Dielectric barrier discharge development process dynamic simulation method based on equivalent circuit model

Abstract

The invention discloses a dielectric barrier discharge development process dynamic simulation method based on an equivalent circuit model. The method comprises the following steps: building a DBD experiment platform to obtain electrical, optical and particle characteristics under different experiment conditions; constructing a DBD equivalent circuit model; combining electrical characteristic experimental data obtained in the experiment without the discharge air gap with a DBD static equivalent circuit model corresponding to the electrical characteristic experimental data in analogue simulation software, and solving inherent parameters in the model by utilizing an intelligent algorithm; obtaining electrical characteristic experiment data when a discharge air gap exists; substituting the inherent parameters into a DBD dynamic equivalent circuit model, and solving the dynamic change of equivalent circuit parameters in a model discharge area by using an intelligent algorithm; and comparing the parameters and dynamic changes thereof with experimental characteristics, and analyzing a DBD development process mechanism and influence factors. The method analyzes the DBD development process from the simulation result, has the advantage of simple experiment diagnosis complex work, and is also suitable for simulation and simulation research of different power supply conditions and discharge forms.

Description

Technical Field

[0001] The invention relates to the field of plasma technology, and in particular to a dynamic simulation method for a dielectric barrier discharge development process based on an equivalent circuit model. Background Art

[0002] As energy shortage, environmental protection and room temperature effect become increasingly serious, energy-saving and environmentally friendly plasma technology has attracted great attention from countries around the world. Among them, low-temperature plasma has played an important role in many fields such as material surface modification, ozone generation, and pollutant treatment. The generation of discharge plasma is due to the fact that after the external electric field is applied, the electrons gain energy under the action of the external electric field and collide with the surrounding particles. The collision is accompanied by energy transfer, which causes electron avalanches in the surrounding particles and generates a large amount of charge. As the charge accumulates, the intrinsic electric field (self-inductance electric field) is formed. The generated electric field will further accelerate these high-energy electrons, and the conductive channel is formed by the propagation of ionized atoms to the cathode. When this channel passes through the discharge air gap, the gas will be broken down. Dielectric barrier discharge (DBD) is a common means of generating low-temperature plasma. Establishing a reasonable DBD equivalent circuit model is of great significance for a deep understanding of the discharge characteristics and dynamic development process.

[0003] At present, there are mainly three types of equivalent circuit models established at home and abroad: nonlinear clamping model, controlled source model, and resistance-capacitance model. The nonlinear clamping model simulates the bidirectional clamping characteristics of the air gap capacitor by a diode and a voltage source, which mainly reflects the nonlinear behavior of the reactor air gap voltage; the controlled source model uses a voltage-controlled current source to describe the external volt-ampere characteristics of the load under certain excitation modes; the series resistance-capacitance model and the parallel resistance-capacitance model use a series or parallel equivalent resistance-capacitance circuit to replace them when analyzing the steady-state working state of the plasma reactor. However, although these equivalent circuit models can accurately reflect the static state of the discharge, due to the simple model changes, they cannot accurately describe the nonlinear dynamic changes of the equivalent component parameters during the discharge process. Therefore, it is innovative to combine intelligent algorithms with equivalent circuit models to efficiently perform more refined segmented simulation and emulation.

[0004] In the prior art, Qi Zewu et al. in "Design of DBD High-Frequency and High-Voltage Discharge Power Supply and Its Discharge Characteristics" and Zhao Weidong et al. in "Simulation Calculation and Experimental Study of Discharge Power of Coaxial Cylindrical Structure DBD Device" have established nonlinear clamping models for DBD, which can accurately describe the switching of load states within a discharge cycle and obtain equivalent circuits under different states. However, this type of equivalent circuit model is relatively macroscopic and cannot describe the dynamic process of DBD-type loads at work, let alone accurately reveal the discharge characteristics. Application No. 202310644494.6 discloses a research method for the transmission characteristics of plasma electromagnetic waves based on an equivalent circuit model. The invention establishes an initial plasma equivalent circuit model based on the electromagnetic transmission characteristic curve obtained by the moment method, compares the electromagnetic transmission characteristic curves obtained by the moment method and the equivalent circuit method, and determines the optimal values ​​of the parameters of the circuit components in the model, thereby determining the transmission characteristics of electromagnetic waves in the plasma and revealing the transmission mechanism of electromagnetic waves in the plasma. However, this method does not involve segmented simulation or emulation, nor does it explore the dynamic changes of parameters. In addition, the research content is the characteristics of electromagnetic wave transmission, and the constructed equivalent circuit model is not suitable for studying the DBD development process. Summary of the invention

[0005] 1. Technical problems to be solved:

[0006] In view of the above technical problems, the present invention provides a dynamic simulation method of the development process of dielectric barrier discharge based on an equivalent circuit model, which utilizes the advantages of fast optimization speed of intelligent algorithm calculation, combined with the advantages of simplicity and high accuracy of the resistance-capacitance parallel equivalent circuit model based on the air gap discharge channel to simulate the DBD phenomenon. The main purpose of the present invention is to obtain the experimental voltage and current waveform data, first calculate the inherent parameters, and then segment the simulation time, with the goal of fitting the current waveform, to obtain the air gap equivalent resistance and air gap equivalent capacitance in different time periods. According to the dynamic changes of the air gap equivalent resistance and air gap equivalent capacitance during the entire pulse time, the dynamic development process of the discharge is reflected, so as to deeply understand the discharge characteristics, and combine the optical characteristics and particle characteristics collected by the experimental platform to realize the analysis of the mechanism and influencing factors of the DBD discharge development process.

[0007] 2. Technical solution:

[0008] A dynamic simulation method for dielectric barrier discharge development process based on an equivalent circuit model is characterized by comprising the following steps:

[0009] Step 1: Building a DBD experimental platform; the DBD experimental platform is used to conduct experiments of different DBD types, analyze experimental phenomena, and obtain experimental data of corresponding electrical properties, optical properties, and particle properties under different experimental conditions;

[0010] Step 2: construct a DBD equivalent circuit model in a software simulation platform; the DBD equivalent circuit model includes static equivalent circuit models and dynamic equivalent circuit models of different DBD types, which are used to simulate the DBD experiment by numerical fitting to obtain the inherent parameters corresponding to the DBD experiment and the dynamic change simulation results of the equivalent circuit parameters of the discharge area;

[0011] Step 3: Substitute the experimental data of electrical characteristics obtained in the DBD experiment without a discharge air gap into the corresponding DBD static equivalent circuit model in the simulation platform, set the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to solve the inherent parameters in the DBD static equivalent circuit model;

[0012] Step 4: Change the DBD experimental conditions in step 3 to the presence of a discharge air gap, and obtain the experimental data of the electrical characteristics at this time; bring the inherent parameters solved in step 3 into the corresponding DBD dynamic equivalent circuit model, change the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to segment the total simulation time, and numerically fit to solve the simulation results of the dynamic changes of the equivalent circuit parameters in the discharge area in the DBD dynamic equivalent circuit model;

[0013] Step 5: Compare the simulation results of the dynamic changes of the inherent parameters obtained in step 3 and the equivalent circuit parameters of the discharge area obtained in step 4 with the experimental data of the optical properties and particle properties obtained experimentally. This allows the DBD development process mechanism and influencing factors to be analyzed from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge mode conversion, and ultimately the DBD mechanism characteristics can be explored.

