CN113202669B - Multi-objective optimization method for performance of electric control oil injector - Google Patents

Abstract

The purpose of the present invention is to provide a multi-objective optimization method for the performance of an electronically controlled fuel injector, comprising the following steps: establishing a numerical simulation model of the electronically controlled fuel injector; proposing performance evaluation indicators such as response characteristics and injection characteristics; The characteristic parameters of each component of the oiler are analyzed for significance to determine the design variables of the evaluation indicators; the DOE experimental design of the design variables is carried out, and the response values of the evaluation indicators are obtained through simulation; the response surface prediction models of the response characteristics and injection characteristics are respectively constructed; Taking the optimal injection characteristics as the optimization goal, the multi-parameter optimization of design variables is carried out; the screening function of the response characteristics and injection characteristics of the electronically controlled injector is proposed to obtain the corresponding design variables when the electronically controlled injector has the best performance. . The invention can obtain the significant influencing parameters of the performance of the electronically controlled fuel injector, realize the accurate prediction of the response characteristics and the injection characteristics, and can carry out multi-objective optimization of the design variables on the basis of simultaneously improving the response characteristics and the injection characteristics.

Description

A Multi-objective Optimization Method for Electronically Controlled Fuel Injector Performance

technical field

The invention relates to a method for controlling fuel injection of an engine, in particular to a method for optimizing the performance of an engine fuel injector.

Background technique

As the most complex and key component in the high-pressure common rail fuel injection system, the electronically controlled injector's response characteristics and injection characteristics determine the pressure relief speed of the control cavity, the injection timing and the injection quantity, and will affect the high-pressure common rail. The control accuracy of the fuel injection system of the fuel injection system directly affects the performance of the diesel engine. And because the electronically controlled injector is subjected to the coupling effect of electromagnetic, mechanical, hydraulic and other physical fields during the working process, the characteristic parameters of each component of the electronically controlled injector will affect the response characteristics and injection characteristics. Therefore, it is of great significance to carry out multi-objective multi-parameter optimization to improve the response characteristics and injection characteristics of electronically controlled injectors.

Due to the large number of characteristic parameters of each component of the electronically controlled injector, and there may be a coupling effect between the characteristic parameters, the performance optimization of the electronically controlled injector through traditional experimental research requires a lot of manpower and material resources, and there is a long development cycle. and other shortcomings.

At the same time, at present, the optimization of structural parameters of electronically controlled injectors mainly focuses on the optimization of single components and single characteristics such as injector flow characteristics, electromagnetic actuator static and dynamic characteristics, and needle valve response characteristics. Although these optimization methods can improve a specific characteristic of the electronically controlled injector, other characteristics of the electronically controlled injector may be sacrificed in the process of improving the specific characteristic, and there is a problem that cannot fully and effectively improve the electronically controlled fuel injection. performance issues, etc.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a multi-objective optimization method for the performance of an electronically-controlled injector, which can carry out multi-objective optimization of the structural parameters of the electronically-controlled injector on the basis of simultaneously improving the response characteristics and the injection characteristics.

The object of the present invention is achieved in this way:

A multi-objective optimization method for the performance of an electronically controlled fuel injector of the present invention is characterized in that:

(1) Establish a numerical simulation model of the electronically controlled fuel injector;

(2) The evaluation indexes of electronically controlled injector performance such as response characteristics and injection characteristics are proposed;

(3) Significantly analyze the characteristic parameters of each component of the electronically controlled injector, and determine the design variables of the evaluation index;

(4) Carry out the DOE experimental design for the design variables, and obtain the response value of the evaluation index through simulation;

(5) Build the response surface prediction models of the response characteristics and injection characteristics respectively, and evaluate the effectiveness of the prediction models;

(6) Based on the response surface prediction model in step 5, taking the optimal response characteristics and injection characteristics as the optimization goal, carry out multi-parameter optimization of design variables;

(7) The screening function of the response characteristics and injection characteristics of the electronically controlled injector is proposed to obtain the corresponding design variables when the electronically controlled injector has the best performance.

The present invention can also include:

1. The process of establishing the numerical simulation model of the electronically controlled fuel injector in step (1) is as follows: based on the power bond graph theory, the differential motion equation of the electronically controlled fuel injector is deduced, and the numerical simulation model of the electronically controlled fuel injector is built.

