413 results about "Circuit models" patented technology

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 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.

The invention provides a lithium battery parameter online identification method based on dynamic weight particle swarm optimization, and relates to the field of power lithium battery model parameter identification. According to the method, a lithium battery equivalent circuit model based on a second-order RC network is established, and a state-space equation is derived according to the Kirchhoff's current law and the voltage law; a discrete output model is obtained through Laplace transformation and discretization processing; constructing a recursive least square parameter updater with a forgetting factor, and jointly optimizing an initial parameter vector of the forgetting factor recursive least square and the forgetting factor by adopting a dynamic weight particle swarm optimization algorithm; and based on the optimized initial parameter vector and the forgetting factor, performing recursive least square updating with the forgetting factor, performing online identification on model parameters, and reversely deducing an equivalent parameter value in an original circuit. According to the method, the parameter identification precision can be remarkably improved, and the problem that data saturation parameter convergence is slow in a traditional recursive least square method is solved.

The invention relates to the technical field of data processing, and particularly discloses a matrix pre-sequencing method and system based on reinforcement learning and a storage medium, which are used for modeling a matrix pre-sequencing problem into a sequence decision process, and learning an optimal sequencing strategy by utilizing a reinforcement learning agent through interaction with a matrix environment. The state of the agent is defined by the structural features of the matrix, and the action corresponds to the selection of nodes that have not been eliminated. The reward function aims at minimizing the ratio of the number of filling elements to the matrix dimension in the calculation process. The performance of the method is compared with that of a traditional heuristic algorithm in an experiment, and the result shows that in specific test cases such as a large-scale circuit model, the pre-sequencing method based on reinforcement learning has the advantages in the aspects of reducing the number of filling elements and shortening the calculation time.

A converter station AC filter group circuit breaker abnormal arcing modeling analysis method comprises the following steps: firstly, carrying out time mark alignment, amplitude calibration and filtering de-noising on wave recording signals such as AC bus voltage and filter branch current to obtain high-quality input data; then, combining a primary wiring diagram, enabling an alternating current system to be equivalent to an ideal power supply and series impedance, enabling circuit breaker arcing to be equivalent to arc resistance changing along with time, and constructing an equivalent circuit model comprising the power supply, the impedance, a capacitor, an electric reactor and dynamic arc resistance; establishing a state space equation according to a voltage and current constraint relation, and performing time domain solution by adopting a two-step two-order or three-order diagonal implicit Runge-Kutta method to obtain voltage and current responses of the whole process of the fault; on this basis, the arc resistance change is inversed according to the ratio of arc voltage to current, the current zero passage is identified through the resistance symbol change at adjacent moments, and the zero passage section is smoothed; and finally, the inversion result is verified again by means of the simplified equivalent model.

The embodiment of the invention provides a parameter updating method for a battery circuit model, a vehicle and a storage medium, and the method comprises the steps: obtaining a current state parameter and a current operation condition of a target battery, the current operation condition being used for representing the operation stability degree of the target battery; a battery circuit model corresponding to the target battery is used for predicting and obtaining predicted state parameters of the target battery, and the battery circuit model is used for simulating the electrochemical process of the target battery in the charging and discharging process; based on the current operation condition, determining a parameter adjustment factor of the battery circuit model, the parameter adjustment factor being used for quantifying an influence of the current operation condition on a model parameter corresponding to the battery circuit model; and based on the parameter adjustment factor, the current state parameter and the predicted state parameter, updating the current model parameter of the battery circuit model to obtain a target model parameter of the battery circuit model. According to the invention, the technical problem of low safety of the power battery in the prior art is solved.

The invention belongs to the technical field related to operation control of a power system, and provides a transient instability judgment method and system of a network-building type converter in order to solve the problem that an existing transient instability judgment method of the network-building type converter is prone to causing maloperation or missed judgment of a control strategy, and a nonlinear equivalent circuit model of the network-building type converter is established. Calculating transient total energy and critical instability energy of the system in real time, and adaptively switching a control mode according to the magnitude relationship of the transient total energy and the critical instability energy; during normal operation, an original control strategy of the virtual synchronous machine is maintained, and oscillation is suppressed by using the damping characteristic of the virtual synchronous machine, so that the voltage and frequency supporting capacity of a power grid is maximized; and when an instability risk is detected, entering a fault ride-through mode to realize rapid and accurate identification and control of the instability risk.