[0014] Furthermore, the electrical characteristics are the data of DBD voltage and current changing with time, i.e., the current and voltage waveform; the optical characteristics are the temperature of the discharge space, the shape of the luminous image and the light intensity; the particle characteristics are the discharge space spectrum information and the spatial charge distribution;

[0015] The DBD experimental platform collects voltage and current waveforms through voltage and current sensors and oscilloscopes; captures luminous images of the discharge space and measures its light intensity through one or more of ICCD, thermal imager, digital camera, and photomultiplier tube; and measures the discharge space spectrum information and spatial charge distribution through one or more of ICCD, emission spectrometer, Fourier transform infrared absorption spectrometer, laser induced fluorescence spectrometer, and Langmuir probe.

[0016] The different experimental conditions include different power supply parameters, different air gap distances, and different dielectric materials.

[0017] Furthermore, the different DBD types include flat DBD, suspended electrode DBD, surface DBD and DBD-type jet; in step 2, the discharge channel in the DBD dynamic equivalent circuit model includes an RC circuit consisting of a parallel air gap variable capacitor Cg and an air gap variable resistor Rg, a dielectric capacitor Cd, a high voltage electrode and a grounding electrode; a discharge channel is formed between the high voltage electrode and the grounding electrode; the dielectric capacitor Cd in the discharge channel of the flat DBD and the suspended electrode DBD is connected in series with the RC circuit, while the grounding electrode of the suspended electrode DBD is a directly processed object and is considered to be connected to the ground during analysis; there is also a dielectric capacitor C between the high voltage electrode and the discharge channel in the discharge channel of the surface DBD d1 and the dielectric capacitance Cd2 between the high-voltage electrode and the grounding electrode, wherein Cd1 is connected in series with the RC circuit and then connected in parallel with Cd2; in the DBD type jet, in addition to the dielectric capacitance Cd being connected in series with the RC circuit, the body feather discharge part is equivalent to a second RC circuit formed by the body feather variable capacitance Cp and the body feather variable resistance Rp and connected in parallel with Cd; the DBD equivalent circuit model also includes an RL equivalent circuit located in series between the discharge channel and the high-voltage power supply; the RL equivalent circuit is a lead resistance Rw connected in series with a parasitic inductance L; the DBD dynamic equivalent circuit model is a DBD static equivalent circuit model when there is no discharge air gap, and the RC circuit in the circuit is removed when analyzing the DBD static equivalent circuit model.

[0018] Furthermore, in step three, the preset intelligent algorithm is a genetic algorithm, and the experimental data of voltage and current changing with time obtained from the DBD experimental platform is read from the MATLAB software, and the corresponding DBD static equivalent circuit model is built and the parameters and conditions of the model and simulation are set. The simulation data of the current changing with time under the excitation of the experimental voltage data is obtained by numerical fitting, and the minimum error value between the simulated current and the experimental current is obtained by continuous iterative calculation, and the optimal value of the corresponding inherent parameters at this time is obtained; the inherent parameters include the lead resistance Rw, the parasitic inductance L and the dielectric capacitance Cd. When simulating the surface DBD, the inherent parameters include the lead resistance Rw, the parasitic inductance L, the dielectric capacitance Cd1 and Cd2; specifically including the following steps:

[0019] S31: Using the DBD experimental platform built in step 1, conduct experiments with different types of DBDs without discharge air gaps under different experimental conditions; collect data on the change of voltage and current over time in the experiment through an oscilloscope with a preset sampling rate and a voltage and current sensor, the data being the voltage and current values ​​of the corresponding experiment at different sampling time points, and read these data using MATLAB software;

[0020] S32: Calling Simulink simulation software to build a static equivalent circuit model of DBD in the absence of a discharge air gap, and sequentially setting the corresponding Simulink simulation parameter values ​​and conditions under different experimental conditions through MATLAB code; the simulation parameter values ​​include simulation step type, step time, and voltage signal of the excitation source in the circuit; wherein the voltage signal of the excitation source in the circuit is the data of voltage variation over time obtained in the experiment in S31; the simulation condition is the end time of a single Simulink simulation, that is, the total duration of a single experimental data;

[0021] S33: A genetic algorithm framework is built in MATLAB to calculate the inherent parameters when the DBD has no discharge air gap, and obtain the optimal values ​​of the lead resistance Rw, parasitic inductance L and dielectric capacitance Cd; the specific process is as follows:

[0022] First, the basic parameters of the genetic algorithm are set, including the value range of the intrinsic parameters Rw, L, and Cd, the objective function F, the binary digit size of the intrinsic parameter encoding, the population size, the genetic generation, the gene selection, the crossover, the mutation probability, and the minimum allowable error of the numerical fitting;

[0023] Secondly, an initial population is created, and intrinsic parameters with a given population size and value range are randomly generated; after selection, crossover, and mutation, the intrinsic parameter values ​​generated each time are substituted into Simulink, and the static equivalent circuit model built in Simulink is run through MATLAB code to obtain the data of the simulated current variation over time of the equivalent circuit under different intrinsic parameters Rw, L, and Cd;

[0024] Finally, the error value F between the simulated current and the experimental current changing with time is calculated according to the following formula, and the current error value F is used as the objective function:

[0025]

[0026] In the above formula: n is the total number of sampling time points in this experiment; I exp (i) is the experimental current at the i-th sampling time point, I sim (i) is the simulated current at the i-th sampling time point; through continuous iteration, when the objective function value is minimized, the corresponding inherent parameters Rw, L, Cd values ​​are obtained, which are the optimal values ​​of the inherent parameters Rw, L, Cd.