2. The evaluation indexes of the response characteristics and injection characteristics in step (2) are as follows:

The evaluation index of the response characteristic is the needle valve response T _N , and the calculation formula of the needle valve response T _N is as follows:

Among them, T _N is the needle valve response, _TO is the time required for the high-speed solenoid valve of the injector to be energized until the needle valve opens to the maximum lift, and T _C is the power-off of the high-speed solenoid valve of the injector until the needle valve is fully closed. required time;

The evaluation index of the injection characteristics is the fuel injection efficiency η, and the calculation formula of the fuel injection efficiency η is as follows:

Among them, η is the fuel injection efficiency, Q _cycle is the amount of fuel injected by the injector into the cylinder under a single cycle, Q _in is the amount of fuel entering the injector under a single cycle, and Q _leak is the fuel injector under a single cycle. The amount of fuel leakage, Q _back is the fuel return amount of the injector in a single cycle.

3. The characteristic parameters of each component for the significance analysis in step (3) are as follows:

Solenoid valve characteristic parameters include: solenoid valve mass, solenoid valve residual air gap, solenoid valve maximum lift, solenoid valve spring preload, solenoid valve spring stiffness, solenoid valve sealing ball diameter, solenoid valve valve hole diameter;

The characteristic parameters of the control chamber include: the diameter of the oil inlet orifice, the diameter of the oil return orifice, and the volume of the control chamber;

The needle valve characteristic parameters include: needle valve assembly mass, needle valve maximum lift, needle valve spring preload, needle valve spring stiffness, oil holding tank volume, needle valve cavity volume, and nozzle hole diameter.

4. The specific steps for determining the design variables of the evaluation index in step (3) are as follows:

Calculate the influence factor for each component characteristic parameter, and then calculate the percentage of each component characteristic parameter calculation influence factor to the total value, so as to determine the design variables of the evaluation index. The formula for calculating the impact factor is as follows:

Among them, σ _x is the influence factor of the characteristic parameter x, T _{N_max} , T _{N_min} , T _med are the maximum, minimum and reference value of the needle valve response when the value of the characteristic parameter x changes, η _max , η _min , η _med respectively are the maximum value, minimum value and reference value of the fuel injection efficiency when the value of the characteristic parameter x changes, and x _max , x _min , and x _med are the maximum value, the minimum value and the reference value of the value of the characteristic parameter x, respectively.

5. Step (4) is specifically as follows: using the D-optimal experimental design method to design the DOE scheme for the design variables, and substituting the obtained DOE design schemes for the design variables into the numerical simulation model of the electronically controlled injector, respectively, to respond to the needle valve. T _N and fuel injection efficiency η are calculated and solved.

6. Step (5) is as follows: based on the DOE experimental design results in step (4), a quadratic polynomial response surface model is used to construct a prediction model for the needle valve response _TN and fuel injection efficiency η, and the least squares regression method is used to analyze the results. The unknown coefficients of the quadratic polynomial response surface prediction model are solved, and the coefficient of determination and the corrected coefficient of determination are used as a measure of the effectiveness of the prediction model;

The calculation formula of the quadratic polynomial response surface prediction model is as follows:

In the formula, x _i is the ith component of the design variable x, α ₀ is a constant, α _i is a linear coefficient, α _ii is a quadratic coefficient, and a _ij is an interaction coefficient.

7. Step (6) is as follows: taking the minimum needle valve response T _N and the maximum fuel injection efficiency η as the optimization goal, and taking the value range of the design variable as the constraint, based on the needle valve response T _N constructed in step (5) and For the prediction model of fuel injection efficiency η, the Pareto solution set that satisfies all constraints is calculated by using genetic algorithm.

8. The calculation formula of the screening function of the response characteristics and injection characteristics of the electronically controlled injector in step (7) is as follows:

In the formula, F(X) is the screening function, and X is the design variable combination;

The filter function F(X) is minimized, and the optimal solution of the multi-objective optimization design variable combination X of the electronically controlled injector is obtained.

9. Substitute the design variable combination under the optimal performance of the electronically controlled injector obtained in step (7) into the numerical simulation model of the electronically controlled injector in step (1), and analyze the needle valve response T _N and the fuel injection efficiency η is calculated, and the calculation result is compared with the needle valve response reference value T _{N_med} and the fuel injection efficiency η _med .

