Variable stiffness spring simulation design method for high-pressure common rail pump

Abstract

The invention relates to the technical field of diesel engine fuel supply, in particular to a variable stiffness spring simulation design method for a high-pressure common rail pump. Comprising the steps of establishing a multi-physics field coupling model based on simulation software; establishing a thermodynamic module; simulating the movement of the plunger; simulating the movement of the valve core; establishing a fuel pressure dynamic change model; calculating the spring stiffness; calculating a target adjustment parameter; optimizing a spring stiffness coefficient: adjusting the spring stiffness coefficient through a genetic algorithm; a population is set and initialized, then an operation method is selected, crossover operation is carried out, and filial generation individual data is obtained; outputting an optimal parameter; optimal target parameters are calculated, specifically, the optimal parameters are introduced into simulation software, so that the maximum collision speed V of the valve element is reduced, and the system volume efficiency L is improved; by using the variable stiffness spring, the collision speed can be effectively reduced, the impact stress between the valve element and the valve seat is reduced, the fatigue damage between the valve element assemblies is reduced, and the service life of the pump valve assembly of the high-pressure common rail pump is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of diesel engine fuel supply, and particularly relates to a variable stiffness spring simulation design method for a high-pressure common rail pump. Background Art

[0002] As a core component of the fuel supply system, the high-pressure common rail pump of a diesel engine plays a crucial role in the common rail system and the operation of the entire diesel engine. Currently, both the high-pressure common rail pump of the diesel engine fuel supply system and the unit pump of the mechanical fuel supply system adopt a plunger pump with a valve distribution structure. Among them, the structural parameters of the inlet and outlet valves of the plunger pump significantly affect the performance indicators of the high-pressure pump and even the entire diesel engine.

[0003] As a positive displacement pump, the valve core of the pump valve of the plunger pump moves under the combined action of its own gravity, spring force, and hydrodynamic force. During the opening and closing process of the valve core, its response speed largely determines the volumetric efficiency of the reciprocating pump; in addition, the collision of the valve core with the valve seat and the limit mechanism during movement will generate impact stress, directly affecting the durability of the pump valve assembly.

[0004] Among the three forces, the spring force is provided by the return spring of the valve core. According to the relationship between the spring force and the compression amount, the spring can be divided into a linear spring and a non-linear spring. The stiffness coefficient of a linear spring is constant, and the deformation amount is linearly related to the acting force; the stiffness coefficient of a non-linear spring, however, is dynamically adjusted with the change of the deformation amount.

[0005] Currently, the return springs of the inlet valve and outlet valve of the high-pressure pump mostly adopt linear springs specified by national standards. Linear springs have a simple structure and low manufacturing cost, and are suitable for medium and low frequencies and occasions with relatively stable working conditions, but they have limitations in response adaptability. Non-linear springs, on the other hand, can better handle high-frequency opening and closing and complex working conditions with optimized opening and closing characteristics, reducing pressure shocks, but their design and manufacturing costs are relatively high, and their performance stability also needs to be strictly controlled. For example, the governor spring in a diesel engine mechanical governor is a typical non-linear spring, and its design and manufacturing both require precise control.

[0006] In summary, non-linear springs (variable stiffness springs) have shown extensive application potential in the technical field of diesel engine fuel supply. Applying non-linear springs to the pump valves of high-pressure pumps can significantly improve the response speed of the valve core, reduce the backflow of high-pressure fuel, and thus enhance the volumetric efficiency of the pump. At the same time, non-linear springs can also reduce the collision speed between the valve core and the limit mechanism and the valve seat during the valve opening and closing processes, thereby reducing the impact stress and improving the service life and reliability of the pump valve assembly. However, due to the relatively high design and manufacturing costs, the application of non-linear springs in the domestic high-pressure pump technology field is not yet widespread, and currently, most pump valve springs are still mainly linear springs.

