About Feature Calibrations and Strategies
A feature calibration is the process of calibrating lookup tables by comparing an electronic control unit (ECU) strategy to a statistical model. A Simulink® model represents the ECU strategy.
The Model-Based Calibration Toolbox™ calibrates an estimator, or feature, for a control subsystem in an ECU. Features are usually algebraic collections of one or more lookup tables. You use the features to estimate signals in the engine that are unmeasurable, or expensive to measure, and are important for control. The toolbox can calibrate the ECU subsystem by directly comparing it with a plant model of the same feature.
There are advantages to feature calibration versus calibrating using experimental data. Feature calibrations:
Smooth noisy data, that is data with measurement error.
Use statistical models that can make predictions in operating conditions where you have data. You can accurately calibrate and reduce effort gathering experimental data.
A strategy is an algebraic collection of lookup tables, and forms the structure of the feature. Model-Based Calibration Toolbox uses the strategy to estimate signals in the engine that cannot be measured.
For example, a simple strategy to calibrate a feature for Model-Based Calibration Toolbox has two lookup tables:
Table ranging over the variables speed and load
Table to account for the behavior of the model as the air-to-fuel ratio (AFR) varies
To evaluate the feature side by side with the model, you need to have a strategy that takes some or all of the same variables as the model. The strategy is expressed using Simulink diagrams. You can either import a strategy or you can construct a strategy.