[0027] Furthermore, in step 4, the preset intelligent algorithm is a genetic algorithm; based on the DBD dynamic equivalent circuit model constructed in step 2 and the inherent parameters obtained in step 4, the total simulation time is numerically fitted in time periods according to different stages of the DBD discharge state, and the discharge area equivalent circuit parameters of the corresponding DBD dynamic equivalent circuit model and the dynamic change process of the component state value over time are obtained in the time periods corresponding to the different stages of the discharge state, and a current fitting diagram is fitted; the discharge area equivalent circuit parameters include air gap variable capacitance Cg and air gap variable resistance Rg, and when simulating DBD type jets, body feather variable capacitance Cp and body feather variable resistance Rp are also required; the component state value includes the inductor current IL, the voltage across the medium UCd, and the voltage across the air gap UCg; the specific process is:

[0028] A genetic algorithm framework was built in MATLAB to segmentally calculate the discharge area equivalent circuit parameters of DBD with a discharge air gap under each experimental condition, that is, the dynamic changes of the air gap variable capacitance Cg and the air gap variable resistance Rg, and give the current fitting diagram; specifically,

[0029] First: set the basic parameters of the genetic algorithm; set the value range of the air gap variable capacitor Cg and the air gap variable resistor Rg; the segmented calculation adopts the method of dividing the total simulation time into different time periods according to the different stages of the discharge state, and using the same time step method in the same stage;

[0030] Secondly, an initial population is created, and discharge region equivalent circuit parameters with a given population size and value range are randomly generated; thirdly, in the i-th time segment, according to the calculation step of S33, the optimal values ​​of the discharge region equivalent circuit parameters in the time segment and the state values ​​IL, UCd, UCg of the model elements L, Cd, Cg are calculated, and the state value at the end of each segment is assigned to the next segment as the initial state value;

[0031] Finally, the optimal values ​​of the simulated current value, air gap variable capacitance Cg, and air gap variable resistance Rg parameters in each time period are summarized into a data set that changes with time within the entire pulse, namely, the current fitting graph and the dynamic change trend graph of the equivalent circuit parameters Cg and Rg in the discharge area in the equivalent circuit model.

[0032] Furthermore, step five specifically includes the following steps:

[0033] S51: The temporal and spatial evolution of the discharge state in the discharge air gap is obtained through the temperature and luminescence images of the discharge space collected experimentally; the discharge state includes uniform discharge, filamentary discharge, single current pulse discharge, multi-current pulse discharge, and discharge extinction; the particle concentration and charge distribution in the discharge space are measured by the experimental platform to analyze the temporal and spatial variation characteristics of gas excitation, ionization, and reaction of DBD during the discharge process;

[0034] S52: According to the process of the optical and particle characteristics obtained in step S51 changing with time, the accuracy of the dynamic changes of the equivalent circuit parameters of the discharge region in the equivalent circuit model obtained in step 4 can be evaluated; specifically, the association between the equivalent circuit parameters Cg and Rg of the discharge region of the equivalent circuit model and the optical and particle characteristics is established; the association includes that the Rg parameter can reflect the spatiotemporal distribution change of the electron density in space, and the Cg parameter can reflect the spatiotemporal distribution of the relative positions of the positive and negative charges in space; according to the association, the consistency between the dynamic changes of the parameters in the equivalent circuit model and the trend of the experimental results can be qualitatively evaluated;

[0035] S53: According to the changes in the parameters of the equivalent circuit model and the experimental results, the process of conversion of different discharge states of DBD is analyzed; the different discharge states of DBD include the displacement current segment and discharge process segment at the rising and falling edges of the nanosecond pulse, the pulse voltage output stable segment, and the pulse-free voltage output segment; the process includes judging the conversion time points of different discharge states based on the dynamic changes of the observed air gap, the voltage across the medium, and the equivalent circuit parameters of the discharge area, and then summarizing the mechanism and influencing factors of the DBD development process.

[0036] 3. Beneficial effects:

[0037] (1) In this method, DBD circuits are classified according to different discharge forms of DBD devices, and different types of DBD equivalent circuit models are constructed according to different classifications, which can achieve more accurate and efficient analysis of different DBD discharge forms.

[0038] (2) This method uses an intelligent algorithm combined with a DBD equivalent circuit model to first calculate the optimal values ​​of the inherent parameters in the circuit, namely, lead resistance Rw, parasitic inductance L, and dielectric capacitance Cd, which can reduce the impact of these stray parameters in the circuit on the DBD process analysis.

[0039] (3) In this method, since the air gap variable capacitor Cg and the air gap variable resistor Rg of the discharge area equivalent circuit parameters will show nonlinear changes during the discharge process, the experimental conditions are changed on the premise of determining the optimal values ​​of the inherent parameters, namely the lead resistance Rw, the parasitic inductance L and the dielectric capacitance Cd. The intelligent algorithm is combined with the DBD equivalent circuit model to calculate the nonlinear change curves of the air gap variable capacitor Cg and the air gap variable resistor Rg, and the data of the simulated current change with time are solved by these two curves. The goal is to fit the simulated current data with the experimental data one by one, so as to achieve an accurate and reasonable solution to the equivalent circuit parameters of the discharge area, and provide a theoretical basis for explaining the development process of DBD.

[0040] (4) The change curves of the variable air gap capacitance Cg, variable air gap resistance Rg, and current obtained by this method are integrated with the optical properties and particle properties detected by the optical property detection equipment and particle property detection equipment of the experimental platform; in the analysis of the DBD development process, the dielectric barrier discharge development process is divided into 6 stages according to the waveform characteristics of voltage and current: the displacement current segment and discharge process segment at the rising and falling edges of the nanosecond pulse, the pulse voltage output stable segment, and the pulse-free voltage output segment. Taking the displacement current stage as an example, according to the nonlinear change curves of Rg and Cg obtained in the simulation, it can be seen that the larger the Rg value, the smaller the electric field strength in the discharge air gap, the slower the movement of charged particles, and the resistance characteristics; the smaller the Cg value, the smaller the number of charges in the electric field, the relatively concentrated position, the weaker the polarization effect, the smaller the dielectric constant of the air gap, and the basically no ionization of the gas; the particle concentration and charge distribution in the discharge space measured by ICCD, emission spectrometer, Fourier transform infrared absorption spectrometer, laser induced fluorescence spectroscopy, and Langmuir probe are obtained; through the fusion of the two, the relationship between the discharge particle development process, space charge dissipation and recombination, particle concentration changes in spectral data, and the dynamic changes of component parameters can be established.

