19 results about "Diode modelling" patented technology

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 discloses a dual-diode model parameter extraction method for a solar cell and a photovoltaic module and related equipment. The method comprises the following steps: constructing a dual-diode model of the solar cell and the photovoltaic module; constructing a nonlinear equation set satisfied by model parameters according to the double-diode model of the solar cell and the photovoltaic module and the actually measured photoelectric characteristic data, and calculating initial values of the model parameters according to the actually measured photoelectric characteristic data; the equation number of the nonlinear equation set is determined by the number of model parameters; and introducing a preset step length factor to improve an iterative formula of a Newton-Rafson algorithm, and solving a nonlinear equation set satisfied by the model parameters based on the initial value, the improved iterative formula and a preset iterative parameter value so as to extract the dual-diode model parameters of the solar cell and the photovoltaic module. According to the embodiment of the invention, accurate dual-diode model parameters conforming to physical significance can be extracted. The method can be widely applied to the technical field of data processing.

The LDMOS device model comprises a BSIM4 model, a plurality of segmented resistor models which are sequentially connected in series and a plurality of drain substrate diode models, and the segmented resistor models which are sequentially connected in series are connected to a drain electrode of the BSIM4 model in series. A drift region of an LDMOS is simulated through a plurality of segmented resistor models which are sequentially connected in series, and the input end of each segmented resistor model is connected with a corresponding drain substrate diode model. Due to the fact that the segmented resistor models are connected in series, changes of electrical characteristics of drain substrate diodes at different positions of a drift region are simulated, and then the simulation precision of the LDMOS device model on drain substrate parasitic capacitance and gate channel intrinsic capacitance of an LDMOS is improved. And the simulation precision of the reverse leakage current of the drain substrate diode is improved.

The application discloses an AI-based diode model parameter automatic extraction and optimization method, and belongs to the technical field of electronic design.The application solves the problem that the existing diode model parameter extraction method is seriously dependent on manual experience, the process is complicated and time-consuming, and it is difficult to stably obtain high-precision and strong generalization capability model parameters from nonlinear data under the influence of temperature and process deviation.The application constructs an intelligent mapping model from macro electrical characteristics to microscopic model parameters by adaptively denoising and multidimensional feature engineering on measured data, and finally generates a high-fidelity diode electronic design model by combining global optimization of physical constraints, so as to realize high-precision, high-efficiency and full-automatic extraction and optimization of key model parameters such as diode saturation current, ideal factor and series resistance, thereby improving the efficiency, automation level and cross-condition robustness of model extraction.

The application discloses a manufacturing method of a diode and the diode manufactured by the method, wherein the method comprises the following steps: S1, setting a substrate layer and an epitaxial material parameter of a diode model, and establishing a diode physical model; S2, changing a concentration gradient factor of acceptor ions of an active region of the diode physical model, simulating a reverse breakdown voltage under different concentration gradient factors, and obtaining a relationship curve graph of the concentration gradient factor and the reverse breakdown voltage; S3, obtaining a concentration gradient factor range corresponding to a maximum reverse breakdown voltage from the relationship curve graph of the concentration gradient factor and the reverse breakdown voltage; S4, formulating and simulating a manufacturing process of the diode, and obtaining a process parameter for enabling the concentration gradient factor of the acceptor ions of the active region of the diode to fall within the concentration gradient factor range; and S5, manufacturing the diode according to the manufacturing process of the diode and the obtained process parameter. The diode manufactured by the method has an optimal reverse breakdown voltage and an optimal anti-avalanche capability under the same thickness of the epitaxial layer.

