A multi-objective optimization method for the dynamic characteristics and structure of solenoid valves using an equivalent magnetoresistive model database.

Abstract

This invention discloses a multi-objective optimization method for the dynamic characteristics and structure of solenoid valves using an equivalent magnetoresistive model database, relating to the field of solenoid valve optimization. This invention performs electromagnetic simulation on solenoid valves requiring structural optimization to obtain the solenoid valve's magnetic circuit; it then divides the magnetic circuit using the equivalent magnetoresistive model database to obtain an equivalent magnetoresistive model; furthermore, by analyzing the dynamic characteristics of the solenoid valve, a magnetoresistive simulation model is established; using the volume and dynamic characteristics of the solenoid valve as optimization objectives and structural parameters as optimization variables, within feasible variable constraints, a genetic optimization algorithm is used for multi-objective optimization to obtain a series of solenoid valve structural parameters under different dynamic characteristics. This invention utilizes the relationship between the structural parameters of the solenoid valve and the equivalent magnetoresistive model to establish a corresponding optimization objective function, applicable to different loading methods of the solenoid valve, and can optimize the dynamic characteristics and volume of the solenoid valve.

Description

Technical Field

[0001] This invention relates to the field of solenoid valve optimization, and more particularly to a method for optimizing the structure of solenoid valves. Specifically, it relates to a multi-objective optimization method for the dynamic characteristics and structure of solenoid valves using an equivalent magnetoresistive model database. Background Technology

[0002] Solenoid valves, with their simple structure, are used in industrial control systems to adjust the direction, flow rate, speed, and other parameters of the medium. In the wave of "Internet+" and big data, digitalization and intelligentization are rapidly approaching all industries, placing higher demands on the accuracy and reliability of systems. Solenoid valves, with their advantages of simple operation, large thrust, and no pollution, are widely used in automatic control, pneumatic transmission, and hydraulic transmission, playing a crucial role in determining the characteristics of the system.

[0003] The dynamic response of a solenoid valve is a crucial indicator of its performance, directly impacting the control accuracy and effectiveness of the control system. A slow dynamic response increases system uncertainty and reduces overall control precision. However, solenoid valves used in rockets, aircraft, and other applications face stringent requirements for miniaturization, weight reduction, and reliability, necessitating small, high-speed solenoid valves with high response frequencies. Many solenoid valves struggle to simultaneously meet both high performance and small size requirements. Therefore, it is essential to simplify the solenoid valve structure and improve its dynamic performance within limited size and weight constraints.

[0004] Currently, multi-objective optimization of solenoid valves mainly focuses on the following aspects. For example, developing solenoid valves using novel materials, such as polymer materials and cobalt-iron-vanadium alloys, but this significantly increases production costs, hindering large-scale production. Secondly, experimental design methods are used to obtain the relationship between structural parameters and dynamic characteristics; however, this relationship is based on fitting experimental data and only applies to the loading conditions under experimental conditions, failing to represent general situations. Thirdly, optimization is achieved using corresponding multi-objective simulation software; however, the software itself offers little optimization of the solenoid valve's structural parameters, mainly focusing on optimizing the solenoid valve's air gap, spring coefficient, and valve core mass. Summary of the Invention

[0005] To address the problems in the prior art, this invention proposes a multi-objective optimization method for the dynamic characteristics and structure of solenoid valves using an equivalent magnetoresistive model database.

[0006] The technical solution of the present invention is as follows:

[0007] This invention first provides a multi-objective optimization method for the dynamic characteristics and structure of a solenoid valve using an equivalent magnetoresistive model database, which includes the following steps:

[0008] 1) Perform electromagnetic simulation on the solenoid valve that requires structural optimization to obtain the electromagnetic force characteristic diagram, inductance characteristic diagram and magnetic circuit diagram under different coil currents and different valve core displacements within the working range of the solenoid valve.

[0009] 2) Construct a magnetoresistive model database, which includes at least several basic regular-shaped magnetoresistors and stores the equivalent magnetoresistive expressions of the basic regular-shaped magnetoresistors.

