Neural Network Modelling of the Emissions and Performance of a Heavy-Duty Diesel Engine

‘ENPROD’ MODEL – estimating the energy impact of the use of heavy duty construction equipment by using productivity rate

“…Artificial neurons are the elements that constitute the input, output, and hidden layers of the ANN models. Thompson et al [10] used ANN modeling to predict the relationship between the output torque and fuel use, as well as exhaust emissions from heavy-duty diesel engines with limited use of dynamometer testing. In concern with fuel properties.…”

Applying artificial neural networks (ANN) to the estimation of thermal contact conductance in the exhaust valve of internal combustion engine

“…Thompson et al trained a network using experimental results that combustion time is input and torque and exhaust gases are outputs of network. These researchers used the network to determine optimal combustion time for operating engine [11]. Heister and Froehlich suggested the use of neural network modeling in calculation pressure inside cylinder at different engine speeds and times [12].…”

The Applications of Artificial Neural Networks to Engines

“…Hence, in engine development neural networks are used for control problems such as fuel injection, output performance or speed (Hafner et al, 2000;Ouladsine et al, 2004). In addition, advanced control strategies as variable turbine geometry (VGT), exhaust gas recirculation (EGR) or variable valve timing (VVT) have been in the focus of ANN modelling (Thompson et al, 2000). Nevertheless, the application is also used for virtual sensing such as emissions (Hanzevack, 1997;Atkinson, 2002) or as described in Prokhorov (Prokhorov, 2005) for misfire detection, torque monitoring or tyre pressure change detection.…”