Nozzle structure optimization method and device of methanol-diesel direct injection engine and computer storage medium

Abstract

The invention discloses a nozzle structure optimization method of a methanol-diesel direct injection engine, which comprises the following steps: randomly generating parameters of an initial particle swarm and an initial particle swarm algorithm, each particle in the particle swarm representing a group of nozzle parameters, comprise a diesel nozzle aperture, a hole length and an inlet radius, and a methanol nozzle aperture, a hole length and an inlet radius; constructing an engine geometric model containing a diesel oil nozzle and a methanol nozzle, establishing a CFD calculation model, and calculating the fuel consumption rate, the soot emission quality and the nitrogen oxide content; and calculating the fitness values of the particles, updating the speeds and positions of the particles, carrying out iterative calculation, updating the particle swarm by using the particle with the minimum fitness value until the maximum number of iterations is reached, and outputting the nozzle parameters corresponding to the particle with the minimum fitness value. The invention further discloses a corresponding optimization device and a computer storage medium. Structural parameter optimization is conducted on the two nozzles, the injection performance of each nozzle is improved, and the combustion effect of the engine is improved.

Description

Technical Field

[0001] The invention relates to a method for optimizing the nozzle structure of an in-cylinder direct injection engine, and in particular to a method, a device and a computer storage medium for optimizing the nozzle structure of a methanol-diesel in-cylinder direct injection engine. Background Art

[0002] The methanol-diesel dual-fuel engine injects methanol and diesel successively on the same nozzle, and uses diesel compression ignition to ignite methanol to achieve combustion and work. However, the physical and chemical properties of methanol and diesel are significantly different. Methanol has low viscosity, good fluidity, large latent heat of vaporization and difficulty in compression ignition, while diesel has high viscosity and poor fluidity. This difference makes it difficult for traditional nozzle structures to meet the injection requirements of the two fuels when the same nozzle is injected, and problems such as inaccurate injection amount, poor atomization effect, and incomplete combustion are prone to occur, which seriously affects the engine's power performance, economic performance, and emission performance.

[0003] The existing optimization methods for nozzles are mainly for single fuel nozzle optimization, without fully considering the requirements of dual fuel coordinated injection, and mostly adopt trial and error methods, testing different nozzle structures through a large number of experiments to select relatively good solutions. This method not only consumes a lot of manpower, material resources and time costs, but also due to the lack of systematic optimization strategies, it is difficult to accurately determine the optimal nozzle structure parameters, and it is impossible to give full play to the potential of dual fuel engines. Summary of the invention

[0004] In view of the above-mentioned defects of the prior art, the present invention provides a method for optimizing the nozzle structure of a methanol-diesel direct injection engine. The nozzle structure obtained by the existing optimization method is difficult to give full play to the optimal performance of various fuels, resulting in limited improvement in engine performance. The present invention also provides a device for optimizing the nozzle structure of a methanol-diesel direct injection engine and a computer storage medium.

[0005] The technical solution of the present invention is as follows: A method for optimizing the nozzle structure of a methanol-diesel direct injection engine, comprising the following steps: Step 1, randomly generate an initial particle swarm and initialize the parameters of the particle swarm algorithm, each particle in the particle swarm represents a set of nozzle parameters, and the nozzle parameters include diesel nozzle aperture, diesel nozzle aperture length, diesel nozzle inlet radius, methanol nozzle aperture, methanol nozzle aperture length and methanol nozzle inlet radius; Step 2, constructing an engine geometry model including a diesel nozzle and a methanol nozzle; Step 3, importing the engine geometry model into simulation software to establish a CFD mathematical calculation model, and using the CFD mathematical calculation model to calculate the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx; Step 4: Calculate the fitness value of the particle based on the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx, and update the speed and position of the particle, repeat steps 2 and 3, update the particle group with the particle with the smallest fitness value until the maximum number of iterations is reached, and output the nozzle parameters corresponding to the particle with the smallest fitness value.

