LC oscillation loop simulation method and system based on quality factor optimization

Abstract

The application discloses an LC oscillation loop simulation method and system based on quality factor optimization, belongs to the technical field of oscillation loop simulation, and has the advantages that a loop model is built, the quality factor of the loop model is calculated, a single-parameter influence principle is adopted to determine a more accurate loop parameter optimization range, the optimization efficiency is improved, the research and development cycle is shortened, and the test cost is reduced, a multi-parameter joint optimization principle is further adopted to select an optimal target parameter combination, the final target parameter combination is ensured to be excellent in simulation and capable of being actually implemented, reliable technical support is provided for structure and circuit optimization of a to-be-tested device, and the problems of low parameter optimization precision and poor efficiency of the to-be-tested device in a synthetic loop simulation experiment are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oscillation circuit simulation, in particular to an LC oscillation circuit simulation method and system based on quality factor optimization. BACKGROUND

[0002] The circuit breaker plays a role of control, protection and regulation in the power system. When the circuit breaker is disconnected, the entire power supply circuit is in a disconnected state, which will affect the normal work of the adjacent equipment and system, so the circuit breaker should be disconnected as little as possible to reduce the impact on the entire system. Therefore, a large number of breaking tests need to be carried out before the circuit breaker is put into operation to verify whether it can work normally under the most severe operating conditions of the power system.

[0003] At present, the synthetic circuit method has become an effective method for detecting the breaking capacity of various circuit breakers. It improves the convenience and economy of the experiment, and also ensures its equivalence. By using high-voltage synthetic circuit experiments to verify the breaking performance of high-voltage circuit breakers, not only the breaking capacity of the circuit breaker is tested, but also the performance indicators of the circuit breaker product are provided with good judgment basis and improvement basis. Moreover, the synthetic circuit method has low investment, good flexibility, simple operation, wide TRV adjustment range, and can accurately judge the breaking capacity of the circuit breaker, which has great economic value and application value.

[0004] The quality factor (Q value) is a key parameter for measuring the energy loss of the LC oscillation circuit. The higher the Q value, the smaller the circuit loss, the slower the oscillation decay, and the closer the waveform to the ideal sine wave. Low Q value will cause the circuit current to decay rapidly. Q value affects the accuracy of the experiment, and in synthetic tests, Q value needs to match the actual system transient characteristics, so in the design of synthetic circuit tests, a high-precision and high-efficiency Q value simulation calculation method is needed.

[0005] Chinese patent, publication number: CN114626329A, publication date: June 14, 2022, discloses a wireless charging coil simulation method, system and storage medium, which simulates a plurality of coupling coefficients, a plurality of first quality factors of the transmitting coil and a plurality of second quality factors of the receiving coil according to the first size data set of the transmitting coil and the second size data set of the receiving coil; determines the first size data when the number of transmitting coils is one and the second size data when the number of receiving coils is one according to the plurality of coupling coefficients, the plurality of first quality factors and the plurality of second quality factors; and simulates and determines the first physical parameter of the transmitting coil and the second physical parameter of the receiving coil according to the preset coupling transmission simulation model, the first size data and the second size data. Although the physical parameters of the transmitting coil are determined according to the quality factor, the influence of the parameters in the actual connected circuit on the quality factor is not considered. SUMMARY

[0006] The present application is directed to the problem of low parameter optimization accuracy and poor efficiency of the device under test in the synthesis loop simulation experiment, and provides an LC oscillation loop simulation method and system based on quality factor optimization, by building a loop model and calculating the quality factor of the loop model, and using the single parameter influence principle to determine a more accurate loop parameter optimization range, thereby improving the optimization efficiency, shortening the research and development cycle and reducing the test cost, and then using the multi-parameter joint optimization principle to select the best target parameter combination, ensuring that the final target parameter combination is excellent in simulation and can be actually landed, thereby providing reliable technical support for the structure and circuit optimization of the device under test.

[0007] In a first aspect, a technical solution provided in an embodiment of the present application is: an LC oscillation loop simulation method based on quality factor optimization, comprising the following steps:

[0008] S1, a circuit breaker three-dimensional model is constructed based on the actual structure of the circuit breaker to be tested; the circuit breaker three-dimensional model is connected to an LC oscillation loop to construct a loop model;

[0009] S2, the loop parameters in the loop model are adjusted based on the single parameter influence principle, and the operating parameters of the corresponding adjusted loop model are collected;

[0010] S3, the correlation between the loop parameters and the operating parameters is determined based on the loop parameter optimization mechanism to determine the loop parameter optimization range;

[0011] S4, based on the multi-parameter joint optimization principle, the quality factor simulation values of the loop parameters with different values in the loop parameter optimization range are calculated to obtain a parameter simulation combination;

[0012] S5, based on the target quality factor, a candidate parameter combination is selected from the parameter simulation combination, the candidate parameter combination is evaluated to obtain a target parameter combination, and the circuit breaker to be tested is optimized based on the target parameter combination.

[0013] In the scheme, by constructing a loop model according to the actual structure of the to-be-tested device, distortion of the simulation result caused by excessive simplification of the model or large deviation from the actual structure is avoided, a real and reliable basis is provided for subsequent quality factor optimization, and the optimization direction is ensured to be consistent with the actual engineering requirements; by the single-parameter influence principle, the influence law of each type of parameter on the quality factor, current decay and oscillation frequency can be accurately located, so that the quantitative relationship between the parameter change and the performance influence is determined, a reliable basis is provided for the determination of the subsequent optimization range, and analysis confusion caused by the simultaneous change of multiple parameters is avoided; by determining the loop parameter optimization range, the invalid interval with no significant performance fluctuation caused by parameter change is eliminated, thereby reducing the calculation amount of subsequent multi-parameter joint optimization, and significantly saving the simulation time and computing resources; through multi-parameter joint optimization, local optimization caused by single-parameter optimization is avoided, and multiple indexes such as the quality factor and current characteristics are ensured to meet the target requirements at the same time, so that the overall performance consistency of the LC oscillation loop is improved.

