CN113202669A - Multi-objective optimization method for performance of electric control oil injector - Google Patents

Multi-objective optimization method for performance of electric control oil injector Download PDF

Info

Publication number
CN113202669A
CN113202669A CN202110646964.3A CN202110646964A CN113202669A CN 113202669 A CN113202669 A CN 113202669A CN 202110646964 A CN202110646964 A CN 202110646964A CN 113202669 A CN113202669 A CN 113202669A
Authority
CN
China
Prior art keywords
response
characteristic
electric control
performance
injector
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110646964.3A
Other languages
Chinese (zh)
Other versions
CN113202669B (en
Inventor
范立云
周佳升
顾远琪
陈希
许菁
都坤
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Engineering University
Original Assignee
Harbin Engineering University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Harbin Engineering University filed Critical Harbin Engineering University
Priority to CN202110646964.3A priority Critical patent/CN113202669B/en
Publication of CN113202669A publication Critical patent/CN113202669A/en
Application granted granted Critical
Publication of CN113202669B publication Critical patent/CN113202669B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
    • F02M51/00—Fuel-injection apparatus characterised by being operated electrically
    • F02M51/06—Injectors peculiar thereto with means directly operating the valve needle
    • F02M51/061—Injectors peculiar thereto with means directly operating the valve needle using electromagnetic operating means
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
    • F02M61/00—Fuel-injectors not provided for in groups F02M39/00 - F02M57/00 or F02M67/00
    • F02M61/04—Fuel-injectors not provided for in groups F02M39/00 - F02M57/00 or F02M67/00 having valves, e.g. having a plurality of valves in series
    • F02M61/10—Other injectors with elongated valve bodies, i.e. of needle-valve type
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
    • F02M63/00—Other fuel-injection apparatus having pertinent characteristics not provided for in groups F02M39/00 - F02M57/00 or F02M67/00; Details, component parts, or accessories of fuel-injection apparatus, not provided for in, or of interest apart from, the apparatus of groups F02M39/00 - F02M61/00 or F02M67/00; Combination of fuel pump with other devices, e.g. lubricating oil pump
    • F02M63/0012—Valves
    • F02M63/0014—Valves characterised by the valve actuating means
    • F02M63/0015—Valves characterised by the valve actuating means electrical, e.g. using solenoid
    • F02M63/0017—Valves characterised by the valve actuating means electrical, e.g. using solenoid using electromagnetic operating means
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
    • F02M65/00—Testing fuel-injection apparatus, e.g. testing injection timing ; Cleaning of fuel-injection apparatus
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F02—COMBUSTION ENGINES; HOT-GAS OR COMBUSTION-PRODUCT ENGINE PLANTS
    • F02M—SUPPLYING COMBUSTION ENGINES IN GENERAL WITH COMBUSTIBLE MIXTURES OR CONSTITUENTS THEREOF
    • F02M65/00—Testing fuel-injection apparatus, e.g. testing injection timing ; Cleaning of fuel-injection apparatus
    • F02M65/001—Measuring fuel delivery of a fuel injector
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Mechanical Engineering (AREA)
  • Combustion & Propulsion (AREA)
  • Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Theoretical Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • General Physics & Mathematics (AREA)
  • Geometry (AREA)
  • Computer Hardware Design (AREA)
  • Electrical Control Of Air Or Fuel Supplied To Internal-Combustion Engine (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

The invention aims to provide a multi-objective optimization method for the performance of an electric control oil injector, which comprises the following steps: establishing a numerical simulation model of the electric control oil injector; providing evaluation indexes of performances such as response characteristics, injection characteristics and the like; performing significance analysis on characteristic parameters of each component of the electric control oil sprayer, and determining design variables of evaluation indexes; carrying out DOE experimental design on the design variables, and simulating to obtain a response value of the evaluation index; respectively constructing response surface prediction models of response characteristics and injection characteristics; carrying out multi-parameter optimization of design variables by taking the response characteristic and the optimal injection characteristic as optimization targets; and providing a screening function of the response characteristic and the injection characteristic of the electric control oil injector, and obtaining a corresponding design variable value when the performance of the electric control oil injector is optimal. The method can obtain the obvious influence parameters of the performance of the electric control oil sprayer, realize the accurate prediction of the response characteristic and the injection characteristic, and carry out multi-objective optimization on the design variable on the basis of simultaneously improving the response characteristic and the injection characteristic.

