A RBFNN &amp; GACMOO-Based Working State Optimization Control Study on Heavy-Duty Diesel Engine Working in Plateau Environment

Dong, Yi; Liu, Jianmin; Liu, Yanbin; Qiao, Xinqi; Zhang, Xiaoming; Jin, Ying; Zhang, Shaoliang; Wang, Tianqi; Kang, Qi

doi:10.3390/en13010279

Cited by 9 publications

(5 citation statements)

References 31 publications

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“…e configuration of the test bench is shown in Figure 2. It is a device used to determine the state of combustion in the diesel engine and measure the parameters of the gas in the cylinder [29]. e test system is mainly made up of several parts, including computer control system, diesel and its start moto, output dynamo meter, diesel combustion analysis system, and system control unit.…”

Section: Boundary Conditions Of Piston Temperature and Stress Fieldsmentioning

confidence: 99%

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

Qi¹,

Dong²,

Liu³

et al. 2021

Mathematical Problems in Engineering

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In order to increase the reliability and service life of piston in a heavy-duty diesel engine, the geometric structure of piston was optimized based on its maximum temperature and maximum coupling stress. To begin with, the boundary conditions of thermal and stress fields are calculated, which include the heat produced by the combustion in cylinder, the friction-induced heat, and the heat transferred to cooling system. Then, the finite element model was established to calculate and analyse the temperature and thermal-mechanical coupling stress fields of the piston. By combining this simulation model with orthogonal experimental design methods, computations and analyses were performed to determine how the five geometric parameters (depth of intake and exhaust valve grooves, radius of valve grooves transition, radius of top of valve grooves, height of first piston ring groove, and depth of piston ring groove) influence the two evaluation indicators (maximum temperature and maximum stress of piston). Subsequently, using the proposed ABC-OED- FE (artificial bee colony, orthogonal experiment design, and fitting equations) method, the fitting equations between the geometric parameters and evaluation indicators were determined. Taking the minimum values of two evaluation indicators of piston as optimization objectives, artificial bee colony method was run to determine the values of parameters. At last, the two evaluation indicators of the optimized piston were computed. The results indicate that, after optimization, the maximum temperature of piston decreases to be 16.05 K and the maximum stress decreases to be 13.54 MPa. Both temperature and stress conditions of the optimized piston had been improved, which demonstrates the effectiveness of the optimization and the validity of the algorithm.

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Section: Boundary Conditions Of Piston Temperature and Stress Fieldsmentioning

confidence: 99%

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

Qi¹,

Dong²,

Liu³

et al. 2021

Mathematical Problems in Engineering

Self Cite

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“…Qin Zhaoju et al [5] analyze and optimize a piston in a diesel engine with finite element and multidisciplinary optimization methods. There are also some studies that focus on parameter study of piston [6], coated properties [7], diesel engine combustion [8], the geometry of piston [9], and stress analysis [10].…”

Section: Introductionmentioning

confidence: 99%

Creep–Fatigue Experiment and Life Prediction Study of Piston 2A80 Aluminum Alloy

Dong¹,

Liu²,

Liu³

et al. 2021

Materials

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In order to improve the reliability and service life of vehicle and diesel engine, the fatigue life prediction of the piston in a heavy diesel engine was studied by finite element analysis of piston, experiment data of aluminum alloy, fatigue life model based on energy dissipation criteria, and machine learning algorithm. First, the finite element method was used to calculate and analyze the temperature field, thermal stress field, and thermal–mechanical coupling stress field of the piston, and determine the area of heavy thermal and mechanical load that will affect the fatigue life of the piston. Second, based on the results of finite element calculation, the creep–fatigue experiment of 2A80 aluminum alloy was carried out, and the cyclic response characteristics of the material under different loading conditions were obtained. Third, the fatigue life prediction models based on energy dissipation criterion and twin support vector regression are proposed. Then, the accuracy of the two models was verified using experiment data. The results show that the model based on the twin support vector regression is more accurate for predicting the material properties of aluminum alloy. Based on the established life prediction model, the fatigue life of pistons under actual service conditions is predicted. The calculation results show that the minimum fatigue life of the piston under plain condition is 2113.60 h, and the fatigue life under 5000 m altitude condition is 1425.70 h.

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“…There are also many researches focus on the orthogonal experiment, [15][16][17][18] Multiobjective optimization for engineering problems, [19][20][21] crashworthiness, [22][23][24] sheet metal forming, 25,26 composite structure 27-29 and et al In this study, the finite element method is combined with orthogonal experiment design, dynamically guided multi-objective optimization, and non-dominated sorting genetic algorithm to geometrically optimize the working state of cylinder gasket. This study is organized as follows: In Section 1, temperature field, thermalmechanical coupling stress field, and deformation of the cylinder gasket were analyzed using the finite element method.…”

Section: Introductionmentioning

confidence: 99%

“…There are also many researches focus on the orthogonal experiment, 15 – 18 Multi-objective optimization for engineering problems, 19 – 21 crashworthiness, 22 – 24 sheet metal forming, 25 , 26 composite structure 27 – 29 and et al…”

Section: Introductionmentioning

confidence: 99%

Structure optimization of gasket based on orthogonal experiment and NSGA-II

Dong¹,

Liu²,

Liu³

et al. 2021

Science Progress

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With the aim of enhancing both reliability and fatigue life of gasket, this study combines finite element analysis, orthogonal experimental design, dynamically-guided multi-objective optimization, and the non-dominated sorting genetic algorithm with elitist strategy to optimize the geometric parameters of the cylinder gasket. The finite element method was used to analyze the temperature field, thermal-mechanical coupling stress field, and deformation of cylinder gasket. The calculation results were experimentally validated by measured temperature data, and comparison results show that the maximum error between calculated value and experiment value is 7.1%, which is acceptable in engineering problems. Based on above results and orthogonal experiment design method, the effects of five factors, including diameter of combustion chamber circle, diameter of coolant flow hole, length of the insulation zone between third and fourth cylinders, thickness of gasket, and bolt preload, on three indexes: temperature, stress, and deformation of gasket, were examined in depth. Through the variance analysis of the results, three important factors were identified to proceed later calculation. The dynamically guided multi-objective optimization strategy and the non-dominated sorting genetic algorithm were effectively used and combined to determine the optimal geometric parameters of cylinder gasket. Furthermore, calculation results suggest that temperature, stress, and deformation of the optimized cylinder gasket have been improved by 27.88 K, 16.84 MPa, and 0.0542 mm, respectively when compared with the origin object, which shows the excellent performance of gasket optimization and effectiveness of the proposed optimization strategy.

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A RBFNN & GACMOO-Based Working State Optimization Control Study on Heavy-Duty Diesel Engine Working in Plateau Environment

Cited by 9 publications

References 31 publications

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

Analysis and Optimization Study of Piston in Diesel Engine Based on ABC-OED-FE Method

Creep–Fatigue Experiment and Life Prediction Study of Piston 2A80 Aluminum Alloy

Structure optimization of gasket based on orthogonal experiment and NSGA-II

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