[0014] As preferred, in S1, a circuit breaker three-dimensional model is constructed based on the actual structure of the to-be-tested circuit breaker, including the following steps:

[0015] The circuit breaker structure parameters are obtained based on the core conductive structure and arc extinguishing related structure of the to-be-tested circuit breaker, and the circuit breaker three-dimensional model is constructed based on the circuit breaker structure parameters using a preset proportion;

[0016] The structure parameters include the circuit breaker diameter, circuit breaker opening distance, arc diameter and contact material parameters.

[0017] In the scheme, the circuit breaker diameter, opening distance, arc diameter and contact material are selected as key factors directly affecting the LC oscillation loop characteristics, wherein the circuit breaker diameter determines the loop distributed inductance, the opening distance is related to the electric field strength between the contacts, the arc diameter affects the arc extinguishing energy loss, and the conductivity and magnetic permeability of the contact material determine the skin effect and hysteresis loss; by accurately modeling the above parameters, the influence degree of parameter change on the quality factor, current decay and oscillation frequency can be quantified, so that the logic of single-parameter analysis and multi-parameter joint optimization is clearer, the subsequent optimization direction is completely consistent with the actual engineering requirements, and finally the parameters after simulation optimization can directly guide the design and test of the circuit breaker, greatly improving the research and development efficiency and reducing the trial and error cost.

[0018] As preferred, in S1, the circuit breaker three-dimensional model is connected to the LC oscillation loop to construct a loop model, including the following steps:

[0019] The circuit breaker three-dimensional model is equivalent to a loss resistance and an inherent inductance based on the circuit breaker structure parameters to obtain an equivalent circuit breaker, and the equivalent circuit breaker is connected to the LC oscillation loop to construct a loop model;

[0020] The LC oscillation loop comprises a current source capacitor, a current source inductor, a loop resistance and a control switch connected in series.

[0021] In the scheme, by equivalent modeling and selection of the LC oscillation loop, on the one hand, the complex circuit breaker three-dimensional model is equivalent to a loss resistance plus an inherent inductance, which can greatly simplify the calculation complexity, retain the core influence of the circuit breaker on the loop energy loss and inductance characteristics, avoid the low simulation efficiency caused by the direct access of the three-dimensional model, make the electrical characteristic analysis of the LC oscillation loop more efficient, and on the other hand, the LC oscillation loop is a classic and mature transient circuit topology, which can accurately simulate the oscillation decay process of the short-circuit current, and after being combined with the equivalent circuit breaker, the loop transient characteristics when the circuit breaker is connected can be truly reproduced, thereby providing a simulation carrier close to the engineering practice for subsequent quality factor calculation and parameter optimization, so as to ensure that the optimization direction is completely consistent with the actual test requirements.

[0022] As preferred, in S2, the loop parameters in the loop model are adjusted based on the single-parameter influence principle, and the operating parameters of the adjusted loop model are collected, including the following steps:

[0023] The loop parameters include circuit breaker structure parameters and circuit parameters, and the circuit parameters include current source capacitor value, current source inductor value and loop resistance value.

[0024] Within a preset adjustment range, one of the loop parameters is adjusted by a preset step size, and the other types of parameters remain unchanged.

[0025] The current value passing through the equivalent circuit breaker and the voltage value across the current source capacitor are collected in real time as the operating parameters of the loop model.

[0026] In the scheme, by using the single-parameter adjustment principle, the structure parameters and circuit parameters are adjusted step by step while keeping other parameters unchanged, which completely eliminates the coupling interference between parameters, accurately quantifies the independent influence of single parameter change on loop characteristics, and avoids the confusion of influence law caused by the simultaneous change of multiple parameters; by collecting the current value and capacitor voltage value in real time, these two types of data are the core basis for calculating the quality factor, analyzing the current decay coefficient and the oscillation frequency, and providing accurate and traceable data support for subsequent determination of parameter optimization range and development of multi-parameter joint optimization, so as to make the entire optimization process have clear quantitative basis, and greatly improve the reliability and pertinence of the optimization results.

[0027] As preferred, in S3, the loop parameter optimization range is determined based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism, including the following steps:

[0028] The characteristic index of the corresponding adjustment parameter is calculated based on the change of the operating parameter.

[0029] draw a relationship curve of the corresponding adjustment parameter and each characteristic index, and take the adjustment range of the corresponding adjustment parameter with the characteristic index value in the effective value range as the effective interval of the corresponding characteristic index;

[0030] Take the intersection of the effective intervals of multiple characteristic indexes of the same parameter to obtain the optimization range of the loop parameter.

[0031] In the scheme, by drawing the relationship curve, the quantitative correlation between the parameter and the performance can be intuitively presented, and the intersection of the effective intervals of multiple characteristic indexes of the same parameter can ensure that the optimization range meets the multi-dimensional requirements of the quality factor, the oscillation frequency and the attenuation coefficient, rather than a single index, thereby guaranteeing the comprehensive adaptability of the parameter combination; by accurately narrowing the optimization range of the loop parameter, not only can the invalid interval be eliminated, thereby greatly reducing the calculation amount and the simulation time of the subsequent multi-parameter joint optimization, but also the high-value parameter interval is locked for the subsequent joint optimization, so as to improve the pertinence and efficiency of the overall optimization, and ensure that the subsequent optimization focuses on the parameter range that can truly improve the loop performance, thereby guaranteeing the precision of the parameter optimization.

