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One-point Operating Engine을 가지는 PHEV차량의 최적 제어를 위한 연구
강병동(Byeongdong Kang),박형석(Hyungseok Park),이동현(Donghyun Lee),안병훈(Byounghoon An),김동권(Dongkwon Kim),박진일(Jinil Park),김현정(Hyunjung Kim),이종화(Jonghwa Lee),유재석(Jaisuk Yoo) 한국자동차공학회 2011 한국자동차공학회 부문종합 학술대회 Vol.2011 No.5
The threat of high oil price and the harmful environmental effect from fossil fuels trigger intesive investigation on Plug-In Hybrid Electric Vehicles (PHEVs). PHEV has rechargeable batteries that can be restored to full charge by connecting a plug to an external electric power source. Generally, PHEV is driven by the power from the battery and an internal combustion engine. The optimal control strategy for the power split ratio is essential to minimize fuel consumption and to satisfy the drives demand. However, PHEV with one point operating engine has not been studied yet. In this paper, the optimal control algorithm for the power split ratio to minimize the fuel consumption of PHEV with one point operating engine.
비침습적 말초동맥질환 진단을 위한 CNN 기반 앙상블 모델
이동휴(Donghyu Lee),임주현(Joo Hyeon Im),이인찬(In Chan Lee),김수호(Sooho Kim),한진오(Jin-Oh Hahn),윤병동(Byeng D. Youn) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
In order to develop affordable and non-invasive peripheral arterial disease (PAD) screening methods, machine learning-based diagnostic techniques are receiving increasing interest. A recent study of CNN-based pulse waveform analysis techniques for PAD diagnosis demonstrated promise and potential as a diagnostic tool. Accordingly, in this study, Bayesian hyperparameter optimization and ensemble techniques are applied to enhance the performance of CNN-based PAD diagnosis models. For training and evaluation of the PAD diagnosis model, the blood pressure waveform data of virtual PAD patients were generated from a validated transmission line model. The trained diagnostic model was evaluated by various evaluation metrics of the classification performance according to the severity and location of the disease.