Disclosed in the present invention is a parameter calculation method for a single-diode model for a photovoltaic module. The method comprises: firstly, on the basis of an equivalent circuit of a single-diode model, obtaining a model under standard test conditions, and associating model parameters with test environment parameters to obtain a model for any test environment; and then acquiring performance parameters of a photovoltaic module, which comprise a short-circuit current, an open-circuit voltage, the maximum power-point current, the maximum power-point voltage, a short-circuit current temperature coefficient and an open-circuit voltage temperature coefficient, and constructing a system of equations and solving same to obtain model parameters. The present invention can realize the modeling and parameter identification of a model only on the basis of product specification information provided by a module manufacturer, without a complete I-V curve, thereby achieving a strong guiding significance for simulation and production practices.

The invention discloses a cable joint early fault detection method based on mathematical morphology, and belongs to the technical field of power line control, and the method comprises the steps: introducing a carbonization channel resistor and a water film resistor on a diode model, and obtaining a fault equivalent circuit model; building a cable network structure in the simulation software, setting a single-phase earth fault of the damped cable joint in the cable network structure, and performing fault simulation by using the fault equivalent circuit model; based on a fault simulation result, determining a zero-sequence voltage as an early fault detection signal, and enhancing and capturing fine distortion in a zero-sequence voltage waveform by using top-hat transformation to obtain a top-hat characteristic quantity; if the top cap characteristic quantity is greater than an amplitude safety threshold value and the duration greater than the amplitude safety threshold value is greater than a safety duration threshold value, judging that an early fault occurs; and determining the development stage of the early fault by using the top hat feature relative variance. According to the method, the early fault of the damped cable joint is accurately identified, the development stage of the damped cable joint is judged, and the detection sensitivity is improved.

The application relates to the field of photovoltaic system performance evaluation, and discloses a photovoltaic module string output characteristic quantification method and model under near shadow. The method inputs standard test condition electrical parameters of a photovoltaic module, including a short-circuit current, an open-circuit voltage, maximum power point parameters, a temperature coefficient, a cell type and a series-parallel topology structure inside the module, calculates module-level parameters based on a single-diode model, and maps the module-level parameters to cell-level parameters through the topology structure inside the module. In combination with irradiance and temperature under unshaded and shaded conditions, parameters such as photogenerated current and reverse saturation current are dynamically adjusted to calculate cell volt-ampere characteristics. Then, volt-ampere characteristic curves of cells, sub-strings, modules and module strings are integrated step by step to finally obtain voltage-current characteristics of the module string under near shadow. The method is suitable for full-cell modules, half-cell modules and heterojunction modules, and can quickly and accurately quantify the output characteristics of the module string under shading conditions.

This invention discloses a method for measuring the bandgap of photovoltaic modules, belonging to the field of solar cell property analysis technology. The method includes: First, continuously measuring the current-voltage characteristics of the photovoltaic module output in an outdoor environment, recording multiple sets of data and the module temperature during measurement. Second, using the obtained current-voltage data, establishing a three-diode model, where two diodes have fixed ideal factors of 1 and 2, and the ideal factor of the third diode is a variable parameter. Benders parameter decomposition technology and optimization algorithms are used to extract model parameters. Finally, using the relationship between the reverse saturation current with an ideal factor of 1 and temperature, the bandgap of the photovoltaic module is calculated. Compared to existing methods for measuring bandgap, this invention eliminates the need for expensive spectrometers or X-ray photoelectron spectrometers, requires no destructive operations, and is applicable to encapsulated photovoltaic modules of any size with unknown ideal factors. It offers advantages such as low cost and ease of implementation.

Disclosed in the present invention is a photovoltaic module model parameter identification method, comprising the following steps: 1) measuring and recording an I-V curve of a photovoltaic module in a standard test environment; 2) deriving an explicit expression of voltage and current on the basis of an equivalent circuit of a single-diode model; 3) converting a parameter identification problem into an optimization problem, determining a parameter search space of a target function in the optimization problem, solving the optimization problem and obtaining five parameter values of the model by means of parameter conversion; and 4) using the explicit expression in step 2) to simulate the I-V curve, and calculating a simulation error. The present invention improves a parameter identification method for a single-diode model, which requires only one calculation, thereby reducing the calculation amount and improving the accuracy and stability of identification.