[0032] As a preferred, the characteristic index includes the current decay rate, the oscillation frequency and the quality factor.

[0033] As a preferred, in S4, the quality factor simulation value of the loop parameter with different values in the optimization range of the loop parameter is calculated to obtain the parameter simulation combination, including the following steps:

[0034] The loop parameter is regarded as a chromosome, each type of parameter in the loop parameter is regarded as a gene site, and the optimization range of the loop parameter is regarded as the numerical range of each gene site;

[0035] n groups of values are randomly extracted in the numerical range, and the quality factor simulation value of the loop parameter with the corresponding values is calculated, and the parameter combination composed of each group of values of the loop parameter and the corresponding quality factor simulation value is taken as an initial population;

[0036] The genetic algorithm is adopted to perform the crossover and mutation operations on the initial population and iterated under the preset termination condition to obtain the parameter simulation combination.

[0037] In the scheme, by adopting a genetic algorithm, the circuit parameters are encoded as the structure of chromosomes and gene sites, which cleverly adapts to the multi-parameter joint optimization scene, allowing the structural parameters and the circuit parameters to participate in optimization together, breaking the limitations of traditional single-parameter optimization, and laying the foundation for achieving global optimization. By generating an initial population, the optimization range can be fully covered while ensuring population diversity and avoiding premature convergence caused by biased initial samples, thereby ensuring that the optimization process can explore more high-value parameter combinations. Through crossover and mutation operations, the parameter space can be efficiently traversed, thereby accurately finding the optimal parameter combination that takes into account multiple characteristic indicators, thereby significantly improving the optimization effect of the final parameter combination on actual equipment.

[0038] As a preferred, in S5, the candidate parameter combination is selected from the parameter simulation combination based on the target quality factor, including the following steps:

[0039] The deviation of the quality factor simulation value from the target quality factor is sorted from small to large for the parameter combinations in the parameter simulation combination, and the first i groups are taken as the candidate parameter combinations.

[0040] In the scheme, the quality factor is given the highest priority in screening, ensuring that the optimized equipment has low circuit energy loss.

[0041] As a preferred, in S5, the target parameter combination is obtained by evaluating the candidate parameter combinations, including the following steps:

[0042] The quality factor matching degree, process economy, and working condition stability are used as evaluation indicators to evaluate the candidate parameter combinations to obtain the index scores;

[0043] The index weights are obtained based on the Delphi analysis method, and the combination score is obtained by weighted summation based on the index weights;

[0044] The candidate parameter combination with the highest combination score is taken as the target parameter combination.

[0045] In the scheme, the quality factor matching degree, process economy, and working condition stability are used as evaluation indicators, which comprehensively cover the simulation performance and engineering practicality requirements, thereby avoiding focusing only on the quality factor during optimization and ignoring the impact during actual processing. By comprehensively analyzing the above indicators and performing weighted calculation, the advantages and disadvantages of the candidate combination can be quantified and compared, and the best target parameter combination is selected, thereby ensuring that the core performance of the LC oscillation circuit meets the standards, and the process cost and working condition adaptability are also considered, ensuring that the optimization result is excellent and practical, and can directly guide engineering practice.

[0046] In a second aspect, the technical scheme provided in the embodiment of the present application is an LC oscillation loop simulation system based on quality factor optimization, which comprises a model generation module, a single parameter adjustment module, a loop parameter optimization module, a multi-parameter joint optimization module and an evaluation module.

[0047] The model generation module constructs a circuit breaker three-dimensional model based on the actual structure of the circuit breaker to be tested, and inputs the circuit breaker three-dimensional model into an LC oscillation loop to construct a loop model.

[0048] The single parameter adjustment module adjusts the loop parameters in the loop model based on the single parameter influence principle, and collects the operating parameters of the loop model after adjustment.

[0049] The loop parameter optimization module determines the loop parameter optimization range based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism.

[0050] The multi-parameter joint optimization module calculates the quality factor simulation value corresponding to the loop parameter optimization range based on the multi-parameter joint optimization principle, and associates the loop parameters corresponding to the value to obtain a parameter simulation combination set.

[0051] The evaluation module selects a candidate parameter combination from the parameter simulation combination set based on the target quality factor, evaluates the candidate parameter combination to obtain a target parameter combination, and optimizes the circuit breaker to be tested based on the target parameter combination.

[0052] In this scheme, the simulation method in this scheme is carried by constructing a corresponding system, realizing human-computer interaction and improving the user's experience.

[0053] The present application has the following advantages: the present application builds a loop model and calculates the quality factor of the loop model, determines a more accurate loop parameter optimization range by using the single parameter influence principle, thereby improving the optimization efficiency, shortening the research and development cycle and reducing the test cost, selects the best target parameter combination by using the multi-parameter joint optimization principle, ensures that the final target parameter combination is excellent in simulation and can be actually implemented, and thereby provides reliable technical support for the structure and circuit optimization of the equipment to be tested.

[0054] The above summary of the application is only a summary of the technical scheme of the present application, in order to more clearly understand the technical means of the present application, the content of the specification can be implemented, and in order to make the above and other purposes, characteristics and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application are described below. BRIEF DESCRIPTION OF DRAWINGS

[0055] Other features, objects, and advantages of the application will become more apparent from the following detailed description when read in connection with the following drawings, in which like numerals designate like elements in the several figures. The drawings are intended to be illustrative, and not limiting of the application. Like numerals designate like elements in the several views.

