디젤 엔진 연료 분사량 예측을 위한 HCS기반 신경망 근사모델링

In this paper, we proposed the use of hermit cubic spline and back-propagation neural networks to predict rates of injection in diesel engine fuel injection system. The rate of injection in the diesel engine is described in terms of energizing time and rail pressure, and its time integration corresponds to the total fuel quantity. All results verified the possibility of neural network based rates of injection prediction and hermite cubic spline interpolation method as well.