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Cylinder Pressure Prediction of An HCCI Engine Using Deep Learning

Chinese Journal of Mechanical Engineering 2021年第2期34卷 160-167页

作者： Halit Yaşar GültekinÇağıl orha. torkul MerveŞişci Department of Mechanical Engineering Engineering FacultySakarya UniversityEsentepe Campus54187 SerdivanSakaryaTurkey Department of Industrial Engineering Engineering FacultySakarya UniversityEsentepe Campus54187 SerdivanSakaryaTurkey

Engine tests are both costly and time consuming in developing a new internal combustion ***,it is of great importance to predict engine characteristics with high accuracy using artificial ***,it is possible to reduce engine testing costs and speed up the engine development *** Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data *** present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition(HCCI)engine for various excess air coefficients by using Deep Neural Network,which is one of the Deep Learning methods and is based on the Artificial Neural Network(ANN).The Deep Learning results were compared with the ANN and experimental *** results show that the difference between experimental and the Deep Neural Network(DNN)results were less than 1%.The best results were obtained by Deep Learning *** cylinder pressure was predicted with a maximum accuracy of 97.83%of the experimental value by using *** the other hand,the accuracy value was increased up to 99.84%using *** results show that the DNN method can be used effectively to predict cylinder pressures of internal combustion engines.

关键词： Artificial neural network Deep neural network HCCI engine Cylinder pressure Excess air coefficient

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