The advantages of the present invention are:

1. The present invention proposes the evaluation index of the response characteristic and injection characteristic of the electronically controlled fuel injector, carries out a significant analysis on the characteristic parameters of each component, and obtains the characteristic parameters that have a significant impact on the evaluation index, thereby determining the design variable of the evaluation index;

2. The present invention conducts DOE experimental design for design variables, constructs a response surface prediction model of response characteristics and injection characteristics, and evaluates the validity of the prediction model, which ensures the accurate prediction of response characteristics and injection characteristics, and solves the problem of traditional experiments. Research requires a lot of manpower and material resources, and the research and development cycle is long;

3. The invention takes the optimal response characteristics and injection characteristics as the optimization goal, and takes the value range of the design variables as constraints, and carries out multi-objective optimization of the performance of the electronically controlled injector based on the genetic algorithm, which solves the problem of the current optimization method for electronically controlled injection. Oiler performance optimization is not comprehensive, not efficient and so on.

Description of drawings

Fig. 1 is the flow chart of the present invention;

Figure 2 shows the results of the significant analysis of the characteristic parameters of each component;

Fig. 3 is a graph showing the comparison between the predicted value and the simulated value of the quadratic polynomial response surface model of the needle valve response;

Fig. 4 is a graph showing the comparison between the predicted value and the simulated value of the quadratic polynomial response surface model of the fuel injection efficiency;

Figure 5 shows the Pareto solution set for multi-objective optimization of injector performance;

Figure 6 shows the comparison results before and after the optimization of the injector performance.

Detailed ways

The present invention will be described in more detail below in conjunction with the accompanying drawings:

1-6, a multi-objective optimization method for the performance of an electronically controlled fuel injector of the present invention includes the following steps:

Step 1, establish a numerical simulation model of the electronically controlled fuel injector and verify its accuracy;

Specifically, based on the power bond graph theory, the differential motion equation of the electronically controlled fuel injector is derived, the numerical simulation model of the electronically controlled fuel injector is built, and the accuracy of the model is verified.

Step 2, put forward the evaluation indicators of the electronically controlled injector performance such as response characteristics and injection characteristics;

Specifically, the evaluation index of the response characteristic is the needle valve response T _N . The formula for calculating the needle valve response T _N is as follows:

Among them, T _N is the response of the needle valve, _TO is the time required for the high-speed solenoid valve of the injector to be energized until the needle valve opens to the maximum lift, and T _C is the power-off of the high-speed solenoid valve of the injector until the needle valve is fully closed. required time.

The evaluation index of the injection characteristics is the injection efficiency η. The calculation formula of fuel injection efficiency η is as follows:

Among them, η is the fuel injection efficiency, Q _cycle is the amount of fuel injected by the injector into the cylinder under a single cycle; Q _in is the amount of fuel entering the injector under a single cycle; Q _leak is the fuel injector under a single cycle. The amount of fuel leakage; Q _back is the fuel return amount of the injector in a single cycle.

Step 3, carry out a significant analysis on the characteristic parameters of each component of the electronically controlled fuel injector, and determine the design variables of the evaluation index;

Specifically, the characteristic parameters of each component for significance analysis are as follows:

Solenoid valve characteristic parameters include: solenoid valve mass, solenoid valve residual air gap, solenoid valve maximum lift, solenoid valve spring preload, solenoid valve spring stiffness, solenoid valve sealing ball diameter, solenoid valve valve hole diameter;

The characteristic parameters of the control chamber include: the diameter of the oil inlet orifice, the diameter of the oil return orifice, and the volume of the control chamber;

The needle valve characteristic parameters include: needle valve assembly mass, needle valve maximum lift, needle valve spring preload, needle valve spring stiffness, oil holding tank volume, needle valve cavity volume, and nozzle hole diameter.

The specific steps to determine the design variables of the evaluation index are as follows:

Calculate the influence factor for each component characteristic parameter, and then calculate the percentage of each component characteristic parameter calculation influence factor to the total value, so as to determine the design variables of the evaluation index. The formula for calculating the impact factor is as follows:

Among them, σ _x is the influence factor of the characteristic parameter x, T _{N_max} , T _{N_min} , T _med are the maximum, minimum and reference value of the needle valve response when the value of the characteristic parameter x changes, η _max , η _min , η _med respectively are the maximum value, minimum value and reference value of the fuel injection efficiency when the value of the characteristic parameter x changes, and x _max , x _min , and x _med are the maximum value, the minimum value and the reference value of the value of the characteristic parameter x, respectively.

According to the significant analysis results of the characteristic parameters of each component shown in Figure 2, the design variables for the evaluation indicators are determined as the diameter of the solenoid valve sealing ball, the diameter of the oil inlet orifice, the diameter of the oil return orifice, the maximum lift of the needle valve and the nozzle hole. diameter.