[0010] 3) Compare the magnetic reluctance model database, perform magnetic reluctance partitioning on the magnetic circuit diagram from step 1), and obtain the equivalent magnetic circuit model; calculate the equivalent magnetic reluctance R of the entire magnetic circuit based on the equivalent magnetic circuit model. m And calculate the electromagnetic force F acting on the solenoid valve. m and the resulting inductance;

[0011] 4) Analyze the dynamic characteristics of the solenoid valve and establish a magnetoresistive simulation model;

[0012] 5) Taking the volume and dynamic characteristics of the solenoid valve as the optimization objectives and the structural parameters as the optimization variables, within the feasible variable constraints, the genetic optimization algorithm is used to perform multi-objective optimization to obtain a series of solenoid valve structural parameters under different dynamic characteristics.

[0013] As a preferred embodiment of the present invention, in step 2), the several basic regular-shaped magnetic reluctances include cylindrical magnetic reluctances, elliptical magnetic reluctances and arc-shaped magnetic reluctances, and their equivalent magnetic reluctances are calculated by existing formulas; irregular-shaped magnetic reluctances can be obtained by combining basic regular-shaped magnetic reluctances.

[0014] As a preferred embodiment of the present invention, step 3) specifically comprises:

[0015] 3.1) Based on the input solenoid valve magnetic circuit diagram, compare it with the reluctance model database to perform reluctance division and obtain the equivalent magnetic circuit model; the equivalent magnetic circuit model is composed of several reluctance loops connected in series and parallel, and each reluctance loop is composed of several reluctances connected in series; considering that the magnetic flux generated in different reluctance loops has different effects, the magnetic circuit is divided into two reluctance loops according to whether or not the valve core electromagnetic force is generated, that is, the reluctance loop that generates the valve core electromagnetic force is divided separately;

[0016] Since each reluctance is a reluctance already existing in the reluctance model database, the equivalent reluctance expression for each reluctance can be obtained, thus yielding the equivalent reluctance of each reluctance loop; finally, the equivalent reluctance R of the entire magnetic circuit is obtained. m ;

[0017] 3.2) Calculate the magnetomotive force U m U m =IN, where N is the number of coil turns and I is the coil current value;

[0018] 3.3) Calculate the magnetic flux of the reluctance circuit where the valve core is located, and denote it as Φ0;

[0019] 3.4) Calculate the electromagnetic force F acting on the solenoid valve. m And the resulting inductance L:

[0020]

[0021]

[0022] In the formula, μ a S represents the permeability of the working air gap. a This indicates the effective area of ​​the working air gap.

[0023] Furthermore, in step 3.1), the step of comparing the input solenoid valve magnetic circuit diagram with the reluctance model database to perform reluctance partitioning and obtain an equivalent magnetic circuit model specifically includes the following steps:

[0024] 3.1.1) Input the structural parameters of the solenoid valve and the magnetic circuit diagram obtained from the electromagnetic simulation. The magnetic circuit diagram obtained from the electromagnetic simulation contains the magnetic reluctance simulation results of the magnetic circuit diagram.

[0025] 3.1.2) The equivalent magnetic reluctance model database classifies the magnetic reluctance of the solenoid valve into three basic regular shape magnetic reluctances based on the magnetic circuit shape: cylindrical magnetic reluctance, elliptical magnetic reluctance, and arc-shaped magnetic reluctance, and matches the corresponding magnetic reluctance calculation model. On this basis, the same basic regular shape magnetic reluctance is further subdivided, that is, the large basic regular shape magnetic reluctance is further divided into several small basic regular shape magnetic reluctances, and finally the equivalent magnetic circuit model is obtained.

[0026] 3.1.3) Based on the input structural parameters and the equivalent magnetic circuit model obtained in 3.1.2), the magnetic reluctance calculation results of the solenoid valve are calculated, and the magnetic reluctance calculation results are compared with the magnetic reluctance simulation results of the magnetic circuit diagram.

[0027] If the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is greater than 10%, then return to step 3.1.2), and rematch the magnetoresistive calculation model with the equivalent magnetoresistive model database.

