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진동신호를 이용한 CNG-디젤 이종연료 엔진 연소압력 예측 DNN 모델에서 천연가스 대체율 및 디젤 분사시기가 예측 정확도에 미치는 영향
김경곤(Gyeonggon Kim),박찬수(Chansoo Park),김우영(Wooyeong Kim),전지연(Jeeyeon Jeon),전미연(Miyeon Jeon),배충식(Choongsik Bae) 한국자동차공학회 2021 한국 자동차공학회논문집 Vol.29 No.10
In-cylinder pressure of a single-cylinder dual-fuel engine using compressed natural gas(CNG) and diesel was predicted from engine block vibration. A supervised learning model was built using a deep neural network (DNN). Vibration and in-cylinder pressure signals measured by the accelerometer and piezoelectric pressure sensor were used as input and output labels. A parametric study was conducted in order to check the effects of the composition of train conditions on the accuracy of the model. CNG substitution ratio and diesel injection timing were selected as main parameters. Train conditions were divided by combustion modes, which are the pilot-dual fuel(pilot-DF) and reactivity-controlled compression ignition(RCCI), in order to study the effects of parameters on the accuracy of the model. The results showed that the prediction accuracy of the model is related to the amount of train data which have similar trends of in-cylinder pressure with the test conditions, regardless of the total amount of train data.
이상욱(Sanguk Lee),김경곤(Gyeonggon Kim),배충석(Choongsik Bae) 한국연소학회 2020 KOSCOSYMPOSIUM논문집 Vol.2020 No.9
In order to reduce the CO₂ from vehicular emission, hydrogen is applied as a fuel. The hydrogen stratified combustion was investigate in a constant volume combustion chamber. To visualize the hydrogen flame, direct flame and schlieren images were acquired by two high-speed cameras. The injection pressure was 100bar. Owing to the in-cylinder condition, ambient pressure was varied from 5 bar to 15 bar. As the ambient pressure increased, total energy conversion was improved due to the high oxygen content in a CVCC. A high portion of luminous flame was detected when the ambient pressure was low, which indicates the rich-hydrogen combustion. Although hydrogen itself has a wide flammable range, excessively short mixture formation time may deteriorate the energy conversion efficiency.