The invention provides an SOC estimation method and device for a lithium battery, electronic equipment and a storage medium, and belongs to the technical field of battery management, and the method comprises the steps: obtaining a current model parameter of a pre-constructed battery equivalent circuit model and an SOC estimation value at a previous moment; predicting the terminal voltage of the lithium battery at the current moment based on the current model parameter, the current of the lithium battery at the current moment and the SOC estimated value at the previous moment; and estimating the SOC at the current moment based on the SOC estimated value at the previous moment by adopting an SOC estimation algorithm, and correcting the SOC estimated at the current moment based on the deviation between the predicted terminal voltage and the terminal voltage actually measured at the current moment to obtain the optimal SOC estimated value at the current moment. According to the method, the dynamically updated battery equivalent circuit model parameters are introduced, so that the model can reflect the change of the impedance characteristic of the battery in real time, the terminal voltage prediction error is remarkably reduced, and the SOC estimation precision is improved.

The invention discloses a GaN HEMT (High Electron Mobility Transistor) driving method for quantitative suppression of false triggering oscillation. The method comprises the following steps: calculating turn-off transient process time; establishing a false triggering oscillation equivalent circuit model, deducing an oscillation system characteristic equation, performing root locus analysis on the oscillation system characteristic equation, and delimiting a design range of RC parameters with the best oscillation suppression effect; detecting a turn-off signal of the GaN HEMT through a detection circuit, and outputting a trigger signal of which the length is equal to turn-off transient process time; a trigger signal is input into the driving circuit to form a low-impedance grid branch, so that the turn-off process of the GaN HEMT is accelerated; and in response to completion of turn-off of the GaN HEMT, the trigger signal is controlled to drop to a low level, an RC buffer circuit is formed, and false trigger oscillation after the device is turned off is quantitatively suppressed. According to the invention, acceleration of the turn-off process of the GaN HEMT is realized, false trigger oscillation is quantitatively suppressed, the turn-off speed of the device is not influenced, and the gate impedance is reduced in the turn-off process of the device.

The invention discloses a modeling method of a simulation model, a storage medium and a terminal. The method comprises the following steps: acquiring an initial simulation model of a semiconductor device to be modeled; according to the initial simulation model, fitting a drain current-grid voltage characteristic curve of a sub-threshold region of the semiconductor device to be modeled; judging whether the to-be-modeled semiconductor device has subsurface leakage current in a subthreshold region of the drain current-grid voltage characteristic curve or not; if the secondary surface leakage current exists, establishing a sub-circuit model representing the secondary surface leakage current; integrating the sub-circuit model and the initial simulation model; and according to the integrated initial simulation model, fitting the drain current-grid voltage characteristic curve of the sub-threshold region until the fitting curve of the drain current-grid voltage characteristic curve converges, and obtaining a simulation model of the semiconductor device to be modeled. According to the modeling method, the secondary surface leakage current can be accurately modeled, and the simulation precision and accuracy of an integrated circuit simulation model are improved.

The invention discloses a method for estimating the capacity of a lithium battery based on an equivalent circuit model by using cloud data. The method comprises the following steps: acquiring a plurality of related data of a real vehicle cloud lithium battery in an actual charging and discharging process; screening out a plurality of sections of charging data fragments containing identifiable characteristics according to screening conditions; carrying out simple calculation and preprocessing on the obtained data; establishing a lithium battery equivalent circuit model, and determining input parameters of the model and battery parameters to be estimated; optimizing and identifying the to-be-identified parameters of the established equivalent circuit model by adopting a particle swarm optimization algorithm; carrying out optimization estimation by taking the capacity, the initial SOC and the internal resistance of the lithium battery as to-be-identified parameters; and finally, a root-mean-square error between the simulation voltage of the model and the collected actual voltage is used as a fitness function to judge an optimization result, the estimated capacity of the lithium battery is obtained, multi-section data joint fitting is adopted, contingency is eliminated, and the reliability of capacity estimation is improved.