Description

Multi-objective optimization method for performance of electric control oil injector
Technical Field
The invention relates to an engine oil injection control method, in particular to an engine oil injector performance optimization method.
Background
The electronic control oil injector is used as the most complex and key part in a high-pressure common rail fuel injection system, the response characteristic, the injection characteristic and other properties of the electronic control oil injector determine the pressure relief speed, the oil injection timing and the oil injection quantity of a control cavity, and direct influence can be caused on the control precision of the oil injection rule of the high-pressure common rail fuel injection system, so that the quality of the working performance of a diesel engine is determined. And because the electric control oil injector is subjected to the coupling action of electromagnetic, mechanical, hydraulic and other multi-physical fields in the working process, the characteristic parameters of each part of the electric control oil injector can influence the response characteristic, the injection characteristic and other performances. Therefore, the multi-target multi-parameter optimization for improving the response characteristic, the injection characteristic and other performances of the electric control fuel injector is of great significance.
Because the number of characteristic parameters of each part of the electric control oil atomizer is large, and coupling action possibly exists among the characteristic parameters, the performance of the electric control oil atomizer is optimized through traditional experimental research, a large amount of manpower and material resources are consumed, and the defects of long research and development period and the like exist.
Meanwhile, the structural parameter optimization of the electric control oil injector mainly focuses on the optimization of single elements and single characteristics such as the flow characteristic of the oil injector, the static and dynamic characteristic of an electromagnetic actuator, the response characteristic of a needle valve and the like at present. Although the optimization methods can improve a certain specific characteristic of the electric control fuel injector, other characteristics of the electric control fuel injector may be sacrificed in the process of improving the specific characteristic, and the problems that the performance of the electric control fuel injector cannot be comprehensively and effectively improved exist.
Disclosure of Invention
The invention aims to provide a multi-objective optimization method for the performance of an electric control oil sprayer, which can carry out multi-objective optimization on the structural parameters of the electric control oil sprayer on the basis of simultaneously improving the response characteristic and the spraying characteristic.
The purpose of the invention is realized as follows:
the invention discloses a multi-target optimization method for the performance of an electric control oil injector, which is characterized by comprising the following steps:
(1) establishing a numerical simulation model of the electric control oil injector;
(2) providing evaluation indexes of the performance of the electric control oil sprayer such as response characteristics and injection characteristics;
(3) performing significance analysis on characteristic parameters of each component of the electric control oil sprayer, and determining design variables of evaluation indexes;
(4) carrying out DOE experimental design on the design variables, and simulating to obtain a response value of the evaluation index;
(5) respectively constructing response surface prediction models of response characteristics and jetting characteristics, and evaluating the effectiveness of the prediction models;
(6) based on the response surface prediction model in the step 5, carrying out multi-parameter optimization of design variables by taking response characteristic and optimal injection characteristic as optimization targets;
(7) and providing a screening function of the response characteristic and the injection characteristic of the electric control oil injector, and obtaining a corresponding design variable value when the performance of the electric control oil injector is optimal.
The present invention may further comprise:
1. the process of establishing the numerical simulation model of the electric control fuel injector in the step (1) comprises the following steps: and (3) deriving a differential motion equation of the electric control oil injector based on a power bonding diagram theory, and building a numerical simulation model of the electric control oil injector.
2. The evaluation indexes of the performance such as the response characteristic and the injection characteristic in the step (2) are as follows:
the evaluation index of the response characteristic is needle valve response TNNeedle valve response TNThe calculation formula of (a) is as follows:
Figure BDA0003110272790000021
wherein, TNResponsive to needle valve, TOThe time required for electrifying a high-speed electromagnetic valve of the oil injector until a needle valve is opened to the maximum lift is TCThe time is required from the power failure of a high-speed electromagnetic valve of the oil injector to the complete closing of a needle valve;
