854 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.

The invention belongs to the technical field of energy management of hybrid power systems, and discloses a quantum strategy learning energy management method and system for a multi-stack fuel cell hybrid power system, and the method comprises the steps: building a multi-stack fuel cell hybrid power system model which comprises a fuel cell power model, a lithium battery equivalent circuit model and power balance; constructing a quantum hybrid neural network, interacting with the established hybrid power system environment, distributing output power of different power sources, and constructing a state-action-reward set; the strategy is evaluated and updated on the basis of the collected state-action-reward data set, and then the energy management strategy is optimized. By fusing the variable component sub-circuit and the traditional neural network, efficient operation of the fuel cell system is ensured while the state of charge of the lithium battery is maintained in an ideal interval; and the gradient of the quantum circuit parameters is accurately calculated by using a parameter transfer rule, so that the optimization process of the quantum strategy learning energy management strategy is more accurate and efficient.

The invention provides a rapid modeling simulation method based on a time domain hybrid finite element method and a circuit simulator SPICE. The rapid modeling simulation method is used for analyzing transient linear / nonlinear and passive / active complex microwave network circuit models on a PCB. The method comprises the following steps of: constructing an electromagnetic module of a microwave network circuit in computer aided design software, writing an SPICE netlist of the circuit module, and realizing interaction between the electromagnetic module and the circuit module through voltage and current defined on a lumped port, so as to obtain a complete circuit structure; in the electromagnetic part, a modal order reduction technology based on a second-order Arnoldi algorithm is adopted to reduce the order of a wave equation to a low-dimensional Krylov subspace for solving, and the data interaction process of the electromagnetic part and the circuit part in each time step length is obviously accelerated; in the time domain hybrid finite element method, the tree-cotree technology is adopted to overcome the problem of low-frequency breakdown or high-density breakdown occurring in the time domain finite element method; a circuit simulator SPICE enables a joint simulation algorithm to be powerful, and a complex multi-port circuit can be simulated.

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.

Disclosed are a quick simulation and optimization method and system for analog circuits. Aiming at a problem that a customized circuit model is difficultly modeled in a design process of the analog circuit, and the problem of a low circuit design efficiency caused by a slow electromagnetic field simulation speed, the invention proposes to firstly construct a device library, build a circuit and interconnect an AI network to obtain a comprehensive network parameter of the AI network; the comprehensive network parameter in a simulation process is compared with a network parameter target of an analog circuit, and an circuit layout of the analog circuit corresponding to the AI network is output to a three-dimensional full-wave electromagnetic field simulation tool for simulation and verification when requirements are met.

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 discloses a method for modeling an all-vanadium redox flow battery and improving the coulombic efficiency of the battery, aiming at the composition and principle of VRB, a circuit model comprising electrochemistry, fluid mechanics, temperature, bypass current and vanadium battery multi-stack equivalent loss is established, and the influence of pumping loss and bypass current in an all-vanadium redox flow battery pipeline system on the vanadium battery is explored. By establishing the relation between the pumping loss and the pumping loss current, a bypass current model and a multi-stack series vanadium battery equivalent loss circuit model, all the models are converted into a whole, the kernel mechanism of the vanadium battery considering the dynamic response is elaborated, and the dynamic response of the vanadium battery is analyzed according to key factors involved in modeling research of the VRB, including the pumping loss and the bypass current. And how the factors comprehensively influence the performance and the efficiency of the battery is elaborated, and an idea is provided for pipeline design and improvement of the energy efficiency of the battery for manufacturers.

The invention proposes a circuit breaker power module layout optimization method and system based on multi-chip current sharing, and relates to the technical field of power electronics, and the method comprises the steps: collecting parasitic parameters of a circuit breaker power module, and constructing a first switch transient circuit model according to the parasitic parameters; constructing a conduction transient process circuit based on the first switch transient circuit model and the conduction transient characteristics; performing current equalization on the conducted transient process circuit according to the common-source inductance compensation function so as to perform state updating on the conducted transient process circuit, and obtaining a second switch transient circuit model corresponding to the conducted transient process circuit after state updating; extracting a parasitic inductance parameter in the second switch transient circuit model by adopting an ANSYS Q3D simulation tool, and performing multiple iterative optimization on the copper layer shape and the copper layer size of each power tube in the second switch transient circuit model through finite element simulation according to the common-source inductance compensation function and the parasitic inductance parameter; and obtaining an optimized layout scheme of the circuit breaker power module. According to the invention, the problem of local overload caused by non-uniform current distribution can be avoided, and the current sharing degree of the device under the condition that multiple chips are connected in parallel can be improved.

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 transformer hollow winding model building method and system based on a multi-function PEEC method. The method comprises the steps that discretization processing is conducted on a target transformer winding, and the target transformer winding is divided into a plurality of volume units and area units; according to geometric parameters of the volume units and the area units, partial inductance matrixes, potential coefficient matrixes and resistance matrixes among all the grids are calculated; according to geometric characteristics of a target transformer winding, different improved approximation methods are adopted to calculate specific numerical values of the partial inductance matrix and the potential coefficient matrix; and establishing a target transformer winding equivalent circuit model according to the partial inductance matrix, the potential coefficient matrix and the resistance matrix of which the specific numerical values are calculated. The method not only improves the accuracy and calculation efficiency of the model, but also simplifies the model building process, improves the performance prediction capability of the transformer, and has high adaptability.