The invention provides a transformer heavy overload evaluation analysis method and device, and the method comprises the steps: building a thermal circuit model of load-induced heat point temperature rise of a transformer according to the heating power, equivalent heat capacity and equivalent heat resistance of an internal winding of the transformer, and load-induced heat top oil temperature rise of the transformer; converting a heat flow source in the heat circuit model into a hot pressure source based on the Thevenin theorem, constructing an equivalent heat circuit model of the heat circuit model, and calculating load heating hot spot temperature rise of the transformer under different load rates according to the equivalent heat circuit model; according to the historical environment heating temperatures of the transformer under different load rates, obtaining predicted environment heating temperatures of the transformer under different load rates; and obtaining winding hot-spot temperatures of the transformer under different load rates according to the load heating hot-spot temperature rise and the predicted environment heating temperature of the transformer under the same load rate. According to the invention, the thermal state sensing precision of the transformer under the dynamic load is improved.

The invention discloses a virtual impedance compensation method for permanent magnet synchronous generator constant admittance modeling, and relates to the technical field of electromagnetic transient modeling of permanent magnet synchronous generators, and the method comprises the steps: firstly, carrying out the discretization of a permanent magnet synchronous generator model; secondly, decomposing the equivalent resistance matrix into a time-invariant part and a time-varying part; then, virtual impedance is added to the q axis of the generator model; thirdly, constructing a generator constant admittance model; thirdly, a converter accompanying discrete circuit model is integrated, a complete permanent magnet synchronous generator constant admittance model is formed, and a node admittance equation is established based on the Kirchhoff's current law; and finally, executing electromagnetic transient simulation. According to the method, constant admittance modeling is achieved based on virtual impedance compensation, the requirement for real-time inversion of a time-varying admittance matrix is eliminated, simulation calculation resource consumption is remarkably reduced, small errors are kept under various working conditions, and efficient simulation of a large-scale permanent magnet synchronous generator system is supported.

The invention relates to the technical field of industrial big data and unmanned aerial vehicle power management, in particular to an unmanned aerial vehicle power supply management system based on industrial big data. An ideal reference reconstruction module, a fault simulation injection module, a coupling judgment module and a feedback execution module are included; the system reconstructs a noise-free reference voltage curve by using dynamics and a battery equivalent circuit model through collecting an operation instruction, an attitude and environment data, and synchronously superposes fault features to generate a simulation curve; the core of the method is to calculate the waveform similarity between a real observation difference sequence and a theoretical obstacle-containing difference sequence, and execute threshold determination and strategy adjustment according to the waveform similarity. According to the method, conversion from static threshold judgment to dynamic form matching is realized, transient voltage drop caused by normal maneuvering can be automatically counteracted, and the problem of false alarm caused by incapability of distinguishing dynamic response and circuit failure is solved.

The invention relates to the technical field of design optimization, in particular to a control design optimization method and system for a permanent magnet synchronous motor. The method comprises the following steps: obtaining and measuring a stator three-phase voltage value and a current value of the PMSM and a motor rotating speed in real time; constructing a d-q axis motor equivalent circuit model, and calculating an available boundary curve of the voltage of the weakening area by combining the three-phase voltage value of the stator and the rotating speed of the motor; determining a dynamic safety margin coefficient of a weakening area voltage-current working area based on the weakening area voltage available boundary curve; judging the motor rotating speed of the permanent magnet synchronous motor; by introducing voltage-current working area modeling and a dynamic safety margin coefficient, accurate current control and adaptive inverter compensation of the PMSM in a weak magnetic area are realized, and the problems of poor stability, insufficient voltage margin and incomplete compensation in traditional high-speed control are solved.

The invention belongs to the technical field of glass industry, and relates to a method for calculating distribution of electrical parameters of molten glass in an advanced-generation substrate glass gas-electric kiln. Comprising the following steps: setting process boundary conditions of kiln operation; simulating an operation state of the kiln under a set boundary condition by adopting simulation software, equally dividing molten glass in the kiln into a plurality of layers along a vertical height direction, and acquiring temperature distribution data of each layer; based on the temperature distribution data of each layer, determining the resistivity corresponding to each layer of molten glass according to a temperature-resistivity fitting relationship; calculating the resistance of each layer of molten glass based on the resistivity corresponding to each layer of molten glass and in combination with the electrode spacing and sectional area corresponding to each layer of molten glass; and constructing each layer of molten glass into a parallel circuit model, and calculating the current and power of each layer of molten glass according to the loading voltage and resistance. According to the method, accurate quantification and optimal control of the electric heating parameters of the molten glass in the kiln are realized, and the method is suitable for production process optimization of high-generation large-size substrate glass.

