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Automotive Engineering ›› 2021, Vol. 43 ›› Issue (2): 232-240.doi: 10.19562/j.chinasae.qcgc.2021.02.011

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Research on Prediction of State Parameters and Structure Optimization of Diesel Engine Cylinder Gasket

Yi Dong1,Jianmin Liu1,Pu Li2,Yanbin Liu1(),Xinyong Qiao1   

  1. 1.Vehicle Engineering Department,Army Academy of Armored Forces,Beijing 100072
    2.Chinese People’s Liberation Army No. 6456 Factory,Nanyang 473000
  • Received:2020-07-17 Revised:2020-09-17 Online:2021-02-25 Published:2021-03-04
  • Contact: Yanbin Liu E-mail:aafelyb@163.com

Abstract:

In order to improve the reliability and fatigue life of a heavy?duty diesel engine cylinder head gasket, based on its state parameters such as temperature field, thermal?mechanical coupling stress field and deformation, the working parameters of the cylinder head gasket are optimized using related methods. The orthogonal experiment method is used to analyze the influence of the five working parameters of cylinder circle diameter, water hole circle diameter, heat insulation strip length, cylinder gasket thickness and bolt pre?tightening force on the above three state parameters, with the four most significant working parameters defined . Using the proposed hybrid neural network model, the corresponding relationship model between the working parameters and the state parameters is established, and the optimal working parameter value of the cylinder head gasket is calculated and determined in combination with the proposed improved gray wolf algorithm. The finite element analysis results show that the temperature stress and deformation of the cylinder head gasket after the improvement have been significantly improved, which proves the effectiveness of the improvement and the accuracy of the algorithm.

Key words: diesel engine, cylinder head gasket, optimization, hybrid neural network, improved grey wolf algorithm