[0007] Therefore, in order to improve the volumetric efficiency of the high-pressure pump and reduce the impact stress of the spool, it is a feasible solution to use a non-linear spring (variable stiffness spring) to replace the traditional linear spring. Based on this, the present invention proposes a simulation design method for a variable stiffness spring for a high-pressure common rail pump to meet the requirements of high performance and high reliability. Summary of the Invention

[0008] In order to overcome the above technical problems, the purpose of the present invention is to provide a simulation design method for a variable stiffness spring for a high-pressure common rail pump, which solves the problems that most of the pump valve springs of domestic high-pressure pumps are standard parts and linear springs at present, which easily lead to problems such as excessive seating speed of the fuel injection valve and slow spool response speed in some application scenarios, resulting in a decrease in volumetric efficiency due to untimely spool seating.

[0009] The purpose of the present invention can be achieved by the following technical solutions: A simulation design method for a variable stiffness spring for a high-pressure common rail pump, comprising the following steps: S1. Establish a multi-physical field coupling model based on simulation software, including a mechanical module, a hydraulic module, and a thermodynamics module; the above modules are coupled to calculate mechanical parameters and serve as the basis for optimizing the spring stiffness coefficient; S2. Establish a thermodynamics module: collect experimental data of fuel temperature and spring stiffness, fit the collected experimental data to obtain a temperature sensitivity coefficient , couple the spring displacement with the temperature to obtain a non-linear correction function , the temperature sensitivity coefficient and the non-linear correction function are used to calculate the spring stiffness of the coupled variable stiffness spring ; the non-linear correction function , c1, c2, c3 are fitting parameters, and are all greater than 0 and less than or equal to 1, c1 + c2 + c3 = 1, where x and T are calculated after normalization; S3. Simulate the plunger movement: analyze the operating state and force of the plunger, simulate the plunger movement mode, decompose the influencing parameters of the plunger movement, and construct a plunger movement equation; S4. Simulate the spool movement: analyze the operating state and force of the spool, fit the movement speed of the spool, decompose the influencing parameters of the spool movement, and construct a spool movement equation; S5. Establish a dynamic change model of fuel pressure: analyze the influence of fuel pressure fluctuation through the plunger movement equation obtained in S3 and the spool movement equation obtained in S4, and use it to feedback and evaluate the stability of the parameters of the plunger movement equation and the spool movement equation; S6. Calculate the spring stiffness : Set the spring stiffness coefficients a and b; calculate according to the following formula: ; Define the initialization of a0 and b0, and calculate the initial spring stiffness ; x represents the deformation of the spring. The main reason for using the inverse proportional function is that when the independent variable x is small, the decay rate of the dependent variable is faster than that of other functions. Applying this characteristic to the spring stiffness enables the spring to respond quickly under low load conditions, thereby effectively reducing the valve core return lag and improving the dynamic performance of the system. In addition, this characteristic can also maintain stable opening and closing behavior under high load conditions, ensuring the reliability and working efficiency of the system.

[0010] S7. Calculate the target adjustment parameters: Based on the simulation software, obtain the maximum collision velocity V of the valve core and the system volumetric efficiency L; S8. Optimize the spring stiffness coefficient: Adjust the spring stiffness coefficients a and b through the genetic algorithm; set the population and initialize it, then select the operation method and perform the crossover operation to obtain the offspring individual data; perform the mutation operation on the offspring individual data to increase the population diversity; update the population and repeat the iteration until the algorithm converges, and then output the optimal parameters and ; S9. Calculate the optimal target parameters: Introduce the optimal parameters and obtained in S8 into the simulation software AMESim, so that the maximum collision velocity V of the valve core is reduced and the system volumetric efficiency L is improved.

[0011] It should be further noted that: The simulation software is AMESim; the mechanical module is used to simulate the movement of the plunger and the valve core, and calculate the dynamic displacement, velocity and acceleration; the hydraulic module is used to simulate the fuel flow rate and pressure fluctuation; the thermodynamics module is used to simulate the influence of temperature on the nonlinear behavior of the spring.