The invention relates to a method for calculating the power-on and power-off delay time performance of an electromagnetic valve, and the method comprises the following steps: obtaining the mass of a valve element of the electromagnetic valve, the spring stiffness and coil resistance data; establishing an electromagnetic valve equivalent circuit model, and listing a current equation; establishing an electromagnetic valve magnetic circuit mathematical model, and listing a magnetic field equation set; establishing an electromagnetic valve flow field mathematical model, and listing a flow field equation set; establishing a kinematic model of the electromagnetic valve, and listing a kinematic equation; using a finite element method to obtain a valve core electromagnetic force-displacement-current data table and a coil inductance-displacement-current data table; a finite element method is used for obtaining a valve element aerodynamic force-displacement data table; and obtaining the power-on and power-off delay time through data analysis processing and solving of the partial differential equation set. According to the method, prediction of the opening and closing delay response time of the electromagnetic valve is more accurate, visual adjustment in the simulation process is achieved, and the time for obtaining the response time of the electromagnetic valve and the test cost are greatly reduced while the preset precision requirement is met.

The invention discloses an integrated circuit electrical characteristic simulation method and device, a terminal and a storage medium, and the method comprises the steps: obtaining a to-be-simulated integrated circuit model, carrying out the mesh generation of the to-be-simulated integrated circuit model, so as to obtain an integrated circuit mesh data set composed of a plurality of mesh units, constructing a corresponding charge basis function and a current basis function based on the grid units; step-by-step fusion updating of the charge primary function is realized by taking the charge primary function as a fusion object, and meanwhile, corresponding fusion updating is performed on the current primary function in a geometric mapping mode; and after all fusion updating is completed, obtaining an integrated circuit primary function data set, and performing electrical characteristic simulation on the to-be-simulated integrated circuit based on the integrated circuit primary function data set. According to the method, fast updating and low-order representation of a complex coupling capacitance matrix are achieved, compared with a traditional post-order reduction method, the theoretical complexity is reduced from O (n3) to O (n), and meanwhile the model order reduction efficiency is greatly improved while the model precision and the order reduction effect are guaranteed.

The application discloses a method for realizing a conservative charge-controlled memcapacitive hyperchaotic circuit with multiple coexisting attractors. First, a six-dimensional conservative memcapacitive circuit model is constructed by a charge-controlled memcapacitive device, and the memcapacitive characteristics are verified. Then, the balance point and dissipation are used to verify the conservativeness. By changing the system parameters and initial conditions, a larger Lyapunov exponent can be obtained, and it is found that the internal parameter e of the circuit can not only cause the circuit to exhibit complex transient chaotic phenomena, but also has large-scale range chaotic characteristics. The attractor basin, coexisting attractors and complexity reflect the extreme multistability and complex nonlinear dynamic behavior of the circuit. In addition, the initial offset boosting behavior is also found. The application combines the FPGA technology to design a digital conservative charge-controlled memcapacitive hyperchaotic circuit model, and the hardware simulation result is consistent with the numerical calculation result, thereby providing a new idea for the digital realization of a nonlinear storage system.

The invention provides a design method of a fragmented solar cell, the fragmented solar cell and a preparation method thereof, and the design method comprises the following steps: building a circuit model: based on a double-diode model, additionally arranging a first composite branch used for representing the recombination behavior of the fragmented edge of the cell, and a second composite branch used for representing the recombination behavior of the non-fragmented edge of the cell, forming a circuit model of the slice solar cell; model operation and parameter extraction; and establishing an association relationship: establishing the association relationship between the size parameters of the battery splinter edge and the non-splinter edge and the battery performance, wherein the size parameters comprise the width of a splinter isolation region, the width of a non-splinter isolation region, the distance between the splinter edge and the electrode closest to the parallel grid line, and the distance between the non-splinter edge and the electrode closest to the parallel grid line. According to the invention, by constructing the circuit model containing the composite branch with the split edge and the non-split edge, systematic theoretical support is provided for optimization of critical dimensions such as the grid line electrode spacing and the isolation area width, and stable improvement of the power of the module is realized.