[0028] If the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is 5%-10%, then return to step 3.1.2), and increase the number of magnetoresistive divisions for the same basic regular shape using the equivalent magnetoresistive model database; until the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is less than 5%.

[0029] If the difference between the calculated reluctance result and the reluctance simulation result of the magnetic circuit diagram is less than 5%, then the mathematical description of the solenoid valve reluctance under the current equivalent magnetic circuit model will be output.

[0030] As a preferred embodiment of the present invention, the feasible constraint range in step 5) is X∈(X min ,X max ), where X min ,、X max These are the lower and upper limits allowed for each structural parameter during the optimization process, respectively; the multi-objective optimization in step 4) is performed using the genetic optimization algorithm NSGA-II.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. This invention utilizes the relationship between the structural parameters of the solenoid valve and its equivalent magnetic reluctance to establish a corresponding optimization objective function, applicable to different loading methods of the solenoid valve.

[0033] 2. This invention utilizes equivalent magnetoresistance to establish the corresponding dynamic characteristic expression, resulting in a more accurate dynamic simulation model.

[0034] 3. This invention can utilize the established magnetoresistive database for magnetoresistive analysis, construct equivalent magnetic circuits, and perform corresponding calculations, resulting in faster calculation speed and higher accuracy.

[0035] 4. This invention can not only optimize existing products on the market, but also optimize them during the product design stage, thereby greatly reducing the structural volume of the solenoid valve while improving its dynamic characteristics. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the multi-objective optimization method of the present invention;

[0037] Figure 2 This is a schematic diagram of the structure of a solenoid valve to be optimized, as exemplified in the embodiments.

[0038] Figure 3 for Figure 2 Electromagnetic force characteristic diagram of a solenoid valve;

[0039] Figure 4 for Figure 2 Inductance characteristic diagram of a solenoid valve;

[0040] Figure 5 This is a simulation diagram of the magnetic circuit of a solenoid valve.

[0041] Figure 6 A schematic diagram of a common regular-shaped magnetoresistance calculation model;

[0042] Figure 7 A schematic diagram of the equivalent magnetic circuit modeling process;

[0043] Figure 8 This is a schematic diagram of the equivalent magnetic circuit model;

[0044] Figure 9 This is a schematic diagram of the dynamic characteristics of a solenoid valve.

[0045] Figure 10 The figures show a comparison between experimental and simulation results of the dynamic characteristics of the original solenoid valve, where (a) represents the experimental value for opening, (b) represents the simulation value for opening, (c) represents the experimental value for closing, and (d) represents the simulation value for closing.

[0046] Figure 11 This is a schematic diagram of the NSGA-II genetic algorithm used in the embodiment;

[0047] Figure 12 The Pareto solution front graph in the example satisfies all optimization constraints;

[0048] Figure 13 A schematic diagram of the optimized solenoid valve structure;

[0049] Figure 14 To optimize the performance comparison chart of the solenoid valve before and after, (a) shows the performance comparison during the opening phase, and (b) shows the performance comparison during the closing phase. Detailed Implementation

[0050] The present invention will be further described and illustrated below with reference to specific embodiments. The embodiments described are merely examples of the content of this disclosure and do not limit the scope of the invention. The technical features of each embodiment in the present invention can be combined accordingly, provided that there is no mutual conflict.

[0051] like Figure 1 The diagram shown is a basic flowchart of the present invention. The method of the present invention mainly includes the following steps: electromagnetic simulation of the solenoid valve, construction of a magnetoresistive model database, establishment of a magnetoresistive simulation model, and multi-objective optimization. The following detailed description of each step of the present invention is provided in conjunction with specific embodiments. In the embodiments of the present invention, after establishing the magnetoresistive simulation model, a step of verifying the accuracy of the model is also included.