[0012] It should be further noted that: The calculation formula for the maximum collision velocity V of the valve core in S7 is as follows: , is the mass of the valve core, is the acceleration of the valve core; , is the forming distance of the valve core; The calculation formula for the system volumetric efficiency L in S7 is as follows: , is the actual output flow rate, is the theoretical output flow rate; , where is the cross-sectional area of the plunger, is the stroke distance of the plunger, is the plunger drive frequency; , is the movement speed of the plunger.

[0013] Further explanation is needed. The specific steps of the plunger motion equation are as follows: S31. Plunger analysis: Analyze the operating state and force of the plunger. The motion of the plunger is affected by the spring force, fuel pressure, and damping force. Then simulate the motion mode of the plunger; S32. Decompose the influencing parameters of the plunger motion: After analyzing the motion law of the plunger, the parameters affecting the plunger motion include: plunger mass, damping coefficient, spring force, plunger pressure area, damping force, fuel pressure; S33. Construct the plunger motion equation: Through mechanical analysis of the above parameters, the plunger motion equation is obtained as: ; Among them, is the plunger mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the plunger spring displacement when the spring force is generated, is the fuel pressure, is the plunger pressure area, represents the fuel pressure force generated by the fuel ; represents the driving force of the plunger, which is obtained and set by simulation experiments, Among them, the spring force of the plunger .

[0014] Further explanation is needed. The specific steps of the spool motion equation are as follows: S41. Spool analysis: Analyze the operating state and force of the spool. The motion of the spool is affected by the spring force, fuel pressure, and damping force. Then simulate the motion mode of the spool; S42. Decompose the influencing parameters of the spool motion: After analyzing the motion law of the spool, the parameters affecting the spool motion include: spool mass, damping coefficient, spring force, damping force, fuel pressure; S43. Construct the spool motion equation: Through mechanical analysis of the above parameters, the spool motion equation is obtained as: ; Among them, is the spool mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the spool spring displacement and the spring force generated at this time, is the fuel pressure, is the pressure area of the plunger, represents the fuel pressure acting force generated by the fuel .

[0015] Among them, the spring force of the spool .

[0016] It should be further noted that; In S5, the plunger motion equation obtained from S3 and the spool motion equation obtained from S4 are used to analyze the influence of fuel pressure fluctuations; Construct the pressure fluctuation formula as follows: , where is the bulk modulus of elasticity of the fuel, reflecting the compressibility of the fuel; is the volume of the high-pressure chamber; is the fuel flow rate entering the high-pressure chamber, is the fuel flow rate discharged from the high-pressure chamber.

[0017] It should be further noted that the specific steps for adjusting the spring stiffness coefficients a and b by the genetic algorithm are as follows: S81 Set the objective function: The goal is to adjust the spring parameters a and b by the genetic algorithm so that the high-pressure common rail system meets the performance requirements. The optimization problem can be defined as an objective function in the following form: Among them: is the objective function, composed of the maximum collision speed and volumetric efficiency; a and b are the parameters to be optimized; S82 Construct the objective function: The objective function ; where w1 and w2 are weighting coefficients; Set the value ranges of a and b and set the constraint conditions; S83 Initialize the population: Each individual represents a set of spring parameters (a, b), which can be represented by a vector: [a, b], The population is the set of all individuals, with a size of Np, representing the population quantity; then parameter initialization, Randomly generate the initial population, and the individuals in the initial population are evenly distributed in the design space; calculate the objective function value for each individual in the population ; S84 Selection operation method: Assign fitness values to each individual in the population according to the objective function values calculated in S83. The specific formula is as follows: ; Select the selection operation method and select individuals from the population according to the fitness values to generate the parental individuals of the next generation; S85 Crossover operation: Use the two-point crossover or uniform crossover method to randomly select two parental individuals to generate two offspring; S86 Mutation operation Randomly impose small perturbations on the parameters of the offspring individuals to increase the diversity of the population, and set a relatively low mutation probability from 0.01 to 0.1 to prevent premature convergence; S87 Population update: Combine the parental and offspring individuals, sort them according to the fitness, and select the top n individuals as the population of the next generation; When the change in the objective function value of the population is less than the preset threshold or the maximum number of iterations is reached, the algorithm stops and the optimal parameters are output and .