The invention provides a power distribution network analysis method and device based on multiple voltage grades, a medium and a product, and relates to the technical field of power grid analysis. The method comprises the following steps: acquiring operation data of the power distribution network, wherein the operation data comprises topological structures corresponding to a plurality of voltage grades in the power distribution network, static parameters of power grid equipment and operation data of the power grid equipment; according to the operation data, constructing a short-circuit value circuit model and a load flow calculation model of a cross-voltage grade; according to the operation data, a power flow calculation model is adopted to carry out iteration processing on the power flow data, and target power flow data are obtained, and the target power flow data comprise active power and reactive power flow of each line in the power distribution network and voltage amplitude and phase angle of each node; and carrying out power flow condition simulation and short circuit analysis on the power distribution network based on the operation data, the target power flow data and the short circuit value circuit model to obtain protection evaluation information of the power distribution network. The method is used for improving the accuracy and efficiency of power distribution network analysis.

A system and method for enhancing reliability and trustworthiness in cyber-physical systems using artificial intelligence are disclosed. The system comprises a plurality of sensors for collecting real-time data, a data processing unit that analyzes the data using machine learning models to identify patterns and anomalies, and a communication interface for transmitting recommendations based on the analysis. The machine learning models include an adversarial random forest (ARF) model and a probabilistic circuit model, and the analysis results are cross-validated across the collected data to verify accuracy and reliability. The method involves collecting data, analyzing it using the machine learning models, cross-validating the results, generating recommendations, and displaying them to an end-user. The invention provides a novel approach for enhancing the reliability and transparency of AI-driven cyber-physical systems.

The invention discloses a model and data hybrid driven PEM fuel cell life prediction method. The method comprises the following steps: acquiring endurance test data; based on the endurance test data, respectively combining an equivalent circuit model and a polarization curve model to carry out aging characteristic analysis on the PEM fuel cell to obtain aging characteristics; processing the aging characteristics, and extracting a mixed aging index in combination with a part aging model; the mixed aging indexes are input into a life prediction model after being normalized, the aging trend of the PEM fuel cell is predicted, the remaining service life is estimated, and the life prediction model is constructed through optimization of a Bi-LSTM neural network. The aging trend of the PEM fuel cell can be predicted, and the remaining service life can be accurately estimated.

The present disclosure relates to the technical field of electromagnetic compatibility test and evaluation, and particularly relates to a method and system for predicting electromagnetic radiation intensity of an integrated isolation chip. The method comprises: converting a first electromagnetic field model of a transformer into an equivalent circuit model, and obtaining simulated parasitic electrical parameters; comparing the measured parasitic electrical parameters with the simulated parasitic electrical parameters to adjust the equivalent circuit model; inputting the common-mode current of the adjusted equivalent circuit model as an excitation signal into a second electromagnetic field model of a PCB evaluation board to obtain an electromagnetic radiation intensity simulation result of the integrated isolation chip, wherein the common-mode current is determined as the main radiation source of the integrated isolation chip; comparing the electromagnetic radiation intensity simulation result with an electromagnetic radiation intensity measurement result to adjust the second electromagnetic field model, and obtaining an electromagnetic radiation intensity prediction model of the integrated isolation chip. The present disclosure can accurately predict the radiation intensity of the isolation chip, reduce the necessity of multiple rounds of sampling and testing, and improve the reliability and stability of chip design.

The application discloses a kind of generator stator winding partial discharge quantity's inversion method and system, belong to large-scale rotating electrical machine insulation state diagnostic technical field, method includes: obtaining or estimating the key distributed capacitance parameter in insulation structure multi-capacitance equivalent circuit model, mapping relationship database is established;Partial discharge detection is carried out to the generator stator winding of applied test voltage, and the characteristic information of discharge pulse is collected;Based on the key distributed capacitance parameter in mapping relationship database, pre-generated pulse waveform-defect capacitance calibration curve, the characteristic information of discharge pulse collected is executed nonlinear iterative inversion calculation;Quantitative evaluation, type identification and health diagnosis are carried out to the insulation defect of generator stator winding.The application introduces pulse waveform feature into partial discharge physical quantity inversion, improves the accuracy, quantitative level and defect identification ability of generator stator insulation state evaluation, provides technical support for generator life extension and condition maintenance.