[0056] Figure 1 A flow chart of a LC oscillation loop simulation method based on quality factor optimization;

[0057] Figure 2 A circuit schematic diagram of a loop model;

[0058] Figure 3 A schematic diagram of a LC oscillation loop simulation system based on quality factor optimization. DETAILED DESCRIPTION

[0059] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein merely illustrate the present application, and are used to explain the present application, and do not limit the protection scope of the present application. All other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0060] Before the example embodiments are discussed in more detail, it should be mentioned that some of the example embodiments are described as processes or methods depicted as flow diagrams. While the processes are described as sequential processes, many of the operations (or steps) can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations can be re-arranged. The processes can be terminated when their operations are completed, but can also have additional steps not included in the figure, can correspond to methods, functions, procedures, subroutines, subprograms, etc.

[0061] Embodiment 1: As shown in the figure, in order to solve the problem of low parameter optimization accuracy and poor efficiency of the to-be-tested device in the existing synthesis loop simulation experiment, a LC oscillation loop simulation method based on quality factor optimization is provided, comprising the following steps: Figure 1 S1: Constructing a circuit breaker three-dimensional model based on the actual structure of the to-be-tested circuit breaker; connecting the circuit breaker three-dimensional model to the LC oscillation loop to construct a loop model.

[0062] In this embodiment, the circuit breaker three-dimensional model is constructed based on the actual structure of the to-be-tested circuit breaker, comprising the following steps:

[0063]

[0064] ​The circuit breaker structure parameters are obtained based on the core conductive structure and arc extinguishing related structure of the to-be-tested circuit breaker, and a three-dimensional model of the circuit breaker is constructed based on the circuit breaker structure parameters and a preset ratio.

[0065] The structure parameters include a circuit breaker diameter, a circuit breaker opening distance, an arc diameter, and a contact material parameter.

[0066] Specifically, the parametric modeling function of Maxwell can be selected, a 1:1 scale three-dimensional parametric simulation model is constructed in Maxwell, the circuit breaker diameter, the circuit breaker opening distance, and the arc diameter are selected as the structure parameters, the three-dimensional model of the test equipment is adjusted by adjusting the structure parameter values, and the circuit breaker skin effect and magnetic hysteresis loss at different frequencies can be changed by changing the material of the circuit breaker contact, so that more accurate results are obtained in the simulation of the synthetic loop test, and the design of the synthetic loop test is more efficient.

[0067] In this embodiment, the circuit breaker diameter, the opening distance, the arc diameter, and the contact material are selected as key factors directly affecting the LC oscillation loop characteristics, wherein the circuit breaker diameter determines the loop distributed inductance, the opening distance is related to the electric field strength between the contacts, the arc diameter affects the arc extinction energy loss, and the conductivity and magnetic permeability of the contact material affect the skin effect and magnetic hysteresis loss. By precisely modeling the above parameters, the influence of parameter changes on the quality factor, current decay, and oscillation frequency can be quantified, so that the logic of single-parameter analysis and multi-parameter joint optimization is clearer, ensuring that the subsequent optimization direction is completely consistent with the actual engineering requirements, and finally the parameters after simulation optimization can directly guide the design and test of the circuit breaker, greatly improving the research and development efficiency and reducing the trial and error cost.

[0068] In this embodiment, the circuit breaker three-dimensional model is connected to the LC oscillation loop to construct a loop model, including the following steps:

[0069] Based on the circuit breaker structure parameters, the circuit breaker three-dimensional model is equivalent to a loss resistance and an inherent inductance to obtain an equivalent circuit breaker, and the equivalent circuit breaker is connected to the LC oscillation loop to construct a loop model.

[0070] The LC oscillation loop includes a current source capacitor, a current source inductor, a loop resistance, and a control switch connected in series.

[0071] Specifically, as shown in Figure 2 , the circuit breaker three-dimensional model is connected to the LC oscillation loop to construct a loop model, including the following steps: Figure 2The circuit (a) in the circuit (b) is a control circuit, the circuit (b) is a control loop, and the circuit (c) is a loop model, wherein the capacitor C is used for storing electric field energy, is an energy source of the oscillation loop, and the capacitance determines the peak value of the loop current; the resistor R is used for simulating the actual loss of the line, and the resistance directly affects the quality factor of the loop; the inductor L is used for storing magnetic field energy and determines the oscillation frequency together with the capacitor C; and the switch S is used for simulating the tripping and closing actions of the circuit breaker and is used for controlling the on-off time of the loop. The W1 on the right side of the loop model is an equivalent model of the constructed three-dimensional parameter model of the circuit breaker, which is equivalent to a three-tenth turn transverse magnetic contact being connected in series, and the inherent inductance and loss resistance thereof directly affect the oscillation characteristics of the loop. The voltmeter IUc is connected in parallel across the capacitor C and is used for collecting the capacitor voltage.

[0072] Figure 2 The circuit (b) is a control loop, which is used for driving the action of the switch S, wherein V11 is a 5V pulse source, which is used for outputting high and low level signals to control the on-off logic of the switch S; the resistor R5 is a current limiting resistor, which is used for protecting the pulse source and avoiding overcurrent damage; and the voltmeter IV6 is used for monitoring the voltage state of the control loop and ensuring the normal output of the pulse signal. The circuit (a) controls the circuit (b) through a preset control logic, wherein M1 is the core control unit of the entire control logic, which integrates trigger timing, logic judgment and other functions, and guarantees the timing matching of the switch action and the oscillation of the main loop.

[0073] In this embodiment, the equivalent modeling and the selection of the LC oscillation loop can simplify the calculation complexity on one hand, equivalently simplify the complex three-dimensional model of the circuit breaker into a loss resistance plus an inherent inductance, retain the core influence of the circuit breaker on the loop energy loss and inductance characteristics, avoid the low simulation efficiency caused by the direct access of the three-dimensional model, make the electrical characteristic analysis of the LC oscillation loop more efficient, and accurately simulate the oscillation decay process of the short-circuit current. After being combined with the equivalent circuit breaker, the loop transient characteristics when the circuit breaker is connected can be truly reproduced, a simulation carrier close to the engineering practice is provided for subsequent quality factor calculation and parameter optimization, and thus the optimization direction is completely matched with the actual test demand.

[0074] S2: adjusting the loop parameters in the loop model based on the single-parameter influence principle and collecting the operating parameters of the loop model after the adjustment.

[0075] In this embodiment, the loop parameters in the loop model are adjusted based on the single-parameter influence principle, and the operating parameters of the loop model after the adjustment are collected, including the following steps.

[0076] The loop parameters include circuit breaker structure parameters and circuit parameters, and the circuit parameters include a current source capacitance value, a current source inductance value and a loop resistance value.

[0077] In the preset adjustment range, one parameter in the loop parameter is adjusted in sequence with a preset step length, and other types of parameters remain unchanged.

[0078] The current value passing through the equivalent circuit breaker and the voltage value across the current source capacitor at each adjustment are collected in real time as the operating parameters of the loop model.

[0079] Specifically, the preset adjustment range is set to a contact diameter in the range of 20-60 mm, with an adjustment step length of 2 mm; a contact opening distance in the range of 5-30 mm, with an adjustment step length of 5 mm; an arc diameter in the range of 20-60 mm, with an adjustment step length of 2 mm, and not greater than the diameter of the circuit breaker; a capacitance value of the current source capacitor in the range of 5 mF-45 mF, with an adjustment step length of 2.5 mF; an inductance of the current source in the range of 10 uH-400 uH, with an adjustment step length of 10 uH; and a loop resistance value in the range of 1 mΩ-10 mΩ, with a step length of 1 mΩ.

[0080] By adopting the single-parameter adjustment principle and keeping other parameters unchanged, the structure parameters and circuit parameters are adjusted in steps one by one in this embodiment, completely eliminating the coupling interference between parameters, accurately quantifying the independent influence of single parameter change on the loop characteristics, and avoiding the confusion of influence rules caused by multiple parameter changes. By collecting the current value and the capacitor voltage value in real time, these two types of data are the core basis for calculating the quality factor, analyzing the current decay coefficient and the oscillation frequency, and providing accurate and traceable data support for subsequent determination of parameter optimization range and development of multi-parameter joint optimization, so that the entire optimization process has a clear quantitative basis, greatly improving the reliability and pertinence of the optimization results.

[0081] S3: determining a loop parameter optimization range based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism.

[0082] In this embodiment, the loop parameter optimization range is determined based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism, including the following steps:

[0083] Calculate the characteristic index of the corresponding adjustment parameter based on the change of the operating parameter; the characteristic index includes the current decay rate, the oscillation frequency and the quality factor;

[0084] Draw the relationship curve of the corresponding adjustment parameter and each characteristic index, and take the adjustment range of the corresponding adjustment parameter with the characteristic index value in the effective value range as the effective interval of the corresponding characteristic index.

[0085] Take the intersection of the effective intervals of multiple characteristic indexes of the same parameter to obtain the loop parameter optimization range.

[0086] Specifically, the calculation process of the quality factor is as follows:

[0087] ;

[0088] wherein U0 is the initial capacitor voltage, and U1 is the capacitor voltage after one period;

[0089] The calculation process of the oscillation frequency of the current is as follows:

[0090] ;

[0091] wherein L is the inductance value of the current source, and C is the capacitance value of the current source;

[0092] The theoretical formula for the change of the current in the loop with respect to time is as follows:

[0093] ;

[0094] When , the current loop can reach a maximum value:

[0095] ;

[0096] The current decay rate is a coefficient for describing the speed of the decay of the current amplitude, and can be obtained by comparing the actual change value of the current with the theoretical value.

[0097] In the specific calculation, in order to improve the calculation efficiency, Maxwell can be combined with MATLAB for joint simulation, MATLAB can be used to calculate the characteristic indexes and draw the current value-time curve and the voltage value-current curve, and the parameters can be associated with the adjusted parameters.

[0098] In the parameter optimization process of the loop, taking the analysis of the diameter parameter of the circuit breaker as an example, the fixed opening distance is set to 15 mm, the arc diameter is set to 30 mm, C is set to 25 mF, L is set to 200 uH, and R is set to 5 mΩ, only the diameter is increased from 20 mm to 60 mm at a step of 2 mm, the oscillation frequency of the current, the current decay rate and the quality factor are recorded each time, and then the quality factor-diameter curve, the current decay rate-diameter curve and the oscillation frequency-diameter curve are drawn; as shown in the quality factor-diameter curve, when the diameter is 30-50 mm, the Q value increases linearly from 8.2 to 9.5; and when the diameter is 20-28 mm or 52-60 mm, the Q value is basically stable at 7.0 or 9.8 (obviously deviating from the target range), it is determined that 30-50 mm is the effective interval of the Q value; in the current decay rate-diameter curve, when the diameter is greater than 40 mm, the decay coefficient suddenly increases from 0.03 to 0.08 (exceeding the set threshold), and the diameter is less than or equal to 40 mm, which is the effective interval of the decay coefficient, and the intersection of the effective interval of the Q value and the effective interval of the decay coefficient is the parameter optimization range of the diameter, i.e. 30-40 mm; by repeating the verification of all parameters, the parameter optimization range of each parameter is finally obtained.

