Evaluation of Virtual NOx Sensor Models for Off Road Heavy Duty Diesel Engines 2012-01-0358
NOx and PM are the critical emissions to meet the
legislation limits for diesel engines. Often a value for these
emissions is needed online for on-board diagnostics, engine
control, exhaust aftertreatment control, model-based controller
design or model-in-the-loop simulations. Besides the obvious method
of measuring these emissions, a sensible alternative is to estimate
them with virtual sensors.
A lot of literature can be found presenting different modeling
approaches for NOx emissions. Some are very close to the
physics and the chemical reactions taking place inside the
combustion chamber, others are only given by adapting general
functions to measurement data. Hence, generally speaking, there is
not a certain method which is seen as the solution for modeling
emissions. Finding the best model approach is not straightforward
and depends on the model application, the available measurement
channels and the available data set for calibration.
This paper evaluates three different already published virtual
sensor approaches for NOx engine raw emissions of a
heavy-duty diesel engine in off-road applications. The three
proposals consist of a black box polynomial mean value model using
available data from the electronic control unit (ECU), a black box
mean value model using mainly the measured indicated pressure
profile and a crank-angle-based gray box model also based on the
indicated pressure profile.
The final evaluation of the three models was done with
measurements of a highly dynamical test cycle for HD engines,
coming from a wheel-loader application and conducted on a dynamical
engine test bench, whereas dynamical behavior, integral error as
well as transient deviations were analyzed.