine an augmented current for augmenting the current drawn by the load; and generate the augmented current to be drawn from the battery. The system may also include a battery model estimator for estimating the impedance model parameters when the augmented current is drawn from the battery.

The invention provides a lithium iron phosphate battery thermal runaway trend prediction method and system. The method comprises the steps that real-time operation data of a to-be-predicted lithium iron phosphate battery, initial estimated values of all parameters of an equivalent circuit model, a basic process noise covariance matrix and a basic measurement noise covariance matrix within a preset duration are acquired; determining an adjustment factor, and determining an adjusted process noise covariance matrix and an adjusted basic measurement noise covariance matrix based on the adjustment factor; optimizing the initial estimated value of each parameter of the equivalent circuit model corresponding to the lithium iron phosphate battery by using an extended Kalman filtering algorithm to obtain optimized ohm internal resistance, first-stage polarization internal resistance and second-stage polarization internal resistance; determining the temperature rise rate of the to-be-predicted lithium iron phosphate battery at the current moment t and the predicted temperature of the to-be-predicted lithium iron phosphate battery at the moment t + 1; and performing thermal runaway trend prediction on the lithium iron phosphate battery. According to the technical scheme provided by the invention, the reliability, the sensitivity and the timeliness of the prediction result are improved.

The invention discloses a battery energy storage health state detection and evaluation method and system, and relates to the technical field of battery energy storage state monitoring and evaluation, and the method comprises the steps: employing an SOC estimation method, combining an unscented Kalman filter and a Thevenin model to calculate the state of charge of a battery in real time, integrating the multi-dimensional feature data of the battery, inputting the data into an isolation forest algorithm, and carrying out the detection and evaluation of the energy storage health state of the battery. And carrying out deep anomaly detection on the battery sample with the abnormal frequency, and carrying out battery health state evaluation through a multi-stage anomaly detection result. SOC estimation is combined with an unscented Kalman filter, a Thevenin circuit model and an isolation forest algorithm to construct a self-adaptive and high-robustness multi-stage health assessment and anomaly detection system, the unscented Kalman filter performs high-precision prediction on nonlinear state transition, and the robustness of the health assessment and anomaly detection system is improved. The method effectively improves the estimation precision of the SOC under dynamic charging and discharging conditions and the accuracy of anomaly detection, and is suitable for monitoring and safety management of a battery system under complex environments and working conditions.

A method for estimating current-dependent non-linear equivalent circuit model (ECM) parameters of a battery may include measuring a battery voltage across terminals of the battery and a battery current drawn from the battery, deriving linear ECM parameters for modeling a linear ECM of the battery with multiple resistive-capacitive elements with different time constants to characterize temporal behaviors of the battery, continuously tracking an impedance for each of the multiple resistive-capacitive elements and an open circuit voltage of the battery, continuously monitoring the battery current to detect high current events, continuously tracking a deviation for each of the multiple resistive-capacitive elements during the high current events, and deriving non-linear online ECM parameters based on the linear ECM parameters and the deviations for the multiple resistive-capacitive elements during the high current events.

The invention relates to a photovoltaic system rapid power control method considering environmental parameter estimation. The method comprises the following steps: acquiring P-V curve segmentation and local maximum power point information under a local shadow condition by using improved global maximum power point tracking based on search-jump-judgment logic; in the global maximum power point tracking process, whether a trigger signal for executing environmental parameter estimation exists or not is monitored in real time, if yes, environmental parameter estimation is executed until the trigger signal disappears, and environmental parameters of the photovoltaic system are obtained through estimation; performing multi-peak power characteristic curve fitting based on a photovoltaic equivalent circuit model based on the P-V curve segmentation and local maximum power point information and the environmental parameters of the photovoltaic system; and determining a photovoltaic working point based on a given power reference value and the multi-peak power characteristic curve to realize rapid power control of the photovoltaic system. Compared with the prior art, the method has the advantages that no additional sensor is needed, and rapid and flexible tracking of photovoltaic power can be realized.