[0018] Among them, the operation method in S83 is the roulette wheel selection method or the tournament selection method.

[0019] Advantages of the present invention: A variable stiffness spring simulation design method for a high-pressure common rail pump of the present invention couples the motion states involved in the plunger and spool valve in the high-pressure common rail system, analyzes the force state of the system of the variable stiffness spring, and constructs a mechanical module, a hydraulic module, and a thermodynamics module based on simulation software according to the operating state of the system to evaluate the influence of the stiffness of the variable stiffness spring on the system. The optimal parameters are found through an optimization algorithm to reduce the maximum collision speed and improve the volumetric efficiency of the system, while reducing the influence of fuel pressure fluctuations on the system. Description of the drawings

[0020] The present invention will be further described below with reference to the accompanying drawings.

[0021] Figure 1 is a schematic diagram of a variable stiffness spring simulation design method for a high-pressure common rail pump in the present invention. Specific embodiments

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0023] Embodiment 1: Please refer to Figure 1 As shown, this embodiment is a variable stiffness spring simulation design method for a high-pressure common rail pump, and the specific steps are as follows: S1. Establish a multi-physical field coupling model based on the simulation software AMESim, including a mechanical module, a hydraulic module, and a thermodynamics module; Among them, the mechanical module is used to simulate the movement of the plunger and the spool, and calculate the dynamic displacement, velocity, and acceleration; the hydraulic module is used to simulate the fuel flow rate and pressure fluctuation; the thermodynamics module is used to simulate the influence of temperature on the nonlinear behavior of the spring; S2. Establish a thermodynamics module: Collect experimental data of fuel temperature and spring stiffness, and fit the collected experimental data to obtain the temperature sensitivity coefficient , couple the spring displacement and temperature to obtain a nonlinear correction function , the temperature sensitivity coefficient and the nonlinear correction function are used to calculate the spring stiffness of the coupled variable stiffness spring ; the nonlinear correction function , c1, c2, and c3 are fitting parameters respectively; the nonlinear correction function is used to represent the nonlinear behavior of the material and the multi-physical coupling effect, and the fitting parameters should be adjusted according to the results of multiple simulation simulations; S3. Simulate the movement of the plunger: Analyze the operating state and force of the plunger, simulate the movement mode of the plunger, decompose the influencing parameters of the plunger movement, and construct the plunger movement equation; S4. Simulate the movement of the spool: Analyze the operating state and force of the spool, fit the movement speed of the spool, decompose the influencing parameters of the spool movement, and construct the spool movement equation; S5. Establish a dynamic change model of fuel pressure: Analyze the influence of fuel pressure fluctuation through the plunger movement equation obtained in S3 and the spool movement equation obtained in S4, and use it to feedback and evaluate the stability of the parameters of the plunger movement equation and the spool movement equation; S6. Calculate the spring stiffness : Set the spring stiffness coefficients a and b; calculate according to the following formula: ; Define the initial values a0 and b0, and calculate the initial spring stiffness ; S7. Calculate the target adjustment parameters: Based on the simulation software AMESim, obtain the maximum collision speed V of the spool and the system volumetric efficiency L, where, , is the mass of the spool, is the acceleration of the spool; , is the actual output flow rate, is the theoretical output flow rate; , is the forming distance of the spool; , where is the cross-sectional area of the plunger, is the stroke distance of the plunger, is the driving frequency of the plunger; , is the moving speed of the plunger; S8. Optimize the spring stiffness coefficient: Adjust the spring stiffness coefficients a and b through the genetic algorithm; set the population and initialize it, then select the operation method and perform the crossover operation to obtain the data of the offspring individuals; perform the mutation operation on the data of the offspring individuals to increase the population diversity; update the population and repeat the iteration until the algorithm converges, and then output the optimal parameters and ; S9. Calculate the optimal target parameters: Introduce the optimal parameters and obtained in S8 into the simulation software AMESim, so that the maximum collision speed V of the spool is reduced and the volumetric efficiency L of the system is improved; Since the spool will repeatedly impact the valve seat during operation, the use of the variable stiffness spring in the present invention can effectively reduce the collision speed, reduce the impact stress between the spool and the valve seat, reduce the fatigue damage between the spool components, and improve the service life of the pump valve components of the high-pressure common rail pump.