the evaluation index of the injection characteristic is the oil injection efficiency eta, and the calculation formula of the oil injection efficiency eta is as follows:
Figure BDA0003110272790000022
where eta is the injection efficiency, QcycleQuantity of fuel injected into cylinder for injector in single cycle, QinFor the quantity of fuel entering the injector in a single cycle, QleakIs the fuel leakage quantity, Q, of the fuel injector under single circulationbackThe oil return quantity of the oil injector under a single circulation is shown.
3. The characteristic parameters of each part subjected to significance analysis in the step (3) are as follows:
the characteristic parameters of the electromagnetic valve comprise: the method comprises the following steps of (1) electromagnetic valve quality, electromagnetic valve residual air gap, electromagnetic valve maximum lift, electromagnetic valve spring pre-tightening force, electromagnetic valve spring stiffness, electromagnetic valve sealing ball diameter and electromagnetic valve hole diameter;
controlling the cavity characteristic parameters includes: the diameter of the oil inlet throttling hole, the diameter of the oil return throttling hole and the volume of the control cavity;
the needle valve characteristic parameters comprise: the needle valve assembly quality, the maximum lift of the needle valve, the pretightening force of a needle valve spring, the rigidity of the needle valve spring, the volume of an oil containing groove, the volume of a needle valve cavity and the diameter of a spray hole.
4. The specific steps for determining the design variables of the evaluation indexes in the step (3) are as follows:
and respectively calculating the influence factors of the characteristic parameters of each part, and then respectively calculating the percentage of the calculation influence factors of the characteristic parameters of each part in the total value, thereby determining the design variables of the evaluation indexes. The calculation formula of the influence factor is as follows:
Figure BDA0003110272790000031
wherein σxAn influence factor, T, of a characteristic parameter xN_max、TN_min、TmedThe maximum value, the minimum value and the reference value, eta, of the valve response when the characteristic parameter x changesmax、ηmin、ηmedRespectively the maximum value, the minimum value and the reference value of the oil injection efficiency when the value of the characteristic parameter x is changed, xmax、xmin、xmedRespectively a maximum value, a minimum value and a reference value of the characteristic parameter x.
5. The step (4) is specifically as follows: designing a design variable by adopting a D-optimal experimental design method to carry out DOE scheme design, respectively substituting the obtained DOE design schemes of the design variable into a numerical simulation model of the electric control fuel injector, and responding T to the needle valveNAnd calculating and solving the fuel injection efficiency eta.
6. The step (5) is specifically as follows: based on the DOE experimental design result of the step (4), adopting a quadratic polynomial response surface model to perform needle valve response TNConstructing a prediction model of the oil injection efficiency eta, solving unknown coefficients of a quadratic polynomial response surface prediction model by using a least square regression method, and using a curability coefficient and a correction curability coefficient as measurement indexes of the effectiveness of the prediction model;
the quadratic polynomial response surface prediction model calculation formula is as follows:
Figure BDA0003110272790000032
in the formula, xiTo design the ith component, α, of the variable x0Is a constant, αiIs a linear coefficient, alphaiiIs a quadratic coefficient, aijIs the interaction coefficient.
7. The step (6) is specifically as follows: response T with needle valveNThe minimum and the maximum of the fuel injection efficiency eta are optimized targets, the value range of design variables is taken as constraint, and the needle valve response T constructed in the step (5) is based onNAnd calculating with a prediction model of the oil injection efficiency eta by using a genetic algorithm to obtain a Pareto solution set meeting all constraint conditions.
8. The screening function calculation formula of the response characteristic and the injection characteristic of the electric control oil injector in the step (7) is as follows:
Figure BDA0003110272790000033
wherein F (X) is a screening function, and X is a design variable combination;
and (5) minimizing the screening function F (X) to obtain the optimal solution of the multi-objective optimization design variable combination X of the electric control fuel injector.
9. Substituting the design variable combination obtained in the step (7) under the condition of optimal performance of the electric control fuel injector into the numerical simulation model of the electric control fuel injector in the step (1) to respond T to the needle valveNCalculating the fuel injection efficiency eta, and comparing the calculation result with a needle valve response reference value TN_medAnd the efficiency η of oil injectionmedAnd (6) carrying out comparison.