The invention belongs to the technical field of battery state estimation, and particularly relates to a battery SOC estimation method fusing an AEKF algorithm and an LSTM neural network, and the method comprises the following steps: 1, selecting an experiment object, and building an equivalent circuit model; and 2, carrying out parameter identification on the battery by adopting an AFFRLS algorithm. According to the battery SOC estimation method fusing the AEKF algorithm and the LSTM neural network, according to the power battery SOC prediction method of the small-power electric vehicle based on the AEKF-LSTM fusion algorithm, the maximum estimation error of the AEKF algorithm under the actual working condition is about 0.04, and the maximum estimation error of the AEKF-LSTM fusion algorithm is about 0.02. Therefore, compared with a single AEKF algorithm, the method for predicting the SOC of the power battery of the small-power electric vehicle based on the AEKF-LSTM fusion algorithm has the advantage that the estimation precision is obviously improved. Meanwhile, it is verified that the fusion algorithm can be used for SOC prediction of irregular and large-fluctuation battery data.

The invention provides an accelerated simulation solving method and system for a controllable self-recovery energy dissipation device, and the method comprises the steps: S1, enabling an inductance element between a nonlinear network and a linear network in a hybrid cascade DC power transmission system to be equivalent to a short transmission line, and building circuit models for the linear network and the nonlinear network respectively; s2, obtaining the value of the current controlled voltage source based on the node voltage of the previous simulation time step of the linear and nonlinear networks, the value of the controlled voltage source and the information interaction format; s3, node voltage solving is carried out based on the value of the controlled voltage source of the current simulation time step to obtain the node voltage of the current simulation time step, if the number of iterations is met, the operation is stopped, and otherwise, the step S2 is executed; the nonlinear network comprises a controllable self-recovery energy dissipation device; according to the invention, the energy dissipation device and the linear main circuit in the circuit system are decoupled in a sub-network manner, the calculation amount is reduced, and the iterative algorithm is used for solving, so that the high-efficiency and high-precision simulation of a nonlinear network and a linear network is ensured.

The invention discloses a relaxation time distribution-based hydrogen fuel cell equivalent circuit model establishment method, and belongs to the technical field of hydrogen fuel cells. The method comprises the following steps: acquiring full-band impedance data of the hydrogen fuel cell; performing relaxation time distribution analysis on the full-band impedance data to obtain a relaxation time relation spectrogram; identifying and constructing an initial equivalent circuit model based on characteristic peaks of different frequency bands in the relation spectrogram; the characteristic peaks at different frequency bands are used for representing different electrochemical characteristic processes of the hydrogen fuel cell; and according to the full-band impedance data and the initial equivalent circuit model, performing model parameter adjustment, and based on the adjusted model parameters, obtaining an equivalent circuit model constructed for the hydrogen fuel cell. According to the method, the high-precision and reasonable equivalent circuit model can be constructed.

Embodiments of the present application provide a verification system, method, device, medium and program, the verification system comprising: a test excitation generation module for generating a test excitation, the test excitation at least comprising serial data with clock jitter; the CDR circuit model is used for carrying out recovery processing on the input serial data and outputting a recovery result to a next-stage circuit model; the CDR jitter compensation device is used for detecting clock jitter deviation between input and output of the CDR circuit model; determining a control parameter according to the clock jitter deviation; the control parameters are fed back to the test excitation generation module; wherein the control parameter is used for adjusting the clock jitter size of the serial data generated by the test excitation generation module, so as to correct the clock jitter introduced by the CDR circuit model during the recovery processing of the serial data. According to the verification system provided by the embodiment of the invention, the clock jitter can be corrected.