[0024] Embodiment 2: On the basis of Embodiment 1, this embodiment further illustrates the specific steps of the plunger motion equation as follows: S31. Plunger analysis: Analyze the operating state and force of the plunger. The motion of the plunger is affected by the spring force, fuel pressure, and damping force, and then simulate the motion mode of the plunger; The plunger in the high-pressure common rail system reciprocates by the drive of the cam. Its main task is to compress the fuel and inject it into the high-pressure chamber to provide high-pressure fuel for the injector; Set the driving force of the plunger as during the motion of the plunger, and generate fuel pressure during the motion. The higher the pressure, the greater the reaction force on the plunger, the increase in the plunger motion resistance, and at the same time, the pressure fluctuation will cause the instability of the plunger motion and affect the motion of the spool; The spring force generated by the plunger spring and the damping force also affect the motion of the plunger; the above factors will comprehensively affect the stability of the plunger motion and affect the generated fuel pressure ; S32. Decompose the influencing parameters of the plunger movement: After analyzing the movement law of the plunger, the parameters affecting the plunger movement include: plunger mass, damping coefficient, spring force, plunger pressure area, damping force, fuel pressure; S33. Construct the plunger movement equation: Through mechanical analysis of the above parameters, the plunger movement equation is obtained as: ; Wherein, is the plunger mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the plunger spring displacement when the spring force is generated, is the fuel pressure, is the plunger pressure area, represents the fuel pressure acting force generated by the fuel ; represents the driving force of the plunger, which is obtained from simulation experiments and set.

[0025] The spring force of the plunger ; The fuel pressure acting force is determined by the fuel pressure and the plunger pressure area together, while the damping force is caused by the friction between the plunger and the liquid or other dissipation effects, is related to the plunger speed, and the plunger speed affects the volumetric efficiency L.

[0026] The actual output flow rate of the high-pressure oil pump is less than the theoretical output flow rate. The ratio of the actual output flow rate of the high-pressure oil pump to the theoretical output flow rate is the volumetric efficiency of the high-pressure oil pump.

[0027] Example 3: Based on any of the above embodiments, the specific steps of the spool movement equation in this embodiment are further described as follows: S41. Spool analysis: Analyze the operating state and force of the spool. The movement of the spool is jointly affected by the spring force, fuel pressure and damping force, and then simulate the plunger movement mode; The driving force of the spool movement comes from the fuel pressure. The greater the fuel pressure, the greater the maximum collision speed obtained by the spool. It is necessary to adjust the stiffness coefficient of the spring to reduce the maximum collision speed; S42. Decompose the influencing parameters of the spool movement: After analyzing the movement law of the spool valve, the parameters affecting the spool valve movement include: spool valve mass, damping coefficient, spring force, damping force, fuel pressure; S43. Construct the spool valve movement equation: Through mechanical analysis of the above parameters, the spool valve movement equation is obtained as follows: ; Among them, is the spool valve mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the spool valve spring displacement when the spring force generated, is the fuel pressure, is the plunger compression area, represents the fuel pressure acting force generated by the fuel ;

[0028] The maximum collision speed V is an important output result of the spool valve movement equation, and the speed reaches the maximum when the spool valve reaches the seat surface; the calculation of the maximum collision speed V depends on the dynamic equation of the spool valve and is obtained through numerical integration or simulation calculation.

[0029] The magnitude of the maximum collision speed V is jointly affected by fuel pressure, spring stiffness, damping effect, etc., and the collision speed can be reduced by optimizing these parameters; by reasonably designing the variable stiffness spring parameters a and b, the acceleration of the spool valve can be effectively slowed down, thereby reducing the maximum collision speed V.