[0052] Step 1: Perform electromagnetic simulation for the solenoid valve that needs optimization. First, use AutoCAD to draw the structural diagram of the solenoid valve. The structural diagram of the solenoid valve studied in this embodiment is as follows: Figure 2 As shown; the structural diagram is imported into Maxwell software. The outer boundary of the solenoid valve model is defined as a balloon boundary to simulate an infinite solution region, effectively isolating charge or voltage sources outside the model. Then, Maxwell software is used to define the solenoid valve material, mesh it, and set the boundaries. The electromagnetic force characteristics under different coil currents and valve core displacements within the solenoid valve's operating range are obtained through software calculations, as shown below. Figure 3 As shown, inductance characteristics Figure 4 As shown, the magnetic circuit diagram is as follows: Figure 5 As shown.

[0053] Step two involves building a magnetoresistive model database. This database includes at least several basic regular-shaped magnetoresistive reluctances and stores their equivalent reluctance expressions. The reluctance of these basic regular-shaped reluctances can be calculated using formulas, and irregular shapes can be calculated through the evolution and combination of regular shapes. Common regular-shaped magnetoresistive reluctances are mainly cylindrical, elliptical, and arc-shaped reluctances, such as... Figure 6 As shown, a database of magnetoresistive models is built based on common regular-shaped magnetoresistive models. The magnetoresistive models described here are only for common regular shapes; more can be added later as needed.

[0054] Step 3: Perform equivalent magnetic circuit modeling based on the magnetoresistive model database. Based on the input solenoid valve magnetic circuit diagram, compare it with the magnetoresistive model database to perform magnetoresistive partitioning and build the corresponding magnetic circuit model. The flowchart is as follows: Figure 7 As shown. Specifically, 1) Input the solenoid valve structural parameters and the magnetic circuit diagram obtained from the electromagnetic simulation. The magnetic circuit diagram obtained from the electromagnetic simulation contains the magnetoresistive simulation results of the magnetic circuit diagram;

[0055] 2) The equivalent magnetic reluctance model database classifies the magnetic reluctance of solenoid valves into three basic regular shape magnetic reluctances based on the shape of the magnetic circuit: cylindrical magnetic reluctance, elliptical magnetic reluctance, and arc magnetic reluctance, and matches the corresponding magnetic reluctance calculation model. On this basis, the same basic regular shape magnetic reluctance is further subdivided, that is, the large basic regular shape magnetic reluctance is further divided into several small basic regular shape magnetic reluctances, and finally the equivalent magnetic circuit model is obtained.

[0056] 3) Calculate the electromagnetic valve reluctance based on the input structural parameters and the equivalent magnetic circuit model obtained in 2), and compare the reluctance calculation results with the reluctance simulation results of the magnetic circuit diagram;

[0057] If the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is greater than 10%, then return to step 2) and rematch the magnetoresistive calculation model with the equivalent magnetoresistive model database.

[0058] If the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is 5%-10%, then return to step 2), and increase the number of magnetoresistive divisions for the same basic regular shape using the equivalent magnetoresistive model database; until the difference between the calculated magnetoresistive result and the magnetoresistive simulation result of the magnetic circuit diagram is less than 5%.

[0059] If the difference between the calculated reluctance result and the reluctance simulation result of the magnetic circuit diagram is less than 5%, then the mathematical description of the solenoid valve reluctance under the current equivalent magnetic circuit model will be output.

[0060] The equivalent magnetic circuit finally constructed in this embodiment is as follows: Figure 8As shown. In this embodiment, when dividing the magnetic circuit, considering the different effects of magnetic flux generated in different reluctance circuits, the division is based on the amount of magnetic flux that generates electromagnetic force. It is mainly divided into two major reluctance circuits, with the valve core located in reluctance circuits R1 to R5 and R... 11 To R 16 and R 17 To R 19 The magnetic flux Φ2 is formed by the electromagnetic force generated by the valve core. Φ1 represents the magnetic flux produced by other reluctance circuits, and Φ3 represents the total magnetic flux generated by the solenoid valve.

[0061] Take U m R represents magnetomotive force. i Represents magnetic reluctance. Magnetomotive force U m The calculation formula is:

[0062] U m =IN

[0063] In the formula, N is the number of turns in the coil, and I is the coil current. The magnetic reluctance R... * The basic formula is:

[0064]

[0065] In the formula, x represents the length of the magnetic flux path, μ represents the permeability of the material, and s represents the cross-sectional area of ​​the magnetic flux path. Taking reluctance R1, R3, and R7 as examples, R1 is a radial cylindrical reluctance model, R3 is an axial cylindrical reluctance model, and R7 is an elliptical reluctance model. In the formula, r1 is the valve core radius, r2 is the thickness of the middle part of the solenoid valve, r3 is the radius of the fastening cap, l1 is the thickness of the sealing ring, l2 is the length of the solenoid valve mounting thread, l3 is the thickness of the valve body end, l4 is the length of the fastening cap thread, and θ is the starting angle of the magnetic flux path.

[0066]

[0067]

[0068]

[0069] The equivalent reluctance of each reluctance circuit can be expressed based on the equivalent reluctance, where R is the equivalent reluctance. ci R represents the equivalent magnetic reluctance of the i-th magnetic circuit. c This represents the equivalent magnetic reluctance of the entire magnetic circuit.

[0070]

[0071]

[0072]

[0073]

[0074] The magnetic flux of each reluctance circuit is:

[0075]

[0076]

[0077]

[0078] Therefore, the expressions for the electromagnetic force and inductance acting on the solenoid valve can be derived, where μ... a S represents the permeability of the working air gap. a Indicates the effective area of ​​the working air gap:

[0079]

[0080]

[0081] Step four: Dynamic characteristic analysis of the solenoid valve and establishment of a magnetoresistive simulation model. The dynamic characteristics of the solenoid valve are as follows: Figure 9 As shown. It mainly includes two processes: the start-up process and the stop-down process. The entire start-up dynamic response time t on Including the start delay time t on1 That is, the coil current rises to the critical current value I. on The time, and the start time of exercise t on2 That is, the time it takes for the valve core to fully open; the entire closing dynamic response time t off Including the shutdown delay time t off1 That is, the coil current drops to the critical shut-off current value I. off The time, and the time to shut down the exercise t off2 This refers to the time it takes for the valve core to completely close.

[0082] During operation, the valve core of the solenoid valve is subjected to not only electromagnetic force F m The solenoid valve operates under the influence of multiple forces, including hydraulic pressure, pneumatic pressure, and spring force. Therefore, the differential equation for the opening motion of the solenoid valve is:

[0083]

[0084] The differential equation for the closing motion of the solenoid valve is:

[0085]

[0086] In the formula, m represents the valve core mass, x represents the valve core displacement, and k s F represents the spring constant, x0 represents the pre-compression of the spring, and F represents the spring force coefficient. tF represents other forces acting on the valve core. f This indicates the frictional force between the valve core and the valve body.

[0087] At the instant the solenoid valve is about to open or close, both the valve core velocity and acceleration are zero, and the critical electromagnetic force F for opening the high-speed switching valve can be obtained. mon and the critical electromagnetic force F to close moff In the formula d gap This indicates the working air gap of the solenoid valve.

[0088] F mon =k s x o +F f +F t

[0089] F moff =k s (x0+d gap )-F f -F t

[0090] Based on the relationship between the current I and the inductance L in the circuit, the turn-on delay time t can be calculated. on1 and the closing delay time t off1 The relationship between the current I in the circuit is as follows:

[0091]

[0092] Substituting the expression for the generated inductance L into the equation, the turn-on delay time t can be calculated. on1 and the closing delay time t off1 for:

[0093]

[0094]

[0095] Based on the differential equations of motion for the opening and closing of the solenoid valve, the opening time t can be calculated. on2 and the time to stop the movement t off2 :

[0096]

[0097]

[0098] The solenoid valve opening dynamic response time t on and disable dynamic response time t off for:

[0099] t on =t on1 +t on2

[0100] t off =t off1 +t off2

[0101] Substituting the structural parameter X of the solenoid valve, the main components of the solenoid valve structure include the valve body diameter, valve core diameter, fastening cap thread radius, fastening cap thread length, and valve body end thickness. In this embodiment, the structural parameters are selected as follows: X = {d1, r1, r2, r3, l1, l2, l3, l4}, where d1 is the gap between the valve core and valve body, r1 is the valve core radius, r2 is the thickness of the middle part of the solenoid valve, r3 is the fastening cap radius, l1 is the sealing ring thickness, l2 is the solenoid valve mounting thread length, l3 is the valve body end thickness, l4 is the fastening cap thread length, and θ is the starting angle of the magnetic flux path. The mathematical description of the solenoid valve's dynamic characteristics with respect to the structural parameters can be obtained as follows:

[0102] f t (X)=t on (X)+t off (X).

[0103] Step 5: Verification of the magnetoresistive simulation model. Based on the electromagnetic force characteristics, inductance characteristics, and the mathematical description of the solenoid valve's dynamic characteristics regarding the structure, a model is constructed and compared with the experimentally measured dynamic characteristics of the valve core. Figure 10 As shown. The PWM modulation loading method is used here as an example only to explain this application. By comparison, it can be seen that the maximum error in the solenoid valve opening delay time is 3%, the maximum error in the opening motion time is 7%, the maximum error in the closing delay time is 7.5%, and the maximum error in the closing motion time is 4.3%. The maximum error between the simulated dynamic characteristic curve and the experimentally measured dynamic characteristic curve is 7.5%, indicating that the mathematical description of the solenoid valve's dynamic characteristics with respect to structural parameters obtained in step four can well simulate the solenoid valve's dynamic characteristics.

[0104] Step six: Multi-objective optimization of the solenoid valve. The optimization objectives are the volume and dynamic characteristics of the solenoid valve, with structural parameters as the optimization variables. The optimization is performed within feasible variable constraints, where the constraint condition is X∈(X... min ,X max Using the genetic algorithm toolbox in Matlab, the NSGA-II genetic optimization algorithm is called for multi-objective optimization. The basic optimization process is as follows: Figure 11 As shown, other corresponding multi-objective optimization algorithms can also be used for optimization. The Pareto front satisfying all constraints is obtained, as shown... Figure 12 .

[0105] The multi-objective optimization of this invention can obtain a series of solenoid valve structural parameters with different dynamic characteristics. Users can select from the optimization results according to the required volume or dynamic characteristics. Based on the Pareto solution front obtained in step six, the solution set A that satisfies both improved dynamic characteristics and minimum structural volume is selected; alternatively, a suitable solution set can be selected based on actual needs. Samples are manufactured based on the corresponding structural parameters of solution set A, and the performance of the samples is tested to experimentally verify the optimized solenoid valve structure. Figure 13 , Figure 14 As shown, the maximum radius of the solenoid valve before optimization was 11mm, and after optimization, the maximum radius was 8mm, resulting in a 27.3% reduction in volume. The opening delay time before optimization was 0.62ms, and after optimization, it was 0.51ms, an improvement of 17.7%; the opening motion time before optimization was 1.02ms, and after optimization, it was 0.83ms, an improvement of 18.6%; the closing delay time before optimization was 0.36ms, and after optimization, it was 0.16ms, an improvement of 55.5%; the closing motion time before optimization was 0.88ms, and after optimization, it was 0.82ms, an improvement of 6.8%. The dynamic characteristics and volume well meet the optimization requirements. The above embodiments only illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. For those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

Claims

1. A dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database, characterized by, The method comprises the following steps: 1) performing electromagnetic simulation on the electromagnetic valve in need of structure optimization to obtain an electromagnetic force characteristic diagram, an inductance characteristic diagram and a magnetic circuit diagram under different coil currents and different spool displacements in a working range of the electromagnetic valve; 2) building a magnetic resistance model database, wherein the magnetic resistance model database comprises at least a plurality of basic regular shape magnetic resistances, and the magnetic resistance model database stores equivalent magnetic resistance expressions of the basic regular shape magnetic resistances; 3) Compare the magnetic resistance model database, and divide the magnetic circuit diagram of step 1) into magnetic resistance to obtain an equivalent magnetic circuit model; calculate the equivalent magnetic resistance R of the entire magnetic circuit according to the equivalent magnetic circuit model m , and calculate the electromagnetic force F on the electromagnetic valve m and the inductance generated; 4) analyzing dynamic characteristics of the electromagnetic valve to build a magnetic resistance simulation model; 5) taking the volume and dynamic characteristics of the electromagnetic valve as optimization targets, taking structure parameters as optimization variables, and performing multi-objective optimization in a feasible variable constraint range by using a genetic optimization algorithm to obtain a series of structure parameters of the electromagnetic valve under different dynamic characteristics.

2. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 1, characterized in that, The electromagnetic simulation in step 1) is specifically as follows: An electromagnetic valve structure diagram is drawn by using AutoCAD; the structure diagram is imported into Maxwell software, a balloon boundary is defined as an outer boundary of the electromagnetic valve model, material definition, mesh division and boundary setting of the electromagnetic valve are completed by using the Maxwell software, and electromagnetic force characteristic diagrams, inductance characteristic diagrams and magnetic circuit diagrams under different coil currents and different spool displacements in a working range of the electromagnetic valve are obtained by calculation.

3. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 1, characterized in that, In step 2), the plurality of basic regular shape magnetic resistances comprise a cylindrical magnetic resistance, an elliptical magnetic resistance and a circular arc magnetic resistance, and equivalent magnetic resistances thereof are calculated by using existing formulas; irregular shape magnetic resistances can be obtained by combining the basic regular shape magnetic resistances.

4. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 1, characterized in that, The step 3) is specifically as follows: 3.1) dividing magnetic resistances according to the input electromagnetic valve magnetic circuit diagram and the magnetic resistance model database to obtain an equivalent magnetic circuit model; the equivalent magnetic circuit model is composed of a plurality of magnetic resistance circuits in series and parallel combination, and each magnetic resistance circuit is composed of a plurality of magnetic resistances in series; different magnetic flux effects are considered in different magnetic resistance circuits, and therefore the magnetic circuit is divided into two magnetic resistance circuits according to whether the magnetic resistance circuit produces electromagnetic force of the spool, that is, the magnetic resistance circuit producing electromagnetic force of the spool is divided separately; Since each magnetic reluctance is a magnetic reluctance model in the database, the equivalent magnetic reluctance expression of each magnetic reluctance can be obtained, and then the equivalent magnetic reluctance of each magnetic reluctance circuit is obtained; finally, the equivalent magnetic reluctance R of the entire magnetic circuit is obtained m ; 3.2) Calculation of the magnetomotive force U m , U m = IN, N being the number of turns of the coil and I the value of the current in the coil; 3.3) calculating magnetic flux of the magnetic resistance circuit where the spool is located, denoted as Φ0; 3.4) Solving the electromagnetic force F on the solenoid m and the resulting inductance L: where μ a represents the permeability of the working air gap, S a represents the effective area of the working air gap.

5. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 4, characterized in that, In step 3.1), the dividing magnetic resistances according to the input electromagnetic valve magnetic circuit diagram and the magnetic resistance model database to obtain an equivalent magnetic circuit model specifically comprises the following steps: 3.1.1) inputting electromagnetic valve structure parameters and a magnetic circuit diagram obtained by electromagnetic simulation, wherein the magnetic circuit diagram obtained by electromagnetic simulation contains magnetic resistance simulation results of the magnetic circuit diagram; 3.1.2) dividing electromagnetic valve magnetic resistances into three types of basic regular shape magnetic resistances, namely cylindrical magnetic resistances, elliptical magnetic resistances and circular arc magnetic resistances, according to the magnetic circuit shape and matching corresponding magnetic resistance calculation models; on this basis, the same basic regular shape magnetic resistance is further divided, that is, a large basic regular shape magnetic resistance is divided into a plurality of small basic regular shape magnetic resistances, and finally an equivalent magnetic circuit model is obtained; 3.1.3) calculating electromagnetic valve magnetic resistance calculation results according to input structure parameters and the equivalent magnetic circuit model obtained in 3.1.2), and comparing the magnetic resistance calculation results with magnetic resistance simulation results of the magnetic circuit diagram; If the difference between the magnetic reluctance calculation result and the magnetic reluctance simulation result of the magnetic circuit diagram is more than 10%, return to step 3.1.2) and re-match the magnetic reluctance calculation model from the equivalent magnetic reluctance model database; If the difference between the magnetic reluctance calculation result and the magnetic reluctance simulation result of the magnetic circuit diagram is between 5%-10%, return to step 3.1.2) and increase the number of magnetic reluctance division of the same basic rule shape from the equivalent magnetic reluctance model database; until the difference between the magnetic reluctance calculation result and the magnetic reluctance simulation result of the magnetic circuit diagram is less than 5%; If the difference between the magnetic reluctance calculation result and the magnetic reluctance simulation result of the magnetic circuit diagram is less than 5%, output the mathematical description of the magnetic reluctance of the electromagnetic valve under the current equivalent magnetic circuit model.

6. The method of Claim 1, wherein In step 4), the dynamic characteristics of the electromagnetic valve are represented by the dynamic response time of the electromagnetic valve; The dynamic response time of the solenoid valve consists of the opening dynamic response time t on and the closing dynamic response time t off time wherein the opening dynamic response time t on includes an opening delay time t on1 , i.e. the time for the coil current to rise to a critical current value I on , and an opening movement time t on2 , i.e. the time for the valve core to be fully opened; the closing dynamic response time t off includes a closing delay time t off1 , i.e. the time for the coil current to drop to a closing critical current value I off , and a closing movement time t off2 , i.e. the time for the valve core to be fully closed.

7. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 6, characterized in that, The establishment of the magnetic reluctance simulation model in step 4) is specifically: 4.1) The electromagnetic valve spool will not only be subjected to electromagnetic force F m in the work, but also to the action of multi-field forces including spring force; the electromagnetic valve opening motion differential equation is: The differential equation of the closing movement of the electromagnetic valve is: where m represents the mass of the spool, x represents the displacement of the spool, k s represents the spring force coefficient, x0represents the pre-compression of the spring, F t represents other forces acting on the spool, F f represents the friction between the spool and the valve body; 4.2) According to the relationship between the current I and the inductance L in the circuit, the turn-on delay time t on1 and the turn-off delay time t off1 are calculated. 4.3) According to the differential equation of the opening and closing movement of the electromagnetic valve, the opening movement time t on2 and the closing movement time t off2 are solved. 4.4) Dynamic response time t of the opening of the solenoid valve on and the closing of the solenoid valve t off is: t on = t on1 + t on2 t off = t off1 + t off2 Substitute the structure parameters X of the electromagnetic valve into the equation, and the mathematical description of the dynamic characteristics of the electromagnetic valve about the structure parameters is: f t (X) = t on (X) + t off (X) 4.5) According to the electromagnetic force characteristic diagram and the inductance characteristic diagram obtained in step 1), and the mathematical description of the dynamic characteristics of the electromagnetic valve about the structure in step 4.4), model is established, and the dynamic characteristics of the electromagnetic valve measured by experiment are compared to verify whether the mathematical description of the dynamic characteristics of the electromagnetic valve about the structure can well simulate the dynamic characteristics of the electromagnetic valve.

8. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 7, characterized in that, The structure parameters X of the electromagnetic valve include the valve body diameter, the valve core diameter, the thread radius of the fastening screw cap, the thread length of the fastening screw cap, and the thickness of the valve body end.

9. The dynamic characteristic and structure multi-objective optimization method of a solenoid valve using an equivalent magnetic reluctance model database according to claim 1, characterized in that, The feasible constraint range in the step 5) is X∈(X min ,X max ), wherein X min , and X max are lower limit value and upper limit value of each structure parameter in the optimization process, respectively; the multi-objective optimization in the step 4) is performed by using a genetic optimization algorithm NSGA-II.

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