The invention relates to the technical field of wireless power transmission, and particularly discloses a method for calculating loss of a magnetic coupling mechanism of a wireless power transmission system, which comprises the following steps of: firstly, establishing a circuit model of the system and determining system parameters; then establishing a coupling mechanism loss model, namely calculating skin loss of the primary and secondary coils based on current of the primary and secondary coils, coil parameters and system working frequency, and calculating proximity loss of the primary and secondary coils based on magnetic field intensity (obtained through simulation) of the primary and secondary coils, the coil parameters and the system working frequency; calculating the loss of the primary and secondary side magnetic cores based on the magnetic induction intensity (obtained through simulation) of the primary and secondary side magnetic cores, the magnetic core parameters and the system working frequency; and calculating the loss of the primary and secondary magnetic shielding plate based on the parameters of the primary and secondary magnetic shielding plate and the magnetic field intensity (obtained through simulation) of the surface. The loss of the coupling mechanism is calculated through finite element simulation software and compared with the actual measurement efficiency of an actual system, and the simulation result conforms to the reality.

The invention provides an integrated circuit model verification method and system, computer equipment and a storage medium. The method comprises the steps that parameters in a model library are analyzed through a script, and model parameters needed by verification are automatically extracted; a standard configuration file format is obtained, the model parameters are loaded into a standard configuration file, and a simulation configuration file is generated; obtaining netlist file formats required by different simulators, and generating netlist files which comprise output instructions and are adaptive to different simulators in batches according to the simulation configuration file; calling each simulator to execute the corresponding netlist file for simulation, and outputting an intermediate file; analyzing the numerical data in the intermediate file, and generating a standard format file; and comparing the standard format files generated by different simulators to obtain a verification result. According to the scheme, batch parameter configuration, netlist generation, simulation execution and result processing of the integrated circuit model can be realized, so that the model verification efficiency is improved.

The invention discloses a new energy automobile battery monitoring method and system, and relates to the technical field of new energy automobile battery monitoring, and the method comprises the steps: collecting battery operation data, initializing a population through a Halton sequence, executing preliminary VMD decomposition, calculating a Hilbert envelope, calculating an envelope entropy, and initializing a sparrow search algorithm HLSSA parameter and population classification. Updating the three populations, integrating and updating the populations, selecting cross individual pairs, executing Laplacian cross perturbation, outputting an optimal parameter group, executing final VMD decomposition, outputting an iteratively updated modal component, outputting a statistical feature vector, generating an Nyquist graph, fitting a Randles circuit model, performing feature screening, outputting an EIS feature set, and integrating the feature vector; according to the method, an SVR model is constructed to predict SOH and SOC values, VMD decomposition and envelope entropy feature analysis are used, the accuracy of feature extraction is improved, and through combination of Halton sequence initialization and sparrow search algorithm HLSSA optimization, the precision of battery health state prediction is improved.

The invention discloses an energy storage valve simulation analysis method and device, electronic equipment and a storage medium, and the method comprises the steps: generating a through-flow loop structure model of an energy storage valve sub-module, extracting stray parameters of the through-flow loop structure model, obtaining a short-circuit electrical parameter value of a circuit model based on the stray parameters and the circuit model of the energy storage valve sub-module, and obtaining a short-circuit electrical parameter value of the circuit model; and performing force simulation on the conductor parts based on the short-circuit electrical parameter values to obtain a force simulation analysis result, so that force simulation of the conductor parts in the through-flow loop structure model can be realized, namely simulation analysis of the energy storage valve can be realized, and electric power generated by each conductor part where the through-flow loop is located can be simulated under the condition that the energy storage valve is in a short-circuit fault. According to the force simulation analysis result, reason analysis and evaluation can be carried out, and reference is provided for optimizing the structural design of the energy storage valve sub-module.