The invention discloses a method for extracting parameters of a three-diode model of a photovoltaic cell, and the method comprises the steps: building a three-diode equivalent circuit model of the photovoltaic cell, and determining a plurality of to-be-recognized parameters of the photovoltaic cell according to the three-diode equivalent circuit model; output current-voltage I-V curve data of the three-diode equivalent circuit model are obtained, and the curve data at least comprise three feature point data, namely open circuit point voltage, short circuit point current and voltage and current of the maximum power point; and solving the three-diode equivalent circuit model based on the obtained I-V curve data, and obtaining an optimal solution of the to-be-identified parameters. The whole parameter extraction step has no matrix inversion operation and no random search process, the calculation complexity is low, continuous automatic model monitoring can be realized, and a parameter feasible region does not need to be manually set.

The invention belongs to the field of microwave circuit and device modeling, and provides a PIN diode electric heating modeling method based on neural network space mapping. The method comprises the following steps: firstly, establishing an electric heating coarse model and a fine model of the PIN diode, and correcting the output of the coarse model through space mapping; the modeling process is divided into two times of mapping, firstly, a rough model electrical module input mapping network is established, the error between the electrical module output current and the fine model output current is reduced, secondly, a rough model thermal module input mapping network is established, and the error between the thermal module output temperature and the fine model output temperature is reduced. The electrical and thermal characteristic responses of the model are corrected by adjusting weight parameters in the two input mapping networks, so that the response of the PIN diode model based on neural network space mapping established by the invention is consistent with that of a fine model. According to the modeling method provided by the invention, the modeling precision and efficiency of the diode electrothermal model can be effectively improved, and the reliability of a simulation result under a temperature effect is ensured.

The application relates to a super-junction MOSFET device drift region parabolic variable resistance model and a modeling method, which comprises the following steps: constructing a super-junction MOSFET circuit model, wherein the model is composed of a MOSFET, a drift region parabolic variable resistance, a body diode and a first resistance I and a first resistance II; resistance modeling is carried out on the drift region of the super-junction MOSFET device according to the physical structure parameters of the super-junction MOSFET, and a parabolic variable resistance model of the drift region is obtained by adopting a parabolic approximation; a Taylor polynomial is introduced to describe a self-heating first resistance model. The parameters of the drift region parabolic variable resistance model are obtained through the physical structure parameters of the super-junction MOSFET device, the parameters of a conventional MOSFET model, the parameters of a body diode model and the parameters of a self-heating first resistance model are obtained through actual measurement data of the device. The application can well simulate the characteristics of the super-junction MOSFET device in various working regions, and the simulation accuracy is high.

The invention discloses a single-diode model parameter extraction method of a solar cell and a photovoltaic module and related equipment. The method comprises the following steps: constructing a single-diode model of the solar cell and the photovoltaic module; constructing a nonlinear equation set satisfied by model parameters according to the single-diode model of the solar cell and the photovoltaic module and the actually measured photoelectric characteristic data, and calculating initial values of the model parameters according to the actually measured photoelectric characteristic data; and introducing a preset step length factor to improve an iterative formula of a Newton-Rafson algorithm, determining an iterative parameter value, and carrying out Newton-Rafson solution on the nonlinear equation set satisfying the model parameters based on the initial value, the improved iterative formula and the iterative parameter value so as to extract the single-diode model parameters of the solar cell and the photovoltaic module. According to the embodiment of the invention, accurate single-diode model parameters conforming to physical significance can be extracted. The method can be widely applied to the technical field of data processing.