[0030] Among them, the spring force of the spool valve .

[0031] Example 4: Based on any of the above embodiments, this embodiment further illustrates that the fuel pressure dynamic change model specifically includes: Analyze the influence of fuel pressure fluctuation through the plunger movement equation obtained by S3 and the spool valve movement equation obtained by S4; Fuel pressure is the core parameter of the high-pressure common rail system and directly affects the injection characteristics of the injector. The flow rate and pressure fluctuation formula describe the dynamic change of fuel pressure over time, and the pressure fluctuation formula is as follows: , where is the bulk modulus of elasticity of the fuel, reflecting the compressibility of the fuel; is the volume of the high-pressure chamber; is the fuel flow rate entering the high-pressure chamber, is the fuel flow rate discharged from the high-pressure chamber; used to dynamically capture the influence of plunger movement, spool valve opening and closing, pressure fluctuation, etc. on fuel pressure; when When approaching 1, the overall fuel pressure of the system tends to be stable. The reciprocating motion of the plunger directly affects the volume of the high-pressure chamber, thereby changing the fuel pressure; and the fuel pressure is an important force driving the spool movement. The pressure fluctuation formula establishes the connection between the plunger movement, fuel pressure, and spool dynamic behavior, and is used to feedback and evaluate the stability of the parameters of the plunger movement equation and spool movement equation.

[0032] Example 5: Based on any of the above embodiments, this embodiment further illustrates the specific steps of adjusting the spring stiffness coefficients a and b by the genetic algorithm. Among them, the genetic algorithm (GA) is a global optimization algorithm based on natural selection and genetic mechanisms, and is very suitable for solving high-dimensional, nonlinear, and multi-objective optimization problems. In the high-pressure common rail system, the genetic algorithm can be used to optimize the spring parameters a and b to improve system performance, such as reducing the maximum collision speed of the spool, reducing pressure fluctuations, and improving volumetric efficiency.

[0033] Optimize the spring stiffness coefficients, adjust the spring stiffness coefficients a and b by the genetic algorithm; set the population and initialize it, then select the operation method and perform crossover operation to obtain the offspring individual data; perform mutation operation on the offspring individual data to increase population diversity; update the population and repeat the iteration until the algorithm converges, and then output the optimal parameters and .

[0034] The specific steps are as follows: S81 Set the objective function: The goal is to adjust the spring parameters a and b by the genetic algorithm to make the high-pressure common rail system meet the performance requirements. The optimization problem can be defined as an objective function in the following form: ; Where: is the objective function, which consists of the maximum collision speed and volumetric efficiency; a and b are the parameters to be optimized; S82 Construct the objective function: The objective function ; where w1 and w2 are weighting coefficients; The goal is that the smaller the maximum collision speed V of the spool, the better; the larger the volumetric efficiency L of the system, the better.

[0035] Set the value ranges of a and b, and set constraint conditions such as: The spring force cannot exceed the material strength limit of the spool or plunger.

[0036] The dynamic response time of the system meets specific requirements.

[0037] S83 Initialize the population: Set the population representation Each individual represents a set of spring parameters (a, b), which can be represented by a vector: [a, b]. The population is the set of all individuals, with a size of Np, representing the population quantity. Then parameter initialization Randomly generate the initial population, and the individuals in the initial population are evenly distributed within the design space. For each individual in the population, Calculate its objective function value ; S84 Selection operation method: Assign fitness values to each individual in the population according to the objective function values calculated in S83. The specific formula is as follows: ; Use the roulette wheel selection method or the tournament selection method to select individuals from the population according to the fitness values to generate the parental individuals of the next generation.

[0038] S85 Crossover operation: Use the two-point crossover or uniform crossover method to randomly select two parental individuals to generate two offspring; S86 Mutation operation Randomly impose small perturbations on the parameters of the offspring individuals to increase the diversity of the population, and set a relatively low mutation probability from 0.01 to 0.1 to prevent premature convergence.