The invention discloses a common-mode electromagnetic interference modeling and suppression method for a matrix converter, and the method comprehensively considers high-frequency parameters and topological characteristics, builds a conduction CM EMI equivalent circuit model of the matrix converter, completes the impedance network fitting of key elements and the extraction of high-frequency parasitic parameters, and achieves the modeling and suppression of the common-mode electromagnetic interference of the matrix converter. The precision of the CM EMI model of the matrix converter is improved, and the analysis of the CM EMI characteristics of the matrix converter is simplified. According to the common-mode electromagnetic interference suppression method for the matrix converter, CM EMI characteristics of the matrix converter are analyzed, a low-attenuation loop in the converter is constructed by adopting a method of combining a neutral line leading-back type structure and increasing output filter capacitor neutral-point-to-ground parasitic capacitance, the propagation proportion of noise in a linear impedance stabilization network measurement branch is reduced, and the measurement accuracy of the common-mode electromagnetic interference suppression method for the matrix converter is improved. And effective suppression of low-cost CM EMI noise is realized on the premise of not depending on an input EMI filter.

The invention belongs to the field of single-flow zinc-nickel battery model establishment and parameter identification, and particularly relates to a construction method of an equivalent circuit model considering the shelving time of a single-flow zinc-nickel battery, which comprises the following steps of: establishing a second-order RC equivalent circuit model; adding a resistor and a single-pole double-throw switch on the second-order RC equivalent circuit model to form a state switching equivalent circuit model; when the load current is not zero, the battery is in a working state, and a GrGWO algorithm is adopted to identify parameters of the second-order RC equivalent circuit model; and when the load current is 0, the battery is in a shelving state, the single-pole double-throw switch acts, the circuit structure is changed, and parameters of the state switching equivalent circuit model are identified by adopting an MPA algorithm. The characteristic that when the single-liquid-flow zinc-nickel battery is shelved, the time constant can change along with the increase of shelving time is considered, so that the model can better track the change of the terminal voltage of the single-liquid-flow zinc-nickel battery under a complex working condition, and the accuracy of the model is improved.

The invention discloses a modeling method of a radio frequency MOS (Metal Oxide Semiconductor) device, and relates to the technical field of MOS device modeling. Electromagnetic simulation and thermal field simulation are combined, a dynamic parasitic parameter library is established, parasitic effects under complex working conditions are described, the dynamic parasitic parameter library is taken as a core basis, the dynamic response capability of a model is remarkably improved, and the modeling efficiency of the radio frequency MOS device is improved. Dynamic parasitic parameters are introduced into a small-signal equivalent circuit model, dynamic changes of the parasitic parameters are explicitly embodied, a partition modeling method is introduced, dynamic behaviors of a grid electrode, a source electrode and a drain electrode are refined into independent contributions, local dynamic characteristics of the radio frequency MOS device can be described more accurately, modeling precision is enhanced, large-signal excitation and nonlinear polynomial description are introduced, and the dynamic characteristics of the radio frequency MOS device can be described more accurately. The method comprises the steps of capturing nonlinear behaviors under a high-power condition, establishing a unified behavior model from linearity to nonlinearity, accurately describing high-order nonlinearity by utilizing a Volterra series method, and solving key problems of signal frequency aliasing and dynamic distortion in nonlinear analysis in combination with dynamic parasitic parameters.

The invention discloses a modeling method and system for a vehicle network field circuit coupling model under a contact line short-circuit working condition, and relates to the technical field of modeling, and the method comprises the following steps: constructing a short-circuit arc equivalent model under the contact line short-circuit working condition based on an isolation switch equivalent model, one end of the short-circuit arc equivalent model is connected with a contact line in sliding connection with a pantograph in the chain type lumped tau-shaped network model through a switch element, the other end of the short-circuit arc equivalent model is connected with a steel rail in the chain type lumped tau-shaped network model, and a vehicle network circuit model under the contact line short-circuit working condition is obtained; and taking the short-circuit arc current at any short-circuit phase obtained through simulation of the vehicle network circuit model as a current excitation source of the three-dimensional model, and obtaining a vehicle network field model under the contact line short-circuit working condition. The rise rate, peak value and attenuation process of the short-circuit current can be accurately simulated by adding the short-circuit arc, the arc voltage drop is reflected, and the authenticity and practicability of simulation are remarkably improved.