The invention has the advantages that:
1. the evaluation indexes of the response characteristic and the injection characteristic of the electric control oil injector are provided, the characteristic parameters of each component are subjected to significance analysis to obtain the characteristic parameters which have significant influence on the evaluation indexes, and therefore the design variables of the evaluation indexes are determined;
2. according to the invention, DOE experimental design is carried out on design variables, a response surface prediction model of response characteristics and injection characteristics is constructed, and the effectiveness of the prediction model is evaluated, so that the accurate prediction of the response characteristics and the injection characteristics is ensured, and the defects of large consumption of manpower and material resources, long research and development period and the like in the traditional experimental research are overcome;
3. the method takes the optimal response characteristic and the optimal injection characteristic as optimization targets, takes the value range of design variables as constraint, carries out multi-objective optimization of the performance of the electric control oil sprayer based on a genetic algorithm, and solves the problems that the performance of the electric control oil sprayer is not comprehensively optimized and is not efficient by the existing optimization method.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 shows the significance analysis result of characteristic parameters of each component;
FIG. 3 is a comparison graph of a predicted value and a simulation value of a quadratic polynomial response surface model of needle valve response;
FIG. 4 is a comparison graph of a second-order polynomial response surface model predicted value and a simulation value of oil injection efficiency;
FIG. 5 is a Pareto solution set for multi-objective optimization of fuel injector performance;
FIG. 6 is a comparison of results before and after optimization of fuel injector performance.
Detailed Description
The invention will now be described in more detail by way of example with reference to the accompanying drawings in which:
with reference to fig. 1-6, the invention relates to a multi-objective optimization method for the performance of an electric control fuel injector, which comprises the following steps:
step 1, establishing a numerical simulation model of the electric control oil injector and verifying the accuracy of the numerical simulation model;
specifically, a differential motion equation of the electric control oil injector is deduced based on a power bonding diagram theory, a numerical simulation model of the electric control oil injector is built, and model accuracy is verified.
Step 2, providing evaluation indexes of the performance of the electric control oil sprayer such as response characteristics and injection characteristics;
specifically, the evaluation index of the response characteristic is the needle valve response TN. Needle valve response TNThe calculation formula of (a) is as follows:
Figure BDA0003110272790000051
wherein, TNResponsive to needle valve, TOThe time required for electrifying a high-speed electromagnetic valve of the oil injector until a needle valve is opened to the maximum lift is TCThe time is required for the high-speed electromagnetic valve of the fuel injector to be powered off until the needle valve is closed to be complete.
The evaluation index of the injection characteristic is the injection efficiency η. The calculation formula of the oil injection efficiency eta is as follows:
Figure BDA0003110272790000052
where eta is the injection efficiency, QcycleThe amount of fuel injected into the cylinder by the fuel injector for a single cycle; qinThe amount of fuel entering the fuel injector in a single cycle; qleakThe fuel leakage rate of the fuel injector under single circulation; qbackThe oil return quantity of the oil injector under a single circulation is shown.
Step 3, performing significance analysis on characteristic parameters of each part of the electric control oil sprayer, and determining design variables of evaluation indexes;
specifically, the characteristic parameters of each component subjected to significance analysis are as follows:
the characteristic parameters of the electromagnetic valve comprise: the method comprises the following steps of (1) electromagnetic valve quality, electromagnetic valve residual air gap, electromagnetic valve maximum lift, electromagnetic valve spring pre-tightening force, electromagnetic valve spring stiffness, electromagnetic valve sealing ball diameter and electromagnetic valve hole diameter;
controlling the cavity characteristic parameters includes: the diameter of the oil inlet throttling hole, the diameter of the oil return throttling hole and the volume of the control cavity;
the needle valve characteristic parameters comprise: the needle valve assembly quality, the maximum lift of the needle valve, the pretightening force of a needle valve spring, the rigidity of the needle valve spring, the volume of an oil containing groove, the volume of a needle valve cavity and the diameter of a spray hole.
The specific steps for determining the design variables of the evaluation index are as follows:
and respectively calculating the influence factors of the characteristic parameters of each part, and then respectively calculating the percentage of the calculation influence factors of the characteristic parameters of each part in the total value, thereby determining the design variables of the evaluation indexes. The calculation formula of the influence factor is as follows:
Figure BDA0003110272790000053
wherein σxAn influence factor, T, of a characteristic parameter xN_max、TN_min、TmedThe maximum value, the minimum value and the reference value, eta, of the valve response when the characteristic parameter x changesmax、ηmin、ηmedRespectively the maximum value, the minimum value and the reference value of the oil injection efficiency when the value of the characteristic parameter x is changed, xmax、xmin、xmedRespectively a maximum value, a minimum value and a reference value of the characteristic parameter x.
According to the characteristic parameter significance analysis result of each part shown in fig. 2, the design variables for determining the evaluation index are the diameter of the sealing ball of the electromagnetic valve, the diameter of the oil inlet throttle hole, the diameter of the oil return throttle hole, the maximum lift of the needle valve and the diameter of the spray hole.
Step 4, carrying out DOE experimental design on the design variables, and simulating to obtain the response value of the evaluation index;
specifically, design variables are subjected to DOE scheme design by adopting a D-optimal experimental design method, the obtained DOE design schemes of the design variables are respectively substituted into the numerical simulation model of the electric control fuel injector, and response T is given to the needle valveNAnd calculating and solving the fuel injection efficiency eta.
Step 5, respectively constructing response surface prediction models of response characteristics and jetting characteristics, and evaluating the effectiveness of the prediction models;
specifically, based on the DOE experimental design result of the step 4, a quadratic polynomial response surface model is adopted to perform needle valve response TNAnd constructing a prediction model of the oil injection efficiency eta. And solving the unknown coefficient of the quadratic polynomial response surface prediction model by using a least square regression method. According to the needle valve response T shown in FIGS. 3 and 4NCompared with the predicted value and the simulation value of the quadratic polynomial response surface model of the oil injection efficiency eta, the coefficient of decision and the coefficient of correction of the coefficient of decision are both close to 1, and the prediction capability of the prediction model is better.
Step 6, based on the response surface prediction model in the step 5, carrying out multi-parameter optimization of design variables by taking response characteristics and optimal injection characteristics as optimization targets;
in particular, with needle valve response TNThe minimum and maximum fuel injection efficiency eta are optimized targets, the value range of design variables is taken as constraint, and the needle valve response T constructed in the step 5 is based onNAnd calculating a prediction model of the oil injection efficiency eta by using a genetic algorithm to obtain a Pareto solution set shown in the figure 5.
Step 7, providing a screening function of the response characteristic and the injection characteristic of the electric control oil injector, and obtaining a corresponding design variable value when the performance of the electric control oil injector is optimal;
specifically, a screening function calculation formula of the response characteristic and the injection characteristic of the electric control oil injector is as follows:
Figure BDA0003110272790000061
wherein F (X) is a screening function and X is a design variable combination.
Minimizing the screening function F (X) to obtain an optimal solution of the multi-target optimization design variable combination X of the electric control fuel injector: the diameter of a sealing ball of the electromagnetic valve, the diameter of an oil inlet throttling hole, the diameter of an oil return throttling hole, the maximum lift of a needle valve and the diameter of a spraying hole are respectively 1.600mm, 0.233mm, 0.280mm, 0.200mm and 0.160 mm.
And 8, comparing results before and after optimization based on the numerical simulation model of the electronic control fuel injector in the step 1.
Substituting the design variable combination obtained in the step 7 under the condition of optimal performance of the electric control fuel injector into the numerical simulation model of the electric control fuel injector in the step 1, and responding T to the needle valveNCalculating the fuel injection efficiency eta, and comparing the calculation result with a needle valve response reference value TN_medAnd the efficiency η of oil injectionmedAnd (6) carrying out comparison. As can be seen from the comparison shown in FIG. 6, the needle response TNThe response speed is improved by 14.86% by reducing the time from 0.898ms to 0.764 ms; the fuel injection efficiency eta is increased from 75.849% to 76.997%, and the fuel injection efficiency is improved by 1.51%.