[0041] In summary, this method uses the dynamic changes of model parameters and the experimental results of optical and particle characteristics collected by the experimental platform to analyze the mechanism and influencing factors of the DBD development process from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge state conversion, and finally explores the DBD mechanism characteristics. This method can analyze the development process of DBD from the simulation results, and has the advantage of simple experimental diagnosis of complex work. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a system block diagram of the method for solving the equivalent circuit parameters of the discharge region of the DBD equivalent circuit model using the genetic algorithm;

[0043] Figure 2 This is a block diagram of a dynamic simulation system for the dielectric barrier discharge development process based on an equivalent circuit model in this method;

[0044] Figure 3 A schematic diagram of constructing a DBD experimental platform in a specific embodiment;

[0045] Figure 4 Different types of DBD dynamic equivalent circuit models constructed in this method;

[0046] Figure 5 : is a planar DBD equivalent circuit model in a specific embodiment, wherein the left figure is without a discharge air gap, and the right figure is with a discharge air gap;

[0047] Figure 6It is a simulation result diagram of dynamic changes of equivalent circuit parameters in the discharge area in a specific embodiment;

[0048] Figure 7 It is a schematic diagram for analyzing the discharge process of a nanosecond pulse DBD in a specific embodiment. DETAILED DESCRIPTION

[0049] The present invention will be described in detail below with reference to specific embodiments and drawings.

[0050] As attached Figure 2 As shown, a dynamic simulation method for the development process of dielectric barrier discharge based on an equivalent circuit model is characterized by comprising the following steps:

[0051] Step 1: Building a DBD experimental platform; the DBD experimental platform is used to conduct experiments of different DBD types, analyze experimental phenomena, and obtain experimental data of corresponding electrical properties, optical properties, and particle properties under different experimental conditions;

[0052] Step 2: construct a DBD equivalent circuit model in a software simulation platform; the DBD equivalent circuit model includes static equivalent circuit models and dynamic equivalent circuit models of different DBD types, which are used to simulate the DBD experiment by numerical fitting to obtain the inherent parameters corresponding to the DBD experiment and the dynamic change simulation results of the equivalent circuit parameters of the discharge area;

[0053] Step 3: Substitute the experimental data of electrical characteristics obtained in the DBD experiment without a discharge air gap into the corresponding DBD static equivalent circuit model in the simulation platform, set the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to solve the inherent parameters in the DBD static equivalent circuit model;

[0054] Step 4: Change the DBD experimental conditions in step 3 to the presence of a discharge air gap, and obtain the experimental data of the electrical characteristics at this time; bring the inherent parameters solved in step 3 into the corresponding DBD dynamic equivalent circuit model, change the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to segment the total simulation time, and numerically fit to solve the simulation results of the dynamic changes of the equivalent circuit parameters in the discharge area in the DBD dynamic equivalent circuit model;

[0055] Step 5: Compare the simulation results of the dynamic changes of the inherent parameters obtained in step 3 and the equivalent circuit parameters of the discharge area obtained in step 4 with the experimental data of the optical properties and particle properties obtained experimentally. This allows the DBD development process mechanism and influencing factors to be analyzed from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge mode conversion, and ultimately the DBD mechanism characteristics can be explored.

[0056] Furthermore, the electrical characteristics are the data of DBD voltage and current changing with time, i.e., the current and voltage waveform; the optical characteristics are the temperature of the discharge space, the shape of the luminous image and the light intensity; the particle characteristics are the discharge space spectrum information and the spatial charge distribution;

[0057] The DBD experimental platform collects voltage and current waveforms through voltage and current sensors and oscilloscopes; captures luminous images of the discharge space and measures its light intensity through one or more of ICCD, thermal imager, digital camera, and photomultiplier tube; and measures the discharge space spectrum information and spatial charge distribution through one or more of ICCD, emission spectrometer, Fourier transform infrared absorption spectrometer, laser induced fluorescence spectrometer, and Langmuir probe.

[0058] The different experimental conditions include different power supply parameters, different air gap distances, and different dielectric materials.

[0059] Furthermore, as attached Figure 4 , 5 As shown, the different DBD types include flat DBD, suspended electrode DBD, surface DBD and DBD-type jet; in step 2, the discharge channel in the DBD dynamic equivalent circuit model includes an RC circuit composed of a parallel air gap variable capacitor Cg and an air gap variable resistor Rg, a dielectric capacitor Cd, a high voltage electrode and a grounding electrode; a discharge channel is formed between the high voltage electrode and the grounding electrode; the dielectric capacitor Cd in the discharge channel of the flat DBD and the suspended electrode DBD is connected in series with the RC circuit, while the grounding electrode of the suspended electrode DBD is the object to be directly processed and is considered to be connected to the ground during analysis; there is also a dielectric capacitor Cd between the high voltage electrode and the discharge channel in the discharge channel of the surface DBD 1 and the dielectric capacitance Cd2 between the high-voltage electrode and the grounding electrode, wherein Cd1 is connected in series with the RC circuit and then connected in parallel with Cd2; in the DBD type jet, in addition to the dielectric capacitance Cd being connected in series with the RC circuit, the body feather discharge part is equivalent to a second RC circuit formed by the body feather variable capacitance Cp and the body feather variable resistance Rp and connected in parallel with Cd; the DBD equivalent circuit model also includes an RL equivalent circuit located in series between the discharge channel and the high-voltage power supply; the RL equivalent circuit is a lead resistance Rw connected in series with a parasitic inductance L; the DBD dynamic equivalent circuit model is a DBD static equivalent circuit model when there is no discharge air gap, and the RC circuit in the circuit is removed when analyzing the DBD static equivalent circuit model.

[0060] Furthermore, in step three, the preset intelligent algorithm is a genetic algorithm, which reads the experimental data of voltage and current changing with time obtained from the DBD experimental platform from the MATLAB software, builds the corresponding DBD static equivalent circuit model and sets the parameters and conditions of the model and simulation, and obtains the simulation data of current changing with time under the excitation of the experimental voltage data by numerical fitting, obtains the minimum error value between the simulated current and the experimental current by continuous iterative calculation, and obtains the optimal value of the corresponding inherent parameters at this time; the inherent parameters include lead resistance Rw, parasitic inductance L and dielectric capacitance Cd, and when simulating surface DBD, the inherent parameters include lead resistance Rw, parasitic inductance L, dielectric capacitance Cd1 and Cd2; as shown in the attached figure Figure 1 As shown, the specific steps include:

[0061] S31: Using the DBD experimental platform built in step 1, conduct experiments with different types of DBDs without discharge air gaps under different experimental conditions; collect data on the change of voltage and current over time in the experiment through an oscilloscope with a preset sampling rate and a voltage and current sensor, the data being the voltage and current values ​​of the corresponding experiment at different sampling time points, and use MATLAB software to read these data;

[0062] S32: Calling Simulink simulation software to build a static equivalent circuit model of DBD in the absence of a discharge air gap, and sequentially setting the corresponding Simulink simulation parameter values ​​and conditions under different experimental conditions through MATLAB code; the simulation parameter values ​​include simulation step type, step time, and voltage signal of the excitation source in the circuit; wherein the voltage signal of the excitation source in the circuit is the data of voltage variation over time obtained in the experiment in S31; the simulation condition is the end time of a single Simulink simulation, that is, the total duration of a single experimental data;

[0063] S33: A genetic algorithm framework is built in MATLAB to calculate the inherent parameters when the DBD has no discharge air gap, and obtain the optimal values ​​of the lead resistance Rw, parasitic inductance L and dielectric capacitance Cd; the specific process is as follows:

[0064] First, the basic parameters of the genetic algorithm are set, including the value range of the intrinsic parameters Rw, L, and Cd, the objective function F, the binary digit size of the intrinsic parameter encoding, the population size, the genetic generation, the gene selection, the crossover, the mutation probability, and the minimum allowable error of the numerical fitting;

[0065] Secondly, an initial population is created, and intrinsic parameters with a given population size and value range are randomly generated; after selection, crossover, and mutation, the intrinsic parameter values ​​generated each time are substituted into Simulink, and the static equivalent circuit model built in Simulink is run through MATLAB code to obtain the data of the simulated current variation over time of the equivalent circuit under different intrinsic parameters Rw, L, and Cd;

[0066] Finally, the error value F between the simulated current and the experimental current changing with time is calculated according to the following formula, and the current error value F is used as the objective function:

[0067]

[0068] In the above formula: n is the total number of sampling time points in this experiment; I exp (i) is the experimental current at the i-th sampling time point, I sim (i) is the simulated current at the i-th sampling time point; through continuous iteration, when the objective function value is minimized, the corresponding inherent parameters Rw, L, Cd values ​​are obtained, which are the optimal values ​​of the inherent parameters Rw, L, Cd.

[0069] Furthermore, in step 4, the preset intelligent algorithm is a genetic algorithm; based on the DBD dynamic equivalent circuit model constructed in step 2 and the inherent parameters obtained in step 4, the total simulation time is numerically fitted in time periods according to different stages of the DBD discharge state, and the discharge area equivalent circuit parameters of the corresponding DBD dynamic equivalent circuit model and the dynamic change process of the component state value over time are obtained in the time periods corresponding to the different stages of the discharge state, and a current fitting diagram is fitted; the discharge area equivalent circuit parameters include air gap variable capacitance Cg and air gap variable resistance Rg, and when simulating DBD type jets, body feather variable capacitance Cp and body feather variable resistance Rp are also required; the component state value includes the inductor current IL, the voltage across the medium UCd, and the voltage across the air gap UCg; the specific process is:

[0070] A genetic algorithm framework was built in MATLAB to segmentally calculate the discharge area equivalent circuit parameters of DBD with a discharge air gap under each experimental condition, that is, the dynamic changes of the air gap variable capacitance Cg and the air gap variable resistance Rg, and give the current fitting diagram; specifically,

[0071] First: set the basic parameters of the genetic algorithm; set the value range of the air gap variable capacitor Cg and the air gap variable resistor Rg; the segmented calculation adopts the method of dividing the total simulation time into different time periods according to the different stages of the discharge state, and using the same time step method in the same stage;

[0072] Secondly, an initial population is created, and discharge region equivalent circuit parameters with a given population size and value range are randomly generated; thirdly, in the i-th time segment, according to the calculation step of S33, the optimal values ​​of the discharge region equivalent circuit parameters in the time segment and the state values ​​IL, UCd, UCg of the model elements L, Cd, Cg are calculated, and the state value at the end of each segment is assigned to the next segment as the initial state value;

[0073] Finally, the optimal values ​​of the simulated current value, air gap variable capacitance Cg, and air gap variable resistance Rg parameters in each time period are summarized into a data set that changes with time within the entire pulse, namely, the current fitting graph and the dynamic change trend graph of the equivalent circuit parameters Cg and Rg in the discharge area in the equivalent circuit model.

[0074] Furthermore, step five specifically includes the following steps:

[0075] S51: The temporal and spatial evolution of the discharge state in the discharge air gap is obtained through the temperature and luminescence images of the discharge space collected experimentally; the discharge state includes uniform discharge, filamentary discharge, single current pulse discharge, multi-current pulse discharge, and discharge extinction; the particle concentration and charge distribution in the discharge space are measured by the experimental platform to analyze the temporal and spatial variation characteristics of gas excitation, ionization, and reaction of DBD during the discharge process;

[0076] S52: According to the process of the optical and particle characteristics obtained in step S51 changing with time, the accuracy of the dynamic changes of the equivalent circuit parameters of the discharge region in the equivalent circuit model obtained in step 4 can be evaluated; specifically, the association between the equivalent circuit parameters Cg and Rg of the discharge region of the equivalent circuit model and the optical and particle characteristics is established; the association includes that the Rg parameter can reflect the spatiotemporal distribution change of the electron density in space, and the Cg parameter can reflect the spatiotemporal distribution of the relative positions of the positive and negative charges in space; according to the association, the consistency between the dynamic changes of the parameters in the equivalent circuit model and the trend of the experimental results can be qualitatively evaluated;

[0077] S53: According to the changes in the parameters of the equivalent circuit model and the experimental results, the process of conversion of different discharge states of DBD is analyzed; the different discharge states of DBD include the displacement current segment and discharge process segment at the rising and falling edges of the nanosecond pulse, the pulse voltage output stable segment, and the pulse-free voltage output segment; the process includes judging the conversion time points of different discharge states based on the dynamic changes of the observed air gap, the voltage across the medium, and the equivalent circuit parameters of the discharge area, and then summarizing the mechanism and influencing factors of the DBD development process. Specific embodiment:

[0079] The experimental platform constructed in this embodiment is as shown in the attached Figure 3As shown, the flat DBD used is used for illustration; the high voltage electrode of the flat DBD device is a copper column with a diameter of 32mm and a height of 40mm. In order to reduce the edge effect, the front end of the copper column is chamfered by 2mm. The blocking medium is a polytetrafluoroethylene shell with an inner diameter of 32mm, an outer diameter of 50mm, and a thickness of 1.8mm to cover the copper column. The metal electrode is used as the grounding electrode, and the distance between it and the high voltage electrode is 0 and 1mm. Under the conditions of different experimental parameters, according to the experiments of electricity, optics, particle characteristics, etc., the voltage and current waveforms are collected, the ICCD takes the luminous images, collects the spectral information, and the particle detection data. In practical applications, the corresponding acquisition tools are selected according to the accuracy of the experiment or other requirements. For example, Fourier transform infrared absorption spectrometer and laser induced fluorescence spectroscopy can be used to quantitatively measure the spatiotemporal distribution of ground state particles, and ICCD and emission spectrometer can be used to qualitatively measure the spatiotemporal distribution of excited state particles.