[0039] S87 Population update: Combine the parents and offspring, sort them according to fitness, and select the top n individuals as the next generation population; When the change in the objective function value of the population is less than the preset threshold, or the maximum number of iterations is reached, the algorithm stops and outputs the optimal parameters and 。

[0040] It should be further noted that the above formulas are all obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value. The coefficients or thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0041] In the description of this specification, the descriptions referring to terms such as "an embodiment", "example", "specific example", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0042] The above content is only an example and illustration of the present invention. Those skilled in the art of this technology can make various modifications, supplements, or use similar methods to replace the described specific embodiments, as long as they do not deviate from the invention or exceed the scope defined by this claims, they shall fall within the protection scope of the present invention.

Claims

1. A variable stiffness spring simulation design method for a high-pressure common rail pump, characterized in that, It includes the following steps: S1. Establish a multi-physical field coupling model based on simulation software, including a mechanical module, a hydraulic module, and a thermodynamics module; S2. Establish a thermodynamics module: Collect experimental data on fuel temperature and spring stiffness, and fit the collected experimental data to obtain a temperature sensitivity coefficient , couple the spring displacement with the temperature to obtain a non-linear correction function , the temperature sensitivity coefficient and the non-linear correction function are used to calculate the spring stiffness of the variable stiffness spring after coupling ; the non-linear correction function , where c1, c2, and c3 are fitting parameters respectively; S3. Simulate the plunger movement: conduct an operating state analysis and a force analysis on the plunger, simulate the plunger movement mode, decompose the influencing parameters of the plunger movement, and construct a plunger movement equation; S4. Simulate the spool movement: conduct an operating state analysis and a force analysis on the spool, fit the movement speed of the spool, decompose the influencing parameters of the spool movement, and construct a spool movement equation; S5. Establish a dynamic fuel pressure change model: analyze the influence of fuel pressure fluctuations through the plunger movement equation obtained in S3 and the spool movement equation obtained in S4, and use it to feedback and evaluate the stability of the parameters of the plunger movement equation and the spool movement equation; S6. Calculate the spring stiffness : Set the spring stiffness coefficients a and b; Calculations are carried out according to the following formula: : Define the initial values of a0 and b0 and calculate the initial spring stiffness ; S7. Calculate the target adjustment parameters: obtain the maximum collision speed V of the spool and the system volumetric efficiency L based on the simulation software; S8. Optimize the spring stiffness coefficients: Adjust the spring stiffness coefficients a and b through the genetic algorithm; set the population and initialize it, then select the operation method and perform the crossover operation to obtain the data of the offspring individuals; perform the mutation operation on the data of the offspring individuals to increase the population diversity; update the population and repeat the iteration until the algorithm converges, and then output the optimal parameters and ; S9. Calculate the optimal target parameters: Introduce the optimal parameters obtained in S8 and into the simulation software to reduce the maximum collision velocity V of the spool and improve the volumetric efficiency L of the system.

2. The simulation design method of a variable stiffness spring for a high-pressure common rail pump according to claim 1, wherein The simulation software is AMESim; the mechanical module is used to simulate the movement of the plunger and the spool, and calculate the dynamic displacement, speed, and acceleration; the hydraulic module is used to simulate the fuel flow rate and pressure fluctuations; the thermodynamics module is used to simulate the influence of temperature on the nonlinear behavior of the spring.

3. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 1, characterized in that The calculation formula for the maximum collision velocity V of the spool in S7 is as follows: , is the mass of the spool, is the acceleration of the spool; , is the forming distance of the spool; The system volumetric efficiency L is calculated as follows: , is the actual output flow, is the theoretical output flow; ,in is the cross-sectional area of the plunger, is the travel distance of the plunger, is the plunger drive frequency; , is the speed of the plunger.

4. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 1, characterized in that, The specific steps of the plunger movement equation are as follows: S31. Plunger analysis: conduct an operating state analysis and a force analysis on the plunger. The movement of the plunger is jointly affected by the spring force, fuel pressure, and damping force, and then simulate the plunger movement mode; S32. Decompose the influencing parameters of the plunger movement: After analyzing the movement law of the plunger, the parameters affecting the plunger movement include: plunger mass, damping coefficient, spring force, plunger pressure area, damping force, fuel pressure; S33. Establish the plunger motion equation: Through mechanical analysis of the above parameters, the plunger motion equation is obtained as follows: ; Among them, is the plunger mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the plunger spring displacement and the spring force generated at this time, is the fuel pressure, is the plunger compression area, represents the fuel pressure acting force generated by the fuel ; represents the driving force of the plunger, which is obtained from simulation experiments and set.

5. A method for simulating the design of a variable stiffness spring for a high-pressure common rail pump according to claim 4, characterized in that Spring force of the plunger .

6. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 4, characterized in that The specific steps of the spool movement equation are as follows: S41. Spool analysis: conduct an operating state analysis and a force analysis on the spool. The movement of the spool is jointly affected by the spring force, fuel pressure, and damping force, and then simulate the spool movement mode; S42. Decompose the influencing parameters of the spool movement: After analyzing the movement law of the spool, the parameters affecting the spool movement include: spool mass, damping coefficient, spring force, damping force, fuel pressure; S43. Establish the spool motion equation: Through mechanical analysis of the above parameters, the spool motion equation is obtained as follows: ; Among them, is the spool mass, is the linear plunger damping coefficient, is the non-linear damping coefficient, represents the damping force ; is the spool spring displacement and the spring force generated at this time, is the fuel pressure, is the plunger pressure area, represents the fuel pressure force generated by the fuel .

7. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 5, characterized in that Spring force of the spool valve .

8. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 5, characterized in that Analyze the influence of fuel pressure fluctuations through the plunger movement equation obtained in S3 and the spool movement equation obtained in S4; The pressure fluctuation formula is constructed as follows: , where is the bulk modulus of elasticity of the fuel, reflecting the compressibility of the fuel; is the volume of the high-pressure chamber; is the fuel flow rate into the high-pressure chamber, is the fuel flow rate discharged from the high-pressure chamber.

9. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 1, characterized in that, The specific steps of adjusting the spring stiffness coefficients a and b by the genetic algorithm are as follows: S81 Set the objective function: The goal is to adjust the spring parameters a and b through a genetic algorithm so that the high-pressure common rail system meets the performance requirements. The optimization problem can be defined as an objective function in the following form: , Wherein: is the objective function, which consists of the maximum collision speed and the volumetric efficiency; a and b are the parameters to be optimized; S82 Construct the objective function: the objective function ; where w1 and w2 are weighting coefficients; Set the value range of a and b, and set the constraint conditions; S83 Initialize the population: Each individual represents a set of spring parameters (a, b), which can be represented by a vector: [a, b], The population is the set of all individuals, with a size of Np, representing the population quantity; then parameter initialization, Randomly generate an initial population, and the individuals in the initial population are evenly distributed within the design space; for each individual in the population, calculate its objective function value ; S84 Select the operation method: Assign a fitness value to each individual in the population according to the objective function value calculated in S83. The specific formula is as follows: ; Select an operation method and select individuals from the population according to the fitness value to generate the parental individuals of the next generation; S85 Crossover operation: Use the two-point crossover or uniform crossover method to randomly select two parent individuals to generate two offspring; S86 Mutation operation Randomly impose a small perturbation on the parameters of the offspring individuals to increase the diversity of the population, and set a relatively low mutation probability of 0.01 to 0.1 to prevent premature convergence; S87 Population Update: Combine the parent generation and the offspring generation, sort them by fitness, and select the top n individuals as the next generation population; when the change in the objective function value of the population is less than the preset threshold or the maximum number of iterations is reached, the algorithm stops and outputs the optimal parameters and .

10. A variable stiffness spring simulation design method for a high-pressure common rail pump according to claim 9, characterized in that, The operation method is the roulette wheel selection method or the tournament selection method.

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