Claims (10)

1. A multi-objective optimization method for the performance of an electric control oil injector is characterized by comprising the following steps:
(1) establishing a numerical simulation model of the electric control oil injector;
(2) providing evaluation indexes of the performance of the electric control oil sprayer such as response characteristics and injection characteristics;
(3) performing significance analysis on characteristic parameters of each component of the electric control oil sprayer, and determining design variables of evaluation indexes;
(4) carrying out DOE experimental design on the design variables, and simulating to obtain a response value of the evaluation index;
(5) respectively constructing response surface prediction models of response characteristics and jetting characteristics, and evaluating the effectiveness of the prediction models;
(6) based on the response surface prediction model in the step 5, carrying out multi-parameter optimization of design variables by taking response characteristic and optimal injection characteristic as optimization targets;
(7) and providing a screening function of the response characteristic and the injection characteristic of the electric control oil injector, and obtaining a corresponding design variable value when the performance of the electric control oil injector is optimal.
2. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the process of establishing the numerical simulation model of the electric control fuel injector in the step (1) comprises the following steps: and (3) deriving a differential motion equation of the electric control oil injector based on a power bonding diagram theory, and building a numerical simulation model of the electric control oil injector.
3. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the evaluation indexes of the performance such as the response characteristic and the injection characteristic in the step (2) are as follows:
the evaluation index of the response characteristic is needle valve response TNNeedle valve response TNThe calculation formula of (a) is as follows:
Figure FDA0003110272780000011
wherein, TNResponsive to needle valve, TOThe time required for electrifying a high-speed electromagnetic valve of the oil injector until a needle valve is opened to the maximum lift is TCThe time is required from the power failure of a high-speed electromagnetic valve of the oil injector to the complete closing of a needle valve;
the evaluation index of the injection characteristic is the oil injection efficiency eta, and the calculation formula of the oil injection efficiency eta is as follows:
Figure FDA0003110272780000012
where eta is the injection efficiency, QcycleQuantity of fuel injected into cylinder for injector in single cycle, QinFor the quantity of fuel entering the injector in a single cycle, QleakIs the fuel leakage quantity, Q, of the fuel injector under single circulationbackThe oil return quantity of the oil injector under a single circulation is shown.
4. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the characteristic parameters of each part subjected to significance analysis in the step (3) are as follows:
the characteristic parameters of the electromagnetic valve comprise: the method comprises the following steps of (1) electromagnetic valve quality, electromagnetic valve residual air gap, electromagnetic valve maximum lift, electromagnetic valve spring pre-tightening force, electromagnetic valve spring stiffness, electromagnetic valve sealing ball diameter and electromagnetic valve hole diameter;
controlling the cavity characteristic parameters includes: the diameter of the oil inlet throttling hole, the diameter of the oil return throttling hole and the volume of the control cavity;
the needle valve characteristic parameters comprise: the needle valve assembly quality, the maximum lift of the needle valve, the pretightening force of a needle valve spring, the rigidity of the needle valve spring, the volume of an oil containing groove, the volume of a needle valve cavity and the diameter of a spray hole.
5. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 4, wherein: the specific steps for determining the design variables of the evaluation indexes in the step (3) are as follows:
and respectively calculating the influence factors of the characteristic parameters of each part, and then respectively calculating the percentage of the calculation influence factors of the characteristic parameters of each part in the total value, thereby determining the design variables of the evaluation indexes. The calculation formula of the influence factor is as follows:
Figure FDA0003110272780000021
wherein σxAn influence factor, T, of a characteristic parameter xN_max、TN_min、TmedMaximum value and maximum value of the valve response when the value of the characteristic parameter x changesSmall value and reference value, etamax、ηmin、ηmedRespectively the maximum value, the minimum value and the reference value of the oil injection efficiency when the value of the characteristic parameter x is changed, xmax、xmin、xmedRespectively a maximum value, a minimum value and a reference value of the characteristic parameter x.
6. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the step (4) is specifically as follows: designing a design variable by adopting a D-optimal experimental design method to carry out DOE scheme design, respectively substituting the obtained DOE design schemes of the design variable into a numerical simulation model of the electric control fuel injector, and responding T to the needle valveNAnd calculating and solving the fuel injection efficiency eta.
7. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the step (5) is specifically as follows: based on the DOE experimental design result of the step (4), adopting a quadratic polynomial response surface model to perform needle valve response TNConstructing a prediction model of the oil injection efficiency eta, solving unknown coefficients of a quadratic polynomial response surface prediction model by using a least square regression method, and using a curability coefficient and a correction curability coefficient as measurement indexes of the effectiveness of the prediction model;
the quadratic polynomial response surface prediction model calculation formula is as follows:
Figure FDA0003110272780000022
in the formula, xiTo design the ith component, α, of the variable x0Is a constant, αiIs a linear coefficient, alphaiiIs a quadratic coefficient, aijIs the interaction coefficient.
8. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the step (6) is specifically as follows: response T with needle valveNMinimum and maximum oil injection efficiency eta are optimizedThe target is based on the needle valve response T constructed in the step (5) by taking the value range of the design variable as the constraintNAnd calculating with a prediction model of the oil injection efficiency eta by using a genetic algorithm to obtain a Pareto solution set meeting all constraint conditions.
9. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: the screening function calculation formula of the response characteristic and the injection characteristic of the electric control oil injector in the step (7) is as follows:
Figure FDA0003110272780000031
wherein F (X) is a screening function, and X is a design variable combination;
and (5) minimizing the screening function F (X) to obtain the optimal solution of the multi-objective optimization design variable combination X of the electric control fuel injector.
10. The method for multi-objective optimization of performance of an electrically controlled fuel injector as claimed in claim 1, wherein: substituting the design variable combination obtained in the step (7) under the condition of optimal performance of the electric control fuel injector into the numerical simulation model of the electric control fuel injector in the step (1) to respond T to the needle valveNCalculating the fuel injection efficiency eta, and comparing the calculation result with a needle valve response reference value TN_medAnd the efficiency η of oil injectionmedAnd (6) carrying out comparison.
CN202110646964.3A 2021-06-10 2021-06-10 Multi-objective optimization method for performance of electric control oil injector Active CN113202669B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110646964.3A CN113202669B (en) 2021-06-10 2021-06-10 Multi-objective optimization method for performance of electric control oil injector

