Abstract Machine learning (ML) models can accelerate the development of efficient internal
combustion engines. This study assessed the feasibility of data-driven methods toward …

For reduction of engine‐out emissions and improvement of fuel economy, closed‐loop
control of the combustion process has been explored and documented by many …

Electronic engine controls based on real time diagnosis of combustion process can
significantly help in complying with the stricter and stricter regulations on pollutants …

A recurrent non-linear autoregressive with exogenous input (NARX) neural network is
proposed, and a suitable fully-recurrent training methodology is adapted and tuned, for …

This study aims at building an efficient and robust radial basis function (RBF) artificial neural
network (ANN), to reconstruct the in-cylinder pressure of a diesel engine starting from the …

In-cylinder pressure is a key parameter for assessing marine engines health; therefore, its
measurement or prediction is paramount for these engines' diagnosis. Thermodynamic …

Closed-loop combustion control in gasoline engines can improve efficiency, calibration
effort, and performance using different fuels. Knowledge of in-cylinder pressures is a key …

A multitude of high quality, high-resolution data is a cornerstone of the digital services
associated with Industry 4.0. However, a great fraction of industrial machinery in use today …

In this work, frequency response functions (FRFs) are used for estimation of cycle-by-cycle
cylinder pressure and indicated torque waveform, using crankshaft speed fluctuations. The …

The prediction of hull vibration response is the basis for the quantitative control of cabin
noise and underwater radiated noise, which has an important engineering value to obtain …