[0099] By drawing the relationship curve, the quantitative correlation between the parameters and the performance can be intuitively presented. The intersection of the effective intervals of multiple characteristic indexes of the same parameter can ensure that the optimization range meets the requirements of multiple dimensions such as quality factor, oscillation frequency and attenuation coefficient, rather than a single index, thereby ensuring the comprehensive adaptability of the parameter combination. By accurately narrowing the optimization range of the loop parameters, not only can the invalid interval be eliminated, thereby greatly reducing the calculation amount and simulation time of subsequent multi-parameter joint optimization, but also the high-value parameter interval is locked for subsequent joint optimization, so as to improve the pertinence and efficiency of the overall optimization, and ensure that the subsequent optimization focuses on the parameter range that can truly improve the performance of the loop, thereby ensuring the accuracy of the parameter optimization.

[0100] S4: Based on the multi-parameter joint optimization principle, the quality factor simulation value of the loop parameter with different values in the loop parameter optimization range is calculated to obtain a parameter simulation combination.

[0101] In the embodiment, the quality factor simulation value of the loop parameter with different values in the loop parameter optimization range is calculated to obtain a parameter simulation combination, including the following steps:

[0102] The loop parameters are regarded as chromosomes, the various parameters in the loop parameters are regarded as gene positions, and the loop parameter optimization range is regarded as the numerical range of each gene position.

[0103] n groups of values are randomly extracted in the numerical range, and the quality factor simulation value of the loop parameter with the corresponding values is calculated, as shown in the following table:

[0104] Table 1. Quality factor simulation value corresponding to loop parameter with different values:

[0105] ;

[0106] The parameter combination composed of each group of values of the loop parameters and the corresponding quality factor simulation value is used as the initial population.

[0107] The genetic algorithm is used to perform cross and mutation operations on the initial population and iterates under a preset termination condition to obtain the parameter simulation combination.

[0108] Specifically, the fitness function is set, and the formula is expressed as follows:

[0109] ;

[0110] wherein, is the value of a certain population, i.e. a certain loop parameter, is the corresponding quality factor simulation value under the value of the loop parameter, is the target quality factor, is the quality factor matching degree weight, to constrain the satisfaction degree weight, to constrain the satisfaction degree.

[0111] The embodiment ingeniously adapts the multi-parameter joint optimization scene by encoding the circuit parameters into the structure of chromosomes and gene sites by using the genetic algorithm, so that the structural parameters and the circuit parameters can participate in the optimization cooperatively, breaking the limitation of traditional single-parameter optimization, laying a foundation for realizing global optimization; by generating an initial population, the optimization range can be fully covered, while ensuring the diversity of the population and avoiding premature convergence caused by one-sided initial samples, so as to ensure that more high-value parameter combinations can be explored in the optimization process; through the crossover and mutation operations, the parameter space can be efficiently traversed, so that the optimal parameter combination considering multiple characteristic indicators can be accurately found, thereby greatly improving the optimization effect of the finally obtained parameter combination on the actual device.

[0112] The population X is introduced into the fitness function to obtain the fitness values of each population , and the populations are sorted in descending order of the fitness values.

[0113] The tournament selection algorithm is used to select the population, and the specific process is as follows: k individuals are randomly selected from the population as a tournament team, the individual with the highest fitness value in the team is selected, and the individual is put into the parent pool. After repeating the above steps N times, the crossover operation is performed.

[0114] The arithmetic crossover is used in the embodiment, and the specific crossover process is as follows:

[0115] The two parents are randomly paired from the parent pool, and the crossover probability is set For each pair of parents, a random number r between 0 and 1 is generated, and if , the crossover is performed, and the parent 1 is set as , the parent 2 is set as , and two offspring are generated:

[0116] ;

[0117] ;

[0118] Wherein is the crossover factor, i is the number of characteristic indicators, is the i-th characteristic indicator in the parent 1, is the i-th characteristic indicator in the parent 2;

[0119] If , the crossover is not performed, and the parent 1 and the parent 2 are directly used as the offspring.

[0120] The mutation operation in the embodiment uses Gaussian mutation, and the mutation process is as follows:

[0121] Set mutation probability , traverse each gene locus of each chromosome in the offspring population, and generate a random number r between 0 and 1, if then perform mutation, such as offspring 1 is , offspring 2 is , for gene locus , , wherein is a Gaussian random number with a mean of 0 and a standard deviation of , and is 1-2 times the parameter step size, such as the diameter step size of the circuit breaker is 1mm, then can be set to 1.5mm; if then no mutation is performed.

[0122] By inputting the offspring population obtained after crossover and mutation into the fitness function, the fitness value of each offspring is calculated, and the termination condition is verified, if the termination condition is not met, then continue iteration, the termination condition set in this embodiment includes the number of iterations, the change amount of the optimal fitness value in the population of the last 5 generations is less than or equal to the change threshold, and there is a certain individual whose quality factor simulation value deviates from the target quality factor by less than or equal to the deviation threshold, any one of the above is met, then terminate iteration.

[0123] S5: Selecting a candidate parameter combination from the parameter simulation combination based on the target quality factor, evaluating the candidate parameter combination to obtain a target parameter combination, and optimizing the to-be-tested circuit breaker based on the target parameter combination.

[0124] In this embodiment, the candidate parameter combination is selected from the parameter simulation combination based on the target quality factor, including the following steps:

[0125] The deviation of the quality factor simulation value from the target quality factor is sorted in ascending order for the parameter combinations in the parameter simulation combination, and the first i groups are taken as the candidate parameter combination.

[0126] Specifically, the first 10 individuals in the population obtained after terminating iteration are taken as the candidate parameter combination.

[0127] In this embodiment, the quality factor is taken as the highest priority for screening, which ensures that the finally optimized device has low loop energy loss.

[0128] In this embodiment, the candidate parameter combination is evaluated to obtain a target parameter combination, including the following steps:

[0129] The quality factor matching degree, process economy and working condition stability are taken as evaluation indexes to evaluate the candidate parameter combination to obtain scores of each index;

[0130] The index weight is obtained by weighting each index based on the Delphi analysis method, and the combination score is obtained by weighting and summing the scores of each index based on the index weight;

[0131] The candidate parameter combination with the highest combination score is taken as the target parameter combination.

[0132] In this embodiment, the quality factor matching degree, process economy and working condition stability are taken as evaluation indexes to comprehensively cover the simulation performance and engineering practicability requirements, so as to avoid only focusing on the quality factor during optimization and ignoring the influence during actual processing; through comprehensive analysis of the above indexes and weighted calculation, the advantages and disadvantages of the candidate combination can be quantified and compared, and the best target parameter combination is screened out, so as to not only ensure that the core performance of the LC oscillation loop meets the standards, but also take into account the process cost and working condition adaptability, so as to ensure that the optimization result is excellent and practical, and can directly guide engineering practice.

[0133] In this embodiment, the quality factor matching degree, process economy and working condition stability are taken as evaluation indexes to comprehensively cover the simulation performance and engineering practicability requirements, so as to avoid only focusing on the quality factor during optimization and ignoring the influence during actual processing; through comprehensive analysis of the above indexes and weighted calculation, the advantages and disadvantages of the candidate combination can be quantified and compared, and the best target parameter combination is screened out, so as to not only ensure that the core performance of the LC oscillation loop meets the standards, but also take into account the process cost and working condition adaptability, so as to ensure that the optimization result is excellent and practical, and can directly guide engineering practice. Figure 3

[0134] The model generation module constructs a circuit breaker three-dimensional model based on the actual structure of the circuit breaker to be tested, and connects the circuit breaker three-dimensional model to the LC oscillation loop to construct a loop model.

[0135] The single parameter adjustment module adjusts the loop parameters in the loop model based on the single parameter influence principle, and collects the operating parameters of the loop model after adjustment.

[0136] The loop parameter optimization module determines the loop parameter optimization range based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism.

[0137] The multi-parameter joint optimization module calculates the quality factor simulation value corresponding to the loop parameter optimization range based on the multi-parameter joint optimization principle, and associates the corresponding loop parameters to obtain a parameter simulation combination set.

[0138] The evaluation module screens out candidate parameter combinations from the parameter simulation combination set based on the target quality factor, and evaluates the candidate parameter combinations to obtain the target parameter combination. The circuit breaker to be tested is optimized based on the target parameter combination. By constructing the corresponding system, the simulation method in the present scheme is carried, human-computer interaction is realized, and the user's use experience is improved.

[0139] From the above embodiments, at least the following substantial effects are obtained:

[0140] ​(1) The application constructs a loop model according to the actual structure of the device to be tested, avoids the distortion of the simulation results caused by excessive simplification of the model or large deviation from the actual structure, provides a real and reliable basis for subsequent quality factor optimization, and ensures that the optimization direction is consistent with the actual engineering requirements;

[0141] (2) The application can accurately locate the influence law of each type of parameter on the quality factor, current attenuation and oscillation frequency according to the single parameter influence principle, thereby determining the quantitative relationship between the parameter change and the performance, providing a reliable basis for determining the subsequent optimization range, and avoiding the analysis confusion caused by the simultaneous change of multiple parameters;

[0142] (3) The application determines the optimization range of the loop parameters, eliminates the invalid interval with no significant fluctuation of performance caused by parameter change, thereby reducing the calculation amount of subsequent multi-parameter joint optimization, and significantly saving the simulation time and computing resources;

[0143] (4) The application avoids the local optimum caused by single parameter optimization through multi-parameter joint optimization, ensures that multiple indexes such as quality factor and current characteristics meet the target requirements at the same time, and thereby improves the overall performance consistency of the LC oscillation loop.

[0144] The above specific implementation mode is a preferred implementation mode of the LC oscillation loop simulation method and system based on quality factor optimization, and is not limited to the specific implementation range of the application. The scope of the application includes but is not limited to the specific implementation mode, and equivalent changes made according to the shape and structure of the application are within the protection scope of the application.

Claims

1. A method for simulating an LC tank based on quality factor optimization, characterized in that: The method comprises the following steps: S1, constructing a circuit breaker three-dimensional model based on the actual structure of the circuit breaker to be tested; and connecting the circuit breaker three-dimensional model to an LC oscillation circuit to construct a circuit model; S2, adjusting circuit parameters in the circuit model based on a single-parameter influence principle, and collecting operating parameters of the circuit model after the adjustment; S3, determining a circuit parameter optimization range based on the correlation between the circuit parameters and the operating parameters and according to a circuit parameter optimization mechanism; S4, calculating quality factor simulation values of the circuit parameters in the circuit parameter optimization range with different values based on a multi-parameter joint optimization principle to obtain a parameter simulation combination; S5, selecting a candidate parameter combination from the parameter simulation combination based on a target quality factor, evaluating the candidate parameter combination to obtain a target parameter combination, and optimizing the circuit breaker to be tested based on the target parameter combination.

2. The LC oscillation circuit simulation method based on quality factor optimization according to claim 1, wherein in S1, the circuit breaker three-dimensional model is constructed based on the actual structure of the circuit breaker to be tested, comprising the following steps: obtaining circuit breaker structure parameters based on the core conductive structure and arc extinguishing related structure of the circuit breaker to be tested, and constructing the circuit breaker three-dimensional model based on the circuit breaker structure parameters using a preset proportion; the structure parameters include a circuit breaker diameter, a circuit breaker opening distance, an arc diameter, and a contact material parameter.

3. The LC oscillation circuit simulation method based on quality factor optimization according to claim 2, wherein in S1, the circuit model is constructed by connecting the circuit breaker three-dimensional model to the LC oscillation circuit, comprising the following steps: equivalent circuit breakers are obtained by equivalently converting the circuit breaker three-dimensional model into a loss resistance and an inherent inductance based on the circuit breaker structure parameters, and the equivalent circuit breakers are connected to the LC oscillation circuit to construct the circuit model; the LC oscillation circuit comprises a current source capacitor, a current source inductor, a circuit resistance, and a control switch connected in series.

4. The LC oscillation circuit simulation method based on quality factor optimization according to claim 3, wherein in S2, the circuit parameters in the circuit model are adjusted based on the single-parameter influence principle, and operating parameters of the circuit model after the adjustment are collected, comprising the following steps: the circuit parameters include circuit breaker structure parameters and circuit parameters, and the circuit parameters include a current source capacitor value, a current source inductor value, and a circuit resistance value; in a preset adjustment range, one parameter in the circuit parameters is adjusted using a preset step size, and other types of parameters remain unchanged; the current value through the equivalent circuit breaker and the voltage value across the current source capacitor are collected in real time as the operating parameters of the circuit model.

5. The LC oscillation circuit simulation method based on quality factor optimization according to claim 1, wherein in S3, the circuit parameter optimization range is determined based on the correlation between the circuit parameters and the operating parameters and according to the circuit parameter optimization mechanism, comprising the following steps: characteristic indexes of the adjusted parameters are calculated based on the change of the operating parameters; a relationship curve of the adjusted parameters and the characteristic indexes is drawn, and an adjustment range of the adjusted parameters with the characteristic index values in the effective value range is taken as an effective interval of the corresponding characteristic index. ​ ​ ​ ​ The effective range of the multiple characteristic indexes of the same parameter is intersected to obtain a loop parameter optimization range.

6. The LC oscillation loop simulation method based on quality factor optimization according to claim 5, characterized in that: The characteristic indexes include current decay rate, oscillation frequency and quality factor.

7. The LC oscillation loop simulation method based on quality factor optimization according to claim 1, characterized in that: In S4, the quality factor simulation values of the loop parameters with different values in the loop parameter optimization range are calculated to obtain a parameter simulation combination, including the following steps: The loop parameters are regarded as chromosomes, each type of parameter in the loop parameters is regarded as a gene position, and the loop parameter optimization range is regarded as the numerical range of each gene position; n groups of values are randomly extracted in the numerical range, and the quality factor simulation values of the loop parameters with the corresponding values are calculated, and each parameter combination formed by the loop parameters with each group of values and the corresponding quality factor simulation values is taken as an initial population; The genetic algorithm is adopted to perform cross and mutation operations on the initial population and iterates under a preset termination condition to obtain the parameter simulation combination.

8. The LC oscillation loop simulation method based on quality factor optimization according to claim 1, characterized in that: In S5, candidate parameter combinations are selected from the parameter simulation combination based on the target quality factor, including the following steps: The deviations of the quality factor simulation values from the target quality factor are sorted from small to large for the parameter combinations in the parameter simulation combination, and the first i groups are taken as the candidate parameter combinations.

9. The LC oscillation loop simulation method based on quality factor optimization according to claim 1, characterized in that: In S5, the target parameter combination is obtained by evaluating the candidate parameter combinations, including the following steps: The quality factor matching degree, process economy and working condition stability are taken as evaluation indexes to evaluate the candidate parameter combinations to obtain index scores; The indexes are weighted based on the Delphi analysis method to obtain index weights, the index scores are weighted and summed based on the index weights to obtain a combination score; The candidate parameter combination with the highest combination score is taken as the target parameter combination.

10. A simulation system of LC tank based on quality factor optimization, which is suitable for the simulation method of LC tank based on quality factor optimization in any one of claims 1-9, characterized in that: The model generation module, single parameter adjustment module, loop parameter optimization module, multi-parameter joint optimization module and evaluation module are included. The model generation module constructs a circuit breaker three-dimensional model based on the actual structure of the circuit breaker to be tested, and connects the circuit breaker three-dimensional model to an LC oscillation loop to construct a loop model. The single parameter adjustment module adjusts the loop parameters in the loop model based on the single parameter influence principle, and collects the operating parameters of the corresponding adjusted loop model. The loop parameter optimization module determines the loop parameter optimization range based on the correlation between the loop parameters and the operating parameters and according to the loop parameter optimization mechanism. The multi-parameter joint optimization module calculates the corresponding quality factor simulation values in the loop parameter optimization range based on the multi-parameter joint optimization principle, and associates the quality factor simulation values with the corresponding loop parameters to obtain a parameter simulation combination set. The evaluation module selects candidate parameter combinations from the parameter simulation combination set based on the target quality factor, evaluates the candidate parameter combinations to obtain a target parameter combination, and optimizes the circuit breaker to be tested based on the target parameter combination.

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