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110646964.3A CN113202669B (en) 2021-06-10 2021-06-10 Multi-objective optimization method for performance of electric control oil injector

Publications (2)

Publication Number Publication Date
CN113202669A true CN113202669A (en) 2021-08-03
CN113202669B CN113202669B (en) 2022-07-15

Family

ID=77024367

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110646964.3A Active CN113202669B (en) 2021-06-10 2021-06-10 Multi-objective optimization method for performance of electric control oil injector

Country Status (1)

Country Link
CN (1) CN113202669B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114201921A (en) * 2021-12-17 2022-03-18 中国船舶重工集团公司第七一一研究所 Optimal design method for pilot valve of oil injector

Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0971119A2 (en) * 1998-07-08 2000-01-12 Isuzu Motors Limited Common-rail fuel-injection system
JP2000297678A (en) * 1999-04-14 2000-10-24 Nissan Motor Co Ltd Fuel property detection system and fuel supply control system for engine
DE10021072A1 (en) * 1999-05-14 2001-09-27 Aisan Ind Fuel injector
US20030121501A1 (en) * 2002-01-02 2003-07-03 Barnes Travis E. Utilization of a rail pressure predictor model in controlling a common rail fuel injection system
US20100145597A1 (en) * 2008-12-05 2010-06-10 Keegan Kevin R Method and apparatus for characterizing fuel injector performance to reduce variability in fuel injection
CN103197596A (en) * 2013-03-14 2013-07-10 天津大学 Numerical control machining parameter adaptive fuzzy control rule optimization method
CN103729508A (en) * 2013-12-24 2014-04-16 潍柴动力股份有限公司 Fuel injector model selection method and fuel injector model selection device
CN103835851A (en) * 2013-12-06 2014-06-04 潍柴动力股份有限公司 Oil atomizer model selection method and device
CN106089524A (en) * 2016-06-14 2016-11-09 吉林大学 High pressure co-rail system based on genetic algorithm and parameter optimization method
CN107975418A (en) * 2016-10-21 2018-05-01 通用汽车环球科技运作有限责任公司 Multivariable motor torque and discharge closed-loop control for internal combustion engine
DE102018116364A1 (en) * 2017-07-07 2019-01-10 GM Global Technology Operations LLC OPTIMIZING THE CURRENT PROCESSING OF INJECTION FOR ELECTROMAGNETIC OPERATED NOZZLES
CN109595087A (en) * 2019-01-29 2019-04-09 吉林大学 A kind of distributive value oscillation compensation control method based on learning algorithm
CN110287636A (en) * 2019-07-03 2019-09-27 天津职业技术师范大学(中国职业培训指导教师进修中心) A kind of high-speed electromagnetic valve dynamic response characteristic Multipurpose Optimal Method