[0006] Furthermore, the calculation formula of the fitness value is F=0.8×ISFC+0.2×(Soot+NOx), where F is the fitness value.

[0007] Furthermore, when establishing the CFD mathematical calculation model, the diesel mechanism is used as the parent mechanism, the methanol mechanism is used as the child mechanism, and the diesel mechanism and the methanol excitation are combined as the combustion reaction mechanism of the calculation model, wherein the principle of the combination is: if the parent mechanism does not have the data in the child mechanism, the data in the child mechanism is added to the synthesis mechanism; if the data in the child mechanism conflicts with the data in the parent mechanism, the data in the parent mechanism is retained.

[0008] Furthermore, when establishing the CFD mathematical calculation model, the physical properties of NC14H30 are used to replace the physical properties of diesel to simulate the flow characteristics of diesel.

[0009] The present invention also provides a device for optimizing the nozzle structure of a methanol-diesel direct injection engine, comprising: An initialization module is used to randomly generate an initial particle swarm and initialize the parameters of the particle swarm algorithm, wherein each particle in the particle swarm represents a set of nozzle parameters, and the nozzle parameters include a diesel nozzle aperture, a diesel nozzle aperture length, a diesel nozzle inlet radius, a methanol nozzle aperture, a methanol nozzle aperture length, and a methanol nozzle inlet radius; A geometry model building module, which is used to build engine geometry models including diesel and methanol nozzles; A CFD calculation module is used to import the engine geometry model into the simulation software to establish a CFD mathematical calculation model, and calculate the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx by the CFD mathematical calculation model; The iterative update module is used to calculate the fitness value of the particle based on the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx, and update the speed and position of the particle, repeatedly call the geometric model construction module and the CFD calculation module, update the particle group with the particle with the smallest fitness value until the maximum number of iterations is reached, and output the nozzle parameters corresponding to the particle with the smallest fitness value.

[0010] The present invention also provides a computer storage medium on which a computer program is stored. When the computer program is executed by a processor, the nozzle structure optimization method of the methanol-diesel direct injection engine is implemented.

[0011] The advantages of the technical solution provided by the present invention are: The present invention constructs a dual-nozzle engine model, where diesel and methanol are sprayed from different nozzles respectively, and the optimization algorithm is used to separately optimize the spray number structural parameters of diesel and methanol, which can give full play to the adaptability of the two fuels to the structural parameters. It can effectively improve the injection performance of each nozzle, improve the combustion effect in the engine cylinder, and more effectively and reasonably improve the engine output performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 The figure is a schematic flow chart of a method for optimizing the nozzle structure of a methanol-diesel direct injection engine according to an embodiment of the present invention.

[0013] Figure 2 Schematic diagram of the geometric model of the dual-nozzle engine cylinder.

[0014] Figure 3 Schematic diagram of the basic structure of diesel nozzle and methanol nozzle. DETAILED DESCRIPTION

[0015] The present invention is further described below in conjunction with examples. It should be understood that these examples are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading this description, various equivalent modifications to this description by those skilled in the art fall within the scope defined by the claims attached to this application.

[0016] The nozzle structure optimization device of the methanol-diesel direct injection engine of the embodiment comprises: The initialization module is used to randomly generate an initial particle swarm and initialize the parameters of the particle swarm algorithm. Each particle in the particle swarm represents a set of nozzle parameters, which include diesel nozzle aperture, diesel nozzle aperture length, diesel nozzle inlet radius, methanol nozzle aperture, methanol nozzle aperture length and methanol nozzle inlet radius.

[0017] The geometry model building module is used to build the engine geometry model including diesel nozzle and methanol nozzle.

[0018] The CFD calculation module is used to import the engine geometry model into the simulation software to establish a CFD mathematical calculation model, and the CFD mathematical calculation model is used to calculate the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx.

[0019] The iterative update module is used to calculate the fitness value of the particle based on the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx, and update the speed and position of the particle. The geometric model construction module and the CFD calculation module are repeatedly called to update the particle group with the particle with the smallest fitness value until the maximum number of iterations is reached, and the nozzle parameters corresponding to the particle with the smallest fitness value are output.

[0020] Please combine Figure 1 As shown, the optimization method implemented by the nozzle structure optimization device of the methanol-diesel direct injection engine of this embodiment includes the following steps: Step 1: The initialization module initializes the optimization algorithm.

[0021] First, initialize the parameters of the optimization algorithm, which is a particle swarm algorithm. The initialized parameters include the number of particles in the particle swarm algorithm, the maximum number of iterations, the learning factor, etc. At the same time, set the value ranges of the diesel and methanol nozzle parameters, namely the aperture D, the hole length L, and the radius R at the nozzle entrance, a total of six parameter value ranges, to ensure that the optimization process is carried out within a reasonable engineering range. Then, randomly generate an initial particle swarm, which contains N particles, each particle represents a set of nozzle parameter combinations, and the jth particle can be expressed as: R j ={r j1 , r j2 , r j3 , r j4 , r j5 , r j6}, where r j1 =D jd , r j2 =L jd , r j3 =R jd , r j4 =D jm , r j5 =L jm , r j6 =R jm , the subscript d represents the diesel nozzle structural parameters, and the subscript m represents the methanol nozzle structural parameters.

[0022] Step 2: Construct the three-dimensional geometric model of the engine.

[0023] The geometric model of the dual-nozzle engine cylinder is constructed based on the nozzle parameter combination contained in the particles, such as Figure 2 The engine model has two nozzles, namely diesel nozzle 1 and methanol nozzle 2. The basic structures of diesel nozzle 1 and methanol nozzle 2 are shown in Figure 3 As shown, diesel nozzles 1 and methanol nozzles 2 of different sizes are obtained according to different nozzle parameters.

[0024] The diesel nozzle shape control parameters corresponding to the jth particle are aperture r j1 、Kong Length j2 and the radius r at the nozzle inlet j3 The control parameters of methanol nozzle shape are aperture r j4 、Kong Length j5 and the radius r at the nozzle inlet j6 The diesel nozzle sprays diesel, and the methanol nozzle sprays methanol. The parameters of the engine cylinder geometry model are: the cylinder diameter is 14.15 cm, the stroke is 15.66 cm, the distance from the top of the cylinder head to the top dead center of the piston is 0.6 cm, and the width of the gap between the piston and the cylinder wall is 0.12 cm.

[0025] Step 3: CFD modeling and simulation calculation.

[0026] The three-dimensional geometric model of the engine established in step 2 is imported into the simulation software. The simulation software used in this embodiment is ANSYS-FORTE. The CFD mathematical calculation model of the methanol-diesel dual-fuel nozzle engine is established by ANSYS-FORTE, which specifically includes the following steps: (1) Meshing: Meshing the imported engine 3D geometric model.

[0027] (2) Set the engine-related physical parameters: Specifically, the piston temperature is set to 500K, and the initial temperatures of the cylinder head and cylinder wall are set to 470K and 420K. The initial engine temperature is 360K and the pressure is 2.2 bar. The simulation range is 165°CA before top dead center to 125°CA after top dead center. The engine speed is 1200RPM.

[0028] (3) Establishment of a calculation model for the combustion of methanol and diesel in the engine cylinder: This step is used to simulate the combustion process of methanol and diesel in the cylinder. It is necessary to consider the combustion reaction mechanism and corresponding physical properties of the two substances. The diesel mechanism has 193 substances and 854 reactions. The methanol mechanism has 21 substances and 93 reactions. The diesel mechanism is the parent mechanism and the methanol mechanism is the child mechanism. The two mechanisms are merged to form a specific combustion algorithm. The principle of merging is: if the parent mechanism does not have the data in the child mechanism, the data in the child mechanism is added to the synthesis mechanism; if the data in the child mechanism conflicts with the data in the parent mechanism, the data in the parent mechanism is retained. The final synthesis has 195 substances and 880 reactions. NC7H16 is used to represent diesel in the diesel mechanism, and CH3OH is used to represent methanol in the methanol mechanism. When considering physical properties, since diesel is a mixture of multiple substances, if NC7H16 is used to replace diesel, the C atoms it contains are relatively low compared to diesel, and using its physical properties to describe diesel will lead to inaccurate results. For this reason, the physical properties of N-Tetradecan (NC14H30) are used as the physical properties of NC7H16. The molecule of NC14H30 contains 14 carbon atoms, and its carbon chain length and physical properties (such as density, viscosity, evaporation characteristics, etc.) are closer to diesel, which can more realistically reflect the behavior of diesel in the flow process, thereby improving the accuracy of the simulation model. Since the introduction of methanol will affect diesel, the initial temperature is set at 1200K, the pressure is 2.5atm, the constant volume model is used, the diesel:methanol = 8:2, the equivalence ratio is 1, and the reactions that are most sensitive to heat contribution are endothermic: nc7h16+oh=c7h15-2+h2o, 2ho2=h2o2+o2, and exothermic: nc7h16+ho2=c7h15-2+h2o2, nc7h16+o2=c7h15-2+ho2, ch3+ho2=ch3o+oh, o+oh=o2+h, h2o2+m=2oh+m, ch2o+ho2=hco+h2o2, c2h4+oh=ch2o+ch3, ch3oh+ho2=ch2oh+h2o2.

[0029] (4) Determine the control equations and other CFD simulation methods required for simulation calculations: For methanol and diesel, establish the conservation form of the NS equations and the component transport equations to accurately describe the flow and transmission process of the fuel in the nozzle. Use the eddy dissipation model to simulate the combustion process of the two fuels in the engine cylinder. Use the classic SIMPLE algorithm to iteratively solve all grids, and finally obtain the engine's indicated fuel consumption rate ISFC, soot emission mass Soot and nitrogen oxide content NOx.

[0030] Step 4: Iterate and update the calculation.

[0031] First, calculate the fitness value of each particle F = 0.8 × ISFC + 0.2 × (Soot + NOx). Then, the optimization algorithm uses formulas (1) and (2) to continuously adjust the particle's velocity Z and position R according to the particle's current fitness value, that is, to update the nozzle parameter combination. After each iteration, repeat steps 2 and 3 to evaluate the fitness value corresponding to the new parameter combination. Then compare the fitness value of each particle with the entire population and update it. The update rule is to retain the position and corresponding fitness value of the particle with the smallest fitness value. When the preset maximum number of iterations is met, the optimization process ends and the optimal nozzle parameter combination is obtained, that is: S = {D dopt , L dopt , R dopt , D mopt , L mopt , R mopt}. dopt , L dopt , R dopt is the structural parameter of the diesel nozzle of the particle with the smallest fitness value, D mopt , L mopt , R mopt Structural parameters of the methanol nozzle for the particle with the smallest fitness value.

[0032] (1) (2)

[0033] Where: h 1 and h 2 is the learning factor, w is the weight parameter; τ 1 and τ 2 is a random parameter.

[0034] The injection number structural parameters of diesel and methanol obtained by the above method can effectively improve the injection performance of each nozzle, improve the combustion effect in the engine cylinder, and more effectively and reasonably improve the engine output performance.

[0035] It should be noted that the specific methods of the above embodiments can form a computer program product. Therefore, the computer program product implemented by the present application can be stored on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.). In addition, the present application can be implemented in the form of hardware, software, or a combination of hardware and software, or constitute a computer device including at least one processor and a memory, the memory storing a computer program for implementing the above process steps, and the processor executing the computer program on the memory to form the method steps of the above embodiments.

Claims

1. A method for optimizing the nozzle structure of a methanol-diesel direct injection engine, characterized in that: The following steps are involved: Step 1, randomly generate an initial particle swarm and initialize the parameters of the particle swarm algorithm, each particle in the particle swarm represents a set of nozzle parameters, and the nozzle parameters include diesel nozzle aperture, diesel nozzle aperture length, diesel nozzle inlet radius, methanol nozzle aperture, methanol nozzle aperture length and methanol nozzle inlet radius; Step 2, constructing an engine geometry model including a diesel nozzle and a methanol nozzle; Step 3, importing the engine geometry model into simulation software to establish a CFD mathematical calculation model, and using the CFD mathematical calculation model to calculate the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx; Step 4: Calculate the fitness value of the particle based on the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx, and update the speed and position of the particle, repeat steps 2 and 3, update the particle group with the particle with the smallest fitness value until the maximum number of iterations is reached, and output the nozzle parameters corresponding to the particle with the smallest fitness value.

2. The method for optimizing the nozzle structure of a methanol-diesel direct injection engine according to claim 1, characterized in that: The calculation formula of the fitness value is F=0.8×ISFC+0.2×(Soot+NOx), where F is the fitness value.

3. The method for optimizing the nozzle structure of a methanol-diesel direct injection engine according to claim 1, characterized in that: When establishing the CFD mathematical calculation model, the diesel mechanism is used as the parent mechanism, the methanol mechanism is used as the child mechanism, and the diesel mechanism and the methanol excitation are combined as the combustion reaction mechanism of the calculation model, wherein the principle of the combination is: if the parent mechanism does not have the data in the child mechanism, the data in the child mechanism is added to the synthesis mechanism; if the data in the child mechanism conflicts with the data in the parent mechanism, the data in the parent mechanism is retained.

4. The method for optimizing the nozzle structure of a methanol-diesel direct injection engine according to claim 3, characterized in that: When establishing the CFD mathematical calculation model, the physical properties of NC14H30 are used to replace the physical properties of diesel to simulate the flow characteristics of diesel.

5. A device for optimizing the nozzle structure of a methanol-diesel direct injection engine, characterized in that: include: An initialization module is used to randomly generate an initial particle swarm and initialize the parameters of the particle swarm algorithm, wherein each particle in the particle swarm represents a set of nozzle parameters, and the nozzle parameters include a diesel nozzle aperture, a diesel nozzle aperture length, a diesel nozzle inlet radius, a methanol nozzle aperture, a methanol nozzle aperture length, and a methanol nozzle inlet radius; A geometry model building module, which is used to build engine geometry models including diesel and methanol nozzles; A CFD calculation module is used to import the engine geometry model into the simulation software to establish a CFD mathematical calculation model, and calculate the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx by the CFD mathematical calculation model; The iterative update module is used to calculate the fitness value of the particle based on the fuel consumption rate ISFC, the soot emission mass Soot and the nitrogen oxide content NOx, and update the speed and position of the particle, repeatedly call the geometric model construction module and the CFD calculation module, update the particle group with the particle with the smallest fitness value until the maximum number of iterations is reached, and output the nozzle parameters corresponding to the particle with the smallest fitness value.

6. The nozzle structure optimization device for a methanol-diesel direct injection engine according to claim 5, characterized in that: The calculation formula of the fitness value is F=0.8×ISFC+0.2×(Soot+NOx), where F is the fitness value.

7. The nozzle structure optimization device for a methanol-diesel direct injection engine according to claim 5, characterized in that: When establishing the CFD mathematical calculation model, the diesel mechanism is used as the parent mechanism, the methanol mechanism is used as the child mechanism, and the diesel mechanism and the methanol excitation are combined as the combustion reaction mechanism of the calculation model, wherein the principle of the combination is: if the parent mechanism does not have the data in the child mechanism, the data in the child mechanism is added to the synthesis mechanism; if the data in the child mechanism conflicts with the data in the parent mechanism, the data in the parent mechanism is retained.

8. The nozzle structure optimization device for a methanol-diesel direct injection engine according to claim 7, characterized in that: When establishing the CFD mathematical calculation model, the physical properties of NC14H30 are used to replace the physical properties of diesel to simulate the flow characteristics of diesel.

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for optimizing the nozzle structure of a methanol-diesel direct injection engine according to any one of claims 1 to 4 is implemented.

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