[0080] This embodiment uses Simulink simulation software to establish a typical structure of a flat DBD. Figure 5 The static and dynamic equivalent circuit models of the two cases with and without a discharge air gap are shown. The static equivalent circuit model without a discharge air gap includes the lead resistance Rw, parasitic inductance L and dielectric capacitance Cd; the dynamic equivalent circuit model with a discharge air gap also includes the air gap variable capacitance Cg and the air gap variable resistance Rg. When the external applied voltage exceeds the air gap breakdown voltage, the discharge in the DBD air gap generates plasma, and the gas in the air gap is ionized to form a large number of fine fast pulse discharge channels. At this time, the air gap variable capacitance Cg and the air gap variable resistance Rg will show nonlinear changes with the discharge process.

[0081] The experimental data of electrical characteristics obtained in the DBD experiment without a discharge air gap are combined with the corresponding DBD static equivalent circuit model in the simulation platform, and the genetic algorithm is used to solve the values ​​of the inherent parameters Rw, L, and Cd; then the values ​​of the inherent parameters are substituted into the dynamic equivalent circuit model, and combined with the experimental data of electrical characteristics obtained in the DBD experiment with a discharge air gap, the dynamic change simulation results of the discharge area equivalent circuit parameters air gap variable capacitance Cg and air gap variable resistance Rg are obtained, specifically:

[0082] First, calculate the inherent parameters of lead resistance Rw, parasitic inductance L, and dielectric capacitance Cd when DBD has no air gap. Set the basic parameters of the genetic algorithm; including setting the value ranges of the inherent parameters Rw, L, and Cd to 0.1~1000 (Ω), 0.1*1e-6~100*1e-6 (H), 0.1*1e-12~100*1e-12 (F), the binary bit size of the inherent parameter encoding is 10, the population size is 80, the genetic generation is 100, the gene selection probability GGAP is 0.9, the crossover probability pc is 0.8, and the mutation probability pm is 0.1;

[0083] Secondly, an initial population is created to randomly generate intrinsic parameters with a given population size and value range; after selection, crossover, and mutation, the intrinsic parameter values ​​generated each time are substituted into Simulink, and the static equivalent circuit model built in Simulink is run in parallel through MATLAB code to obtain the simulated current variation over time of the equivalent circuit under different intrinsic parameters Rw, L, and Cd; finally, the error value F between the simulated current and the experimental current variation over time is calculated according to the following formula, and the current error value F is used as the objective function:

[0084]

[0085] Where: n is the total number of sampling time points in this experiment; I exp (i) is the experimental current at the i-th sampling time point, I sim (i) is the analog current at the i-th sampling time point. The oscilloscope sampling time interval in this embodiment is 4ns; through continuous iteration, when the objective function value is the minimum, the optimal values ​​of the inherent parameters Rw, L, and Cd obtained in this embodiment are 132.8297Ω, 5.8258μH, and 25.4521pF, respectively.

[0086] Then, the optimal values ​​of the inherent parameters Rw, L, and Cd obtained when there is no air gap are substituted into the dynamic equivalent circuit model with an air gap of 1 mm. On the basis of ensuring the accuracy of the segmented simulation, in order to reduce the time spent, the population size is set to 30, the variable binary bit is 10, and the value ranges of the air gap equivalent capacitance Cg and the air gap equivalent resistance Rg are: 0.01*1e-12~200*1e-12(F), 0.1~10000(Ω); the maximum number of iterations is preferably set to 40. According to the different stages of the DBD discharge state, the total simulation time is numerically fitted in different time periods. The dynamic change process of the discharge area equivalent circuit parameters and the component state value of the corresponding DBD dynamic equivalent circuit model over time is obtained in the time periods corresponding to the different stages of the discharge state: the displacement current segment at the rising and falling edges of the nanosecond pulse uses a time step of 16ns as the simulation time step of this stage; in the process from the beginning of discharge to the end of discharge, the parameter changes are relatively large, so the time step of 12ns is used as the simulation time step of this stage; in the pulse voltage output stable section and the pulse-free voltage output section, the parameter changes are not large, so the time step of 280ns ​​is used as the simulation time step of this stage. When segmenting, the simulation stop condition can be set to reach the maximum number of iterations or the objective function value converges to the threshold or below. Since L, Cd, and Cg have state values ​​in the model, it is necessary to assign the value at the end of each segment to the next segment as the initial value. Finally, the optimal values ​​of the segmented parameters are summarized as a whole.

[0087] Finally, if Figure 6 As shown in the figure, the simulation results also show the dynamic change trend of the component parameters Cg (left) and Rg (middle) in the equivalent circuit model and the final current fitting diagram (right). In the process, it may be found that there are small ripples in the experimental voltage waveform, which is a non-standard output voltage waveform caused by stray resistance and inductance in the circuit.

[0088] According to the dynamic changes of the inherent parameters and equivalent circuit parameters of the discharge area obtained from the above simulation, the experimental results of the optical properties and the experimental results of the particle properties, the DBD development process mechanism and influencing factors are analyzed from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge mode conversion, and finally the DBD mechanism characteristics are explored.

[0089] In this embodiment, the nanosecond pulse output voltage of the high voltage power supply is 9 kV and the frequency is 1 kHz. Figure 7 The figure shows the discharge process of nanosecond pulse DBD. As shown in the figure, the displacement current is dominant in the total current a stage, and the displacement current density Where ε0 is the dielectric constant of vacuum, ε r is the relative dielectric constant of the medium. At this time, the Cg value is around 40pF, the Rg value has reached the upper limit, and the two do not change much. It can be understood that the external electric field is not strong enough, the gas is basically not ionized, the number of charges in the air gap is very small, and the movable charges are very small.

[0090] When the applied voltage continues to increase, discharge occurs, the gas is ionized, and the total current enters stage b. At this time, Rg suddenly decreases to tens of ohms, and Cg gradually increases to the upper limit of 200pF. This is because at this time, the electrons, ions, excited atoms, and oxygen- and nitrogen-containing active molecules generated by the discharge in the air gap increase sharply. Under the action of the external field strength, a large number of electrons obtain sufficient energy to accelerate to the instantaneous anode, and collide with surrounding molecules on the way, which promotes the development of electron avalanche, resulting in rapid expansion and overlap of the discharge channel, and the diffusion of plasma in the gap, which can be regarded as a decrease in Rg. Due to the great displacement of the positive and negative charge centers in the air gap, the charge distribution changes significantly, the dipole moment increases, and the polarization effect is significant, thereby increasing the air gap dielectric constant, and Cg increases. In addition, compared with the high-speed migrating electrons, the positive ions move relatively slowly to the cathode. This difference in migration speed leads to the formation of a positive ion-enriched area near the cathode, which is the cathode sheath. Electrons are accelerated by the strong electric field near the cathode, and the electron density may form a peak.

[0091] After the electron avalanche expands to the entire air gap, the discharge quickly extinguishes. The internal electric field established during the discharge offsets the external electric field, resulting in a field strength that is insufficient to maintain the discharge, and the total current enters the c stage. Charged particles gradually recombine and diffuse, and charges are injected or deposited on the surface of the material. The number of charges decreases, thereby reducing the conductivity. These processes are equivalent to a gradual increase in Rg. Since the dipole moment μ = qd (q and d represent the charge center and the distance between the positive and negative charge centers, respectively), the polarization effect is weakened, the air gap dielectric constant decreases, and therefore Cg gradually decreases.

[0092] The trend of Cg and Rg changes during the falling edge is similar to that during the rising edge. Stage d shows the charge distribution before the second discharge. After the first discharge, there is residual charge on the surface of the dielectric and in the gap. As the applied voltage decreases, the electrons are accelerated toward the ground electrode due to the reverse electric field of the residual charge on the surface, resulting in secondary discharge, ionization, and electron avalanche, entering stage e. After the second discharge, the external applied voltage is basically 0, and the residual charge recombines and diffuses again.

[0093] Through the above process, combined with the experimental platform to collect the optical characteristics and particle characteristics of DBD, the rationality of the dynamic changes of the air gap variable resistance and air gap variable capacitance in the discharge area equivalent circuit parameters in the simulation results during the entire pulse time and the accuracy of the DBD equivalent circuit model were verified; combined with the changes in the equivalent circuit parameters in the discharge area, the mechanism and influencing factors of the DBD development process can also be analyzed more clearly from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge state conversion. This dynamic simulation method of the dielectric barrier discharge development process based on the equivalent circuit model can also be applied to the simulation and emulation research of other power supply conditions and different discharge forms, simplifying the complex work of experimental diagnosis.

[0094] Although the present invention has been disclosed as above in terms of preferred embodiments, they are not intended to limit the present invention. Anyone skilled in the art can make various changes or modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection defined by the claims of this application.

Claims

1. A dynamic simulation method for the development process of dielectric barrier discharge based on an equivalent circuit model, characterized by: The following steps are involved: Step 1: Building a DBD experimental platform; the DBD experimental platform is used to conduct experiments of different DBD types, analyze experimental phenomena, and obtain experimental data of corresponding electrical properties, optical properties, and particle properties under different experimental conditions; Step 2: construct a DBD equivalent circuit model in a software simulation platform; the DBD equivalent circuit model includes static equivalent circuit models and dynamic equivalent circuit models of different DBD types, which are used to simulate the DBD experiment by numerical fitting to obtain the inherent parameters corresponding to the DBD experiment and the dynamic change simulation results of the equivalent circuit parameters of the discharge area; Step 3: Substitute the experimental data of electrical characteristics obtained in the DBD experiment without a discharge air gap into the corresponding DBD static equivalent circuit model in the simulation platform, set the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to solve the inherent parameters in the DBD static equivalent circuit model; Step 4: Change the DBD experimental conditions in step 3 to the presence of a discharge air gap, and obtain the experimental data of the electrical characteristics at this time; bring the inherent parameters solved in step 3 into the corresponding DBD dynamic equivalent circuit model, change the simulation parameter values ​​and conditions, and use the preset intelligent algorithm to segment the total simulation time, and numerically fit to solve the simulation results of the dynamic changes of the equivalent circuit parameters in the discharge area in the DBD dynamic equivalent circuit model; Step 5: Compare the simulation results of the dynamic changes of the inherent parameters obtained in step 3 and the equivalent circuit parameters of the discharge area obtained in step 4 with the experimental data of the optical properties and particle properties obtained experimentally. This allows the DBD development process mechanism and influencing factors to be analyzed from the perspectives of space charge dissipation and recombination, particle concentration changes, and discharge mode conversion, and ultimately the DBD mechanism characteristics can be explored.

2. The method for dynamic simulation of dielectric barrier discharge development process based on equivalent circuit model according to claim 1, characterized in that: The electrical characteristics are the data of DBD voltage and current changing with time, i.e., the current and voltage waveforms; the optical characteristics are the temperature of the discharge space, the shape of the luminous image, and the light intensity; the particle characteristics are the discharge space spectrum information and the spatial charge distribution; The DBD experimental platform collects voltage and current waveforms through voltage and current sensors and oscilloscopes; captures luminous images of the discharge space and measures the light intensity thereof through one or more of ICCD, thermal imager, digital camera, and photomultiplier tube; Measuring the discharge spatial spectrum information and spatial charge distribution by one or more of ICCD, emission spectrometer, Fourier transform infrared absorption spectrometer, laser induced fluorescence spectroscopy, and Langmuir probe; The different experimental conditions include different power supply parameters, different air gap distances, and different dielectric materials.

3. The method for dynamic simulation of dielectric barrier discharge development process based on equivalent circuit model according to claim 2 is characterized in that: The different DBD types include flat DBD, suspended electrode DBD, surface DBD and DBD type jet; in step 2, the discharge channel in the DBD dynamic equivalent circuit model includes an RC circuit composed of a parallel air gap variable capacitor Cg and an air gap variable resistor Rg, a dielectric capacitor Cd, a high voltage electrode and a grounding electrode; a discharge channel is formed between the high voltage electrode and the grounding electrode; the dielectric capacitor Cd in the discharge channel of the flat DBD and the suspended electrode DBD is connected in series with the RC circuit, while the grounding electrode of the suspended electrode DBD is the object to be directly processed and is considered to be connected to the ground during analysis; there is also a dielectric capacitor Cd1 between the high voltage electrode and the discharge channel in the discharge channel of the surface DBD and the dielectric capacitance Cd2 between the high-voltage electrode and the grounding electrode, wherein Cd1 is connected in series with the RC circuit and then connected in parallel with Cd2; in the DBD type jet, in addition to the dielectric capacitance Cd being connected in series with the RC circuit, the body feather discharge part is equivalent to a second RC circuit formed by the body feather variable capacitance Cp and the body feather variable resistance Rp and connected in parallel with Cd; the DBD equivalent circuit model also includes an RL equivalent circuit located in series between the discharge channel and the high-voltage power supply; the RL equivalent circuit is a lead resistance Rw connected in series with a parasitic inductance L; the DBD dynamic equivalent circuit model is a DBD static equivalent circuit model when there is no discharge air gap, and the RC circuit in the circuit is removed when analyzing the DBD static equivalent circuit model.

4. The method for dynamic simulation of dielectric barrier discharge development process based on equivalent circuit model according to claim 3 is characterized in that: In step three, the preset intelligent algorithm is a genetic algorithm, which reads the experimental data of voltage and current changing with time obtained from the DBD experimental platform from the MATLAB software, builds the corresponding DBD static equivalent circuit model and sets the parameters and conditions of the model and simulation, and obtains the simulation data of current changing with time under the excitation of the experimental voltage data by numerical fitting, obtains the minimum error value between the simulated current and the experimental current by continuous iterative calculation, and obtains the optimal value of the corresponding inherent parameters at this time; the inherent parameters include the lead resistance Rw, the parasitic inductance L and the dielectric capacitance Cd, and when simulating the surface DBD, the inherent parameters include the lead resistance Rw, the parasitic inductance L, the dielectric capacitance Cd1 and Cd2; specifically includes the following steps: S31: Using the DBD experimental platform built in step 1, conduct experiments with different types of DBDs without discharge air gaps under different experimental conditions; collect data on the change of voltage and current over time in the experiment through an oscilloscope with a preset sampling rate and a voltage and current sensor, the data being the voltage and current values ​​of the corresponding experiment at different sampling time points, and read these data using MATLAB software; S32: Calling Simulink simulation software to build a static equivalent circuit model of DBD in the absence of a discharge air gap, and sequentially setting the corresponding Simulink simulation parameter values ​​and conditions under different experimental conditions through MATLAB code; the simulation parameter values ​​include simulation step type, step time, and voltage signal of the excitation source in the circuit; wherein the voltage signal of the excitation source in the circuit is the data of voltage variation over time obtained in the experiment in S31; the simulation condition is the end time of a single Simulink simulation, that is, the total duration of a single experimental data; S33: A genetic algorithm framework is built in MATLAB to calculate the inherent parameters when the DBD has no discharge air gap, and obtain the optimal values ​​of the lead resistance Rw, parasitic inductance L and dielectric capacitance Cd; the specific process is as follows: First, the basic parameters of the genetic algorithm are set, including the value range of the intrinsic parameters Rw, L, and Cd, the objective function F, the binary digit size of the intrinsic parameter encoding, the population size, the genetic generation, the gene selection, the crossover, the mutation probability, and the minimum allowable error of the numerical fitting; Secondly, an initial population is created, and intrinsic parameters with a given population size and value range are randomly generated; after selection, crossover, and mutation, the intrinsic parameter values ​​generated each time are substituted into Simulink, and the static equivalent circuit model built in Simulink is run through MATLAB code to obtain the data of the simulated current variation over time of the equivalent circuit under different intrinsic parameters Rw, L, and Cd; Finally, the error value F between the simulated current and the experimental current changing with time is calculated according to the following formula, and the current error value F is used as the objective function: In the above formula: n is the total number of all sampling time points in the experiment; is the experimental current at the i-th sampling time point, is the simulated current at the i-th sampling time point; through continuous iteration, when the objective function value is minimum, the corresponding inherent parameters Rw, L, Cd values ​​at this time are the optimal values ​​of the inherent parameters Rw, L, Cd.

5. The method for dynamic simulation of dielectric barrier discharge development process based on equivalent circuit model according to claim 4 is characterized in that: In step 4, the preset intelligent algorithm is a genetic algorithm; based on the DBD dynamic equivalent circuit model constructed in step 2 and the inherent parameters obtained in step 4, the total simulation time is numerically fitted in time periods according to different stages of the DBD discharge state, and the discharge area equivalent circuit parameters of the corresponding DBD dynamic equivalent circuit model and the dynamic change process of the component state value over time are obtained in the time periods corresponding to the different stages of the discharge state, and a current fitting diagram is fitted; the discharge area equivalent circuit parameters include air gap variable capacitance Cg and air gap variable resistance Rg, and when simulating DBD type jets, body feather variable capacitance Cp and body feather variable resistance Rp are also required; the component state value includes the inductor current IL, the voltage across the medium UCd, and the voltage across the air gap UCg; the specific process is: A genetic algorithm framework was built in MATLAB to segmentally calculate the discharge area equivalent circuit parameters of DBD with a discharge air gap under each experimental condition, that is, the dynamic changes of the air gap variable capacitance Cg and the air gap variable resistance Rg, and give the current fitting diagram; specifically, First: set the basic parameters of the genetic algorithm; set the value range of the air gap variable capacitor Cg and the air gap variable resistor Rg; the segmented calculation adopts the method of dividing the total simulation time into different time periods according to the different stages of the discharge state, and using the same time step method in the same stage; Secondly, an initial population is created, and the discharge area equivalent circuit parameters with a given population size and value range are randomly generated; Again, in the i-th sub-time period, according to the calculation step S33, the optimal values ​​of the equivalent circuit parameters of the discharge region in the sub-time period and the state values ​​IL, UCd, UCg of the model elements L, Cd, Cg are calculated, and the state value at the end of each section is assigned to the next section as the initial state value; Finally, the optimal values ​​of the simulated current value, air gap variable capacitance Cg, and air gap variable resistance Rg parameters in each time period are summarized into a data set that changes with time within the entire pulse, namely, the current fitting graph and the dynamic change trend graph of the equivalent circuit parameters Cg and Rg in the discharge area in the equivalent circuit model.

6. The method for dynamic simulation of dielectric barrier discharge development process based on equivalent circuit model according to claim 5 is characterized in that: Step 5 specifically includes the following steps: S51: The temporal and spatial evolution of the discharge state in the discharge air gap is obtained through the temperature and luminescence images of the discharge space collected experimentally; the discharge state includes uniform discharge, filamentary discharge, single current pulse discharge, multi-current pulse discharge, and discharge extinction; the particle concentration and charge distribution in the discharge space are measured by the experimental platform to analyze the temporal and spatial variation characteristics of gas excitation, ionization, and reaction of DBD during the discharge process; S52: According to the process of the optical and particle characteristics obtained in step S51 changing with time, the accuracy of the dynamic changes of the equivalent circuit parameters of the discharge region in the equivalent circuit model obtained in step 4 can be evaluated; specifically, the association between the equivalent circuit parameters Cg and Rg of the discharge region of the equivalent circuit model and the optical and particle characteristics is established; the association includes that the Rg parameter can reflect the spatiotemporal distribution change of the electron density in space, and the Cg parameter can reflect the spatiotemporal distribution of the relative positions of the positive and negative charges in space; according to the association, the consistency between the dynamic changes of the parameters in the equivalent circuit model and the trend of the experimental results can be qualitatively evaluated; S53: According to the changes in the parameters of the equivalent circuit model and the experimental results, the process of conversion of different discharge states of DBD is analyzed; the different discharge states of DBD include the displacement current segment and discharge process segment at the rising and falling edges of the nanosecond pulse, the pulse voltage output stable segment, and the pulse-free voltage output segment; the process includes judging the conversion time points of different discharge states based on the dynamic changes of the observed air gap, the voltage across the medium, and the equivalent circuit parameters of the discharge area, and then summarizing the mechanism and influencing factors of the DBD development process.

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