Patent Citations (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0971119A2 (en) * 1998-07-08 2000-01-12 Isuzu Motors Limited Common-rail fuel-injection system
JP2000297678A (en) * 1999-04-14 2000-10-24 Nissan Motor Co Ltd Fuel property detection system and fuel supply control system for engine
DE10021072A1 (en) * 1999-05-14 2001-09-27 Aisan Ind Fuel injector
US20030121501A1 (en) * 2002-01-02 2003-07-03 Barnes Travis E. Utilization of a rail pressure predictor model in controlling a common rail fuel injection system
US20100145597A1 (en) * 2008-12-05 2010-06-10 Keegan Kevin R Method and apparatus for characterizing fuel injector performance to reduce variability in fuel injection
CN103197596A (en) * 2013-03-14 2013-07-10 天津大学 Numerical control machining parameter adaptive fuzzy control rule optimization method
CN103835851A (en) * 2013-12-06 2014-06-04 潍柴动力股份有限公司 Oil atomizer model selection method and device
CN103729508A (en) * 2013-12-24 2014-04-16 潍柴动力股份有限公司 Fuel injector model selection method and fuel injector model selection device
CN106089524A (en) * 2016-06-14 2016-11-09 吉林大学 High pressure co-rail system based on genetic algorithm and parameter optimization method
CN107975418A (en) * 2016-10-21 2018-05-01 通用汽车环球科技运作有限责任公司 Multivariable motor torque and discharge closed-loop control for internal combustion engine
DE102018116364A1 (en) * 2017-07-07 2019-01-10 GM Global Technology Operations LLC OPTIMIZING THE CURRENT PROCESSING OF INJECTION FOR ELECTROMAGNETIC OPERATED NOZZLES
CN109595087A (en) * 2019-01-29 2019-04-09 吉林大学 A kind of distributive value oscillation compensation control method based on learning algorithm
CN110287636A (en) * 2019-07-03 2019-09-27 天津职业技术师范大学(中国职业培训指导教师进修中心) A kind of high-speed electromagnetic valve dynamic response characteristic Multipurpose Optimal Method

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
付立洲: "船用低速机电控喷油器的设计及性能研究", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》 *
扈爽: "中高速柴油机电控喷油器设计与性能研究", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》 *
费红姿，屈超，魏云鹏，李瑞良: "高压共轨柴油机循环喷油量预测模型仿真研究", 《哈尔滨工程大学学报》 *
郭世龙等: "喷油器结构参数与喷油一致性相关关系的试验研究", 《车用发动机》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114201921A (en) * 2021-12-17 2022-03-18 中国船舶重工集团公司第七一一研究所 Optimal design method for pilot valve of oil injector

Also Published As

Publication number Publication date
CN113202669B (en) 2022-07-15

Similar Documents

Publication Publication Date Title
CN109595087A (en) A kind of distributive value oscillation compensation control method based on learning algorithm
CN113202669B (en) Multi-objective optimization method for performance of electric control oil injector
CN103502614A (en) Control method for an injection valve and injection system
Zhao et al. Investigation on Electromagnetic Models of High‐Speed Solenoid Valve for Common Rail Injector
Bai et al. Effect of injector parameters on the injection quantity of common rail injection system for diesel engines
Hofmann et al. Optimal injection strategies to compensate for injector aging in common rail fuel systems
CN114239433B (en) Multi-physical decoupling-coupling method for high-pressure common rail system
CN116611292A (en) High-pressure oil pump needle valve seating knocking prediction method and device, electronic equipment and medium
CN114934848B (en) Fuzzy neural network modeling method for optimizing control of combustion performance of diesel engine
Mazzi et al. Hybrid system reduction
di Gaeta et al. Modelling of an electro-hydraulic variable valve actuator for camless engines aimed at controlling valve lift parameters
Kang et al. Control-oriented cyclic modeling method for spark ignition engines
CN102639847B (en) For running method and the controller of valve
Ventura et al. Air path and combustion controls coordination in diesel engine
Min et al. Iterative learning control algorithm for feedforward controller of EGR and VGT systems in a CRDI diesel engine
Liu et al. Introduction to the benchmark challenge on common rail pressure control of gasoline direct injection engines
Yu et al. Multi-objective cooperation optimization research on dynamic response and energy loss of high-speed solenoid valve for diesel engine injector
Gu et al. Multi-objective optimization of high-speed solenoid valve for biodiesel electronic unit pump
Lan et al. Multi-Objective Optimization of Response Characteristics for High Power Common Rail Injector
Qifang et al. Nonlinear GDI rail pressure control: design, analysis and experimental implementation
Ventura et al. Recurrent Neural Network to Estimate Intake Manifold O 2 Concentration in a Diesel Engine
CN113153553B (en) Optimization method for linear characteristic of oil injection quantity of electric control oil injector
Luján et al. A comparison of different algorithms for boost pressure control in a heavy-duty turbocharged diesel engine
Tomaselli et al. Common-rail pressure control using a model reference adaptive control approach
Sakawaki et al. Real-time engine control parameters optimization method for small diesel engine by multi objective genetic algorithm

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant