This paper presents a comprehensive study on the utilization of machine learning and deep
learning techniques to predict the dynamic characteristics of design parameters, exemplified …

Engine performance under full working conditions, especially dynamic ones, is
indispensable in many vehicle-level research fields. To acquire the engine performance …

The process used by engine manufacturers for the development of a new engine includes
the planning and conceptual design phases, followed by the detailed design phase, in …

This study deals with an artificial neural network (ANN) modelling of a marine diesel engine
to predict the output torque, brake power, brake specific fuel consumption and exhaust gas …

Strict environmental laws increase the importance of reducing emissions. While; improving
three-way catalyst (TWC) technology can help reduce emission levels, attention should also …

The performance models are the critical step for condition monitoring and fault diagnosis of
diesel engines, and are an important bridge to describe the link between input parameters …

Deep learning has been used to predict engine phenomena that are otherwise difficult to
predict using conventional modeling approaches. Previous studies using deep learning for …

The investigation of marine diesel engines is still limited and considered new in both:
physical testing and prediction. Therefore, this study deals with an artificial neural network …

This paper presents a physics-informed neural network (PINN) approach for monitoring the
health of diesel engines. The aim is to evaluate the engine dynamics, identify unknown …

The automotive industry is facing a crucial time. The transformation from internal combustion
engines to new electrical technologies requires enormous investment, and hence the IC …