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Nowadays, engine manufacturers are trying to implement strategies that provide the best efficiency and are as clean as possible.
Deep learning can be used to model the behavior of an engine, based on the most important operational variables. This can be used for a variety of purposes,
which include performance optimization or predictive maintenance.
The data set used in this study contains quantitative information about fuel rate and angular speed of an engine, and its corresponding torque and NOx emissions.
Data from 1.200 different engine operations has been acquired. A simple cross-plotting identified the presence of a few outliers, which were removed.
That input and target variables are summarized in the following table.
scaled_fuel_rate = 2*(fuel_rate-0.6)/(314-0.6)-1; scaled_speed = 2*(speed-612.1)/(1801.8-612.1)-1; y_1_1 = tanh(-1.11096-1.61239*scaled_fuel_rate+0.430536*scaled_speed); y_1_2 = tanh(0.53813+0.546026*scaled_fuel_rate-3.48146*scaled_speed); y_1_3 = tanh(2.41882-2.12554*scaled_fuel_rate+3.45315*scaled_speed); y_1_4 = tanh(1.31628-1.76257*scaled_fuel_rate-0.881265*scaled_speed); y_1_5 = tanh(-0.134698-0.138303*scaled_fuel_rate+2.60122*scaled_speed); y_1_6 = tanh(0.110113+0.472119*scaled_fuel_rate-0.0221803*scaled_speed); scaled_torque = (-0.190618-0.174056*y_1_1+0.215817*y_1_2-0.00182521*y_1_3-0.0968754*y_1_4+0.287748*y_1_5+1.61218*y_1_6); scaled_nitrous_oxide_emission = (-0.780686-1.56753*y_1_1+1.44214*y_1_2-0.406431*y_1_3+0.453272*y_1_4+1.93066*y_1_5-1.23584*y_1_6); torque = 0.5*(scaled_torque+1.0)*(1784.3+176.7)-176.7; nitrous_oxide_emission = 0.5*(scaled_nitrous_oxide_emission+1.0)*(1774-0);
The expression can be added to whatever software tool you wanted to use. It can be used by an engineer for performance optimization or it can be embedded in a car for predictive maintenance.
In summary, deep learning allows you to accurately predict the behaviour of an engine in its whole operational range.
The outcomes are improvement of the engine's performance in a more ecological way and prevention of any possible failure before it happens.
As we already mentioned, this problem has been solved with the professional deep learning solution Neural Designer.
To find out more about Neural Designer click here.