The invention belongs to the field of photovoltaic power generation system modeling and parameter identification, and discloses a photovoltaic model parameter optimization system and method based on a multi-stage self-adaptive strategy, and the method aims at five parameters of photo-generated current, reverse saturation current, series resistance, parallel resistance and ideal factors of a single-diode model. A four-stage cascade optimization framework is adopted: firstly, an initial population is generated through Tent chaotic mapping driven by a dynamic physical boundary; secondly, weighted Levy flight global search is implemented on the basis of I-V curve segmentation characteristics; a clustering variance and parameter sensitivity dual-drive mechanism is introduced to realize adaptive balance of exploration and development strategies; and finally, local convergence is completed by adopting BFGS gradient refinement guided by clustering information. According to the method, the problem that global exploration and local convergence are difficult to consider in photovoltaic parameter identification is effectively solved, the parameter fitting precision, the convergence speed and the stability are remarkably improved, and the method is suitable for photovoltaic module performance evaluation and system optimization design.

The invention provides a SiC MOSFET (Metal-Oxide-Semiconductor Field Effect Transistor) modeling method and system considering various parasitic parameters, and belongs to the technical field of SiCMOSFET device modeling. The method comprises the following steps: constructing a parasitic junction capacitance relational expression of the SiC MOSFET device; carrying out sectional modeling on the input capacitance of the SiC MOSFET device; modeling is carried out on an output capacitor and a reverse transmission capacitor of the SiC MOSFET device; obtaining drain inductance, source inductance, gate inductance and gate driving resistance of the SiC MOSFET device; constructing a diode model; and building a double-pulse test circuit of the SiC MOSFET device. According to the method, the defects of an existing SiC MOSFET device modeling method in the aspects of precision and efficiency are overcome, and particularly the problem of simulation deviation caused by neglecting key parasitic parameters and nonlinear behaviors in the high-frequency switching process of the SiC MOSFET device is solved.

This invention provides a method, apparatus, control device, and diagnostic system for diagnosing photovoltaic (PV) power generation systems. The method, based on a differential power processing device in the PV power generation system, includes: acquiring a terminal voltage signal and a current signal output in response to a preset excitation voltage signal from the PV panel under test based on a fault diagnosis trigger signal; matching the terminal voltage signal and current signal with a preset diode model of a solar cell to determine the values ​​of various modeled circuit parameters corresponding to the terminal voltage and current signals in the diode model of the preset solar cell; and performing fault diagnosis on the PV panel under test based on the values ​​of these modeled circuit parameters. This invention can avoid the reduction in PV power generation efficiency caused by faults that are difficult to detect in a localized manner over a long period; and it does not require additional device costs.

A seven-parameter extraction method for a photovoltaic cell double-diode model comprises the following steps: S1, establishing a double-diode equivalent circuit topological structure of a photovoltaic cell, and defining physical meanings of seven parameters; s2, constructing a dual-diode seven-parameter mathematical model based on the I-V characteristics of the photovoltaic cell; s3, acquiring dark-state current-voltage characteristic data of the photovoltaic cell; s4, photo-generated current parameters are calculated; s5, based on the extracted series resistance and parallel resistance, photo-generated current is determined; and S6, model verification and precision evaluation. According to the invention, by introducing an innovative algorithm of dark state characteristic analysis and regional extraction, the technical bottlenecks of low precision and low efficiency of a traditional parameter extraction method are broken through, and high-precision and high-efficiency synchronous extraction of seven parameters of the photovoltaic cell double-diode model is realized; the method provides an effective technical means for establishing a more accurate and reliable photovoltaic cell equivalent circuit model, and has important theoretical value and practical application significance.

The application discloses a photovoltaic array double-diode seven-parameter model parameter identification method. Based on the application of the combination of the improved particle swarm algorithm and the analytic method, two diode ideal factors and series equivalent resistance are solved by optimization, and then the photogenerated current, parallel equivalent resistance and two diode reverse saturation currents are solved by the analytic method. In order to improve the performance of the improved algorithm, a double fitness function is proposed, and an adaptive evolution learning and adaptive mutation operator are introduced. The application solves the problem of difficulty in solving the double-diode seven-parameter model parameters of the photovoltaic array and the problem of low solving precision of the single-diode model parameters.