Step 4, carry out the DOE experimental design on the design variables, and obtain the response value of the evaluation index through simulation;

Specifically, the D-optimal experimental design method is used to design the DOE scheme for the design variables, and the obtained DOE design schemes of the design variables are respectively substituted into the numerical simulation model of the electronically controlled injector, and the needle valve response _TN and the fuel injection efficiency are analyzed. η is calculated and solved.

Step 5: Build the response surface prediction model of the response characteristic and the injection characteristic respectively, and evaluate the validity of the prediction model;

Specifically, based on the DOE experimental design results in step 4, a quadratic polynomial response surface model is used to construct a prediction model for the needle valve response _TN and the fuel injection efficiency η. The unknown coefficients of the quadratic polynomial response surface prediction model are solved by using the least squares regression method. According to the comparison between the predicted value of the quadratic polynomial response surface model of the needle valve response _TN and the fuel injection efficiency η shown in Figure 3 and Figure 4 and the simulation value, it can be seen that the coefficient of determination and the corrected coefficient of determination are both close to 1, indicating that the prediction model The better the prediction ability.

Step 6, based on the response surface prediction model in Step 5, take the optimal response characteristics and injection characteristics as the optimization goal, and carry out multi-parameter optimization of design variables;

Specifically, taking the minimum needle valve response T _N and the maximum fuel injection efficiency η as the optimization goals, and taking the value range of the design variables as constraints, based on the prediction model of the needle valve response T _N and the fuel injection efficiency η constructed in step 5, The Pareto solution set shown in Figure 5 is obtained by using the genetic algorithm.

Step 7, propose a screening function for the response characteristics and injection characteristics of the electronically controlled injector, and obtain the design variable values corresponding to the optimal performance of the electronically controlled injector;

Specifically, the calculation formula of the screening function of the response characteristics and injection characteristics of the electronically controlled injector is as follows:

In the formula, F(X) is the screening function, and X is the design variable combination.

By minimizing the screening function F(X), the optimal solution of the multi-objective optimal design variable combination X of the electronically controlled injector is obtained: the diameter of the solenoid valve sealing ball, the diameter of the oil inlet orifice, the diameter of the oil return orifice, the maximum needle valve diameter The lift and nozzle diameter are 1.600mm, 0.233mm, 0.280mm, 0.200mm, and 0.160mm, respectively.

Step 8, based on the numerical simulation model of the electronically controlled injector in Step 1, compare the results before and after the optimization.

Substitute the design variable combination under the optimal performance of the electronically controlled injector obtained in step 7 into the numerical simulation model of the electronically controlled injector in step 1, calculate the needle valve response T _N and the fuel injection efficiency η, and use The calculation results are compared with the needle valve response reference value T _{N_med} and the injection efficiency η _med . From the comparison results shown in Figure 6, it can be seen that the needle valve response _TN is reduced from 0.898ms to 0.764ms, and the response speed is increased by 14.86%; the fuel injection efficiency η is increased from 75.849% to 76.997%, and the fuel injection efficiency is increased by 1.51%.

Claims (8)

1. a multi-objective optimization method of electronically controlled fuel injector performance, is characterized in that: (1) Establish a numerical simulation model of the electronically controlled fuel injector; (2) The evaluation indexes of electronically controlled injector performance such as response characteristics and injection characteristics are proposed; (3) Significantly analyze the characteristic parameters of each component of the electronically controlled injector, and determine the design variables of the evaluation index; (4) Carry out the DOE experimental design for the design variables, and obtain the response value of the evaluation index through simulation; Step (4) is specifically as follows: using the D-optimal experimental design method to design the DOE scheme for the design variables, and substituting the obtained DOE design schemes for the design variables into the numerical simulation model of the electronically controlled injector, respectively, to respond to the needle valve T _N Calculate and solve with the fuel injection efficiency η; (5) Build the response surface prediction models of the response characteristics and injection characteristics respectively, and evaluate the effectiveness of the prediction models; (6) Based on the response surface prediction model in step 5, taking the optimal response characteristics and injection characteristics as the optimization goal, carry out multi-parameter optimization of design variables; Step (6) is as follows: taking the minimum needle valve response T _N and the maximum fuel injection efficiency η as the optimization goal, and taking the value range of the design variable as the constraint, based on the needle valve response T _N and the fuel injection constructed in step (5) The prediction model of the efficiency η is calculated by using the genetic algorithm to obtain the Pareto solution set that satisfies all the constraints; (7) The screening function of the response characteristics and injection characteristics of the electronically controlled injector is proposed to obtain the corresponding design variables when the electronically controlled injector has the best performance. 2. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 1, is characterized in that: the process of establishing numerical simulation model of electronically controlled fuel injector in step (1) is: based on the power bond diagram theory, deduce the differential motion equation of the electronically controlled fuel injector, and build a numerical simulation model of the electronically controlled fuel injector. 3. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 1, is characterized in that: the evaluation index of performances such as response characteristic and injection characteristic in step (2) is as follows: The evaluation index of the response characteristic is the needle valve response T _N , and the calculation formula of the needle valve response T _N is as follows:

Among them, T _N is the needle valve response, _TO is the time required for the high-speed solenoid valve of the injector to be energized until the needle valve opens to the maximum lift, and T _C is the power-off of the high-speed solenoid valve of the injector until the needle valve is fully closed. required time; The evaluation index of the injection characteristics is the fuel injection efficiency η, and the calculation formula of the fuel injection efficiency η is as follows:

Among them, η is the fuel injection efficiency, Q _cycle is the amount of fuel injected by the injector into the cylinder under a single cycle, Q _in is the amount of fuel entering the injector under a single cycle, and Q _leak is the fuel injector under a single cycle. The amount of fuel leakage, Q _back is the fuel return amount of the injector in a single cycle. 4. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 1, is characterized in that: in step (3), each component characteristic parameter that carries out significant analysis is as follows: Solenoid valve characteristic parameters include: solenoid valve mass, solenoid valve residual air gap, solenoid valve maximum lift, solenoid valve spring preload, solenoid valve spring stiffness, solenoid valve sealing ball diameter, solenoid valve valve hole diameter; The characteristic parameters of the control chamber include: the diameter of the oil inlet orifice, the diameter of the oil return orifice, and the volume of the control chamber; The needle valve characteristic parameters include: needle valve assembly mass, needle valve maximum lift, needle valve spring preload, needle valve spring stiffness, oil holding tank volume, needle valve cavity volume, and nozzle hole diameter. 5. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 4 is characterized in that: the concrete steps of determining the design variable of evaluation index in step (3) are as follows: Calculate the influence factor for each component characteristic parameter separately, and then calculate the percentage of each component characteristic parameter calculation influence factor to the total value, so as to determine the design variables of the evaluation index. The calculation formula of the influence factor is as follows:

Among them, σ _x is the influence factor of the characteristic parameter x, T _{N_max} , T _{N_min} , T _med are the maximum, minimum and reference value of the needle valve response when the value of the characteristic parameter x changes, η _max , η _min , η _med respectively are the maximum value, minimum value and reference value of the fuel injection efficiency when the value of the characteristic parameter x changes, and x _max , x _min , and x _med are the maximum value, the minimum value and the reference value of the value of the characteristic parameter x, respectively. 6. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 1, is characterized in that: step (5) is specially: based on the DOE experimental design result of step (4), adopt quadratic polynomial response The prediction model of the needle valve response T _N and the fuel injection efficiency η is constructed using the surface model, and the unknown coefficient of the quadratic polynomial response surface prediction model is solved by the least squares regression method, and the coefficient of determination and the corrected coefficient of determination are used as the prediction model. measures of effectiveness; The calculation formula of the quadratic polynomial response surface prediction model is as follows:

In the formula, x _i is the ith component of the design variable x, α ₀ is a constant, α _i is a linear coefficient, α _ii is a quadratic coefficient, and a _ij is an interaction coefficient. 7. the multi-objective optimization method of a kind of electronically controlled fuel injector performance according to claim 1, is characterized in that: in step (7), the screening function calculation formula of electronically controlled fuel injector response characteristic and injection characteristic is as follows:

In the formula, F(X) is the screening function, and X is the design variable combination; The filter function F(X) is minimized, and the optimal solution of the multi-objective optimization design variable combination X of the electronically controlled injector is obtained. 8. the multi-objective optimization method of a kind of electronically controlled injector performance according to claim 1 is characterized in that: the design variable combination under the optimal performance of electronically controlled injector obtained in step (7) is substituted into In the numerical simulation model of the electronically controlled injector in step (1), the needle valve response T _N and the fuel injection efficiency η are calculated, and the calculation results are compared with the needle valve response reference value T _{N_med} and the fuel injection efficiency η _med .

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