CAGE User's Guide | ![]() ![]() |
Calibrating the Feature
A feature is a strategy (which is a collection of tables) and a model. Currently the torque table, T
, is filled with values of the torque model, tq
. You must now calibrate the normalizers and tables for F_A
and F_SPK
.
You could calibrate the normalizers and then the tables for F_A and F_SPK in turn. However, CAGE enables you to calibrate the entire feature in one procedure.
To view the Feature view following, click the New_Feature
node.
To calibrate all the tables and their normalizers:
All three tables and normalizers are filled.
As the model and the feature are four-dimensional objects, it is difficult to fully view a comparison between the feature and the model. A meaningful comparison is shown in the lower half of the following figure (select the F_A
node in the branch display). The equation model = strategy is rearranged so that the table is compared to the model and the remainder of the strategy.
This display shows that the range of the normalizer for F_A
is 11 to 17, the range of AFR. The lower pane shows a comparison between the red strategy and a slice through the model, over the range of AFR.
You can use CAGE to improve on these results. CAGE can run an optimization routine over the feature to minimize the total square error between the model and the feature.
New_Feature
node
This reduces the error between the feature and the model.
To view this reduction in error, select the F_A
node in the branch display.
Notice that the mean square error between the model and the feature over this range of values is 0.001348, which is less than the 0.002097 previously obtained.
This completes the calibration of the torque feature.
For more information about calibrating features, see Calibrating the Feature Node.
You now need to export the calibration for the ECU.
![]() | Calibrating the Tables | Exporting Calibrations | ![]() |