The invention relates to a working condition simulation method and device of a converter transformer, equipment and a storage medium. The method comprises the following steps: in response to a selection instruction input by a user in a component selection list in a simulation interface of a target simulation application, creating a simulation circuit model of a to-be-simulated converter circuit according to a component selected by the selection instruction; in response to a definition operation of a user on any part in the simulation circuit model, displaying a definition interface in a nearby area of any part; performing parameter configuration on any part according to the related definition information; after parameter configuration of all components in the simulation circuit model is completed, responding to an operation instruction input by a user in the simulation interface, simulating the operation process of the to-be-simulated converter circuit by using the simulation circuit model, and obtaining and displaying a voltage waveform output by the simulation circuit model; and performing working condition analysis on the voltage waveform to obtain and display the current working condition of the to-be-simulated converter circuit. The method improves the accuracy of the working condition simulation result of the converter transformer.

The application discloses a kind of digital control circuit board anti-interference filter design methods under group pulse action, realize the accurate modeling of EFT noise to digital control circuit conduction interference coupling, and based on conduction interference coupling circuit model and failure threshold, the quantitative design of anti-interference filter is carried out.Compared with traditional method, the application provides a kind of method for establishing chip black box impedance model based on online test and vector matching method, solves the impedance model modeling problem of chip under no internal structure data, and establishes the conduction interference coupling model of digital control circuit under EFT noise, provides model basis for quantitative design;From the angle of quantitative design, the anti-interference filter design method of the application effectively improves the anti-interference level of digital control circuit.

Embodiments of the present disclosure relate to methods and systems for selecting circuit models from a database of circuit models. A method of selecting a base building block model from a trained dataset of base building block models can include performing a semantic similarity search of the trained dataset based on a user specification to produce a candidate set of base building block models. The specification can be communicated to the trained dataset through an initial prompt. The method can also include combining the initial prompt from the user with the candidate set of base building block models to produce an augmented prompt, submitting the augmented prompt to a primary large language model (LLM), and receiving from the primary LLM a prioritized ranking of a final set of base building block candidates produced based at least in part on the specification from the user. The method can also include performing a multi-stage re-ranking of the set of base building block model candidates using a dual encoder and a subsequent cross-encoder.

The invention belongs to the technical field of power equipment state monitoring and fault diagnosis, and particularly relates to a dry-type air-core reactor turn-to-turn short circuit early warning method, which comprises the following steps of: establishing a circuit model and a voltage equation set of a dry-type air-core reactor in a normal operation state and a turn-to-turn short circuit fault state; acquiring a voltage signal and a current signal of the dry-type air-core reactor in a running process in real time; calculating one or more key electrical parameters of the dry-type air-core reactor based on the voltage signal and the current signal; comparing and analyzing the calculated key electrical parameters with corresponding preset thresholds or reference parameters in a normal state; and when the variable quantity or the absolute value of at least one key electrical parameter exceeds a corresponding preset range, triggering turn-to-turn short circuit early warning. According to the invention, the early and accurate early warning of the turn-to-turn short circuit fault of the dry-type air-core reactor is realized, and the technical bottleneck of slow action of traditional overcurrent protection is fundamentally broken through.

This invention relates to the field of automotive energy management technology, specifically disclosing a method for optimizing the parking and charging strategy of range-extended electric vehicles based on the MOMSA algorithm. The method includes establishing a power equivalent circuit model, constructing a battery aging model, and a multi-objective optimization function. The optimization method comprises the following steps: Step 1: Initialize the population; Step 2: Simulate the charging process; Step 3: Calculate the fitness of the population and determine non-dominated solutions; Step 4: Select a position vector based on the congestion distance CD; Step 5: Calculate the fitness value of the updated mantis position; Step 6: Determine new non-dominated solutions in the population and eliminate all dominated solutions; Step 7: Calculate the CD of each Pareto archive member; Step 8: Check if the iteration requirements are met; if not, return to Step 2; Step 9: Select the most suitable charging current. This invention's charging strategy optimization method enables a smoother battery charging process, improving battery life and charging efficiency.