Background in powertrain calibration required; basic knowledge of MATLAB recommended.

*Day 1 of 2*

**Problem Definition**

**Objective:** Get an overview of the general effects of the engine actuators used in the course and review a block-diagram problem statement for the calibration problem to be solved over the two-day course.

Definition of engine type and actuator technologies

Definition of dynamometer test-setup

Definition of actuator control ranges

Qualitative review of engine actuator effects on emissions, performance, and fuel economy

Preview of optimal calibration table solutions to be achieved by the end of the course

**Design of Experiments**

**Objective:** Develop an efficient Design of Experiments (DoE) test plan for the calibration problem definition using the minimal amount of expensive dynamometer test points.

Set up test plan in MBCMODEL interface

Enter engine actuator variable ranges

Design DoE

Apply design constraints

Export DoE to CSV or MATLAB for dynamometer testing

**Test Data Import, Filtering, and Meta Variable Setup**

**Objective:** Import data into Model-Based Calibration Toolbox™ and filter it for bad data. Using the directly measured data, calculate meta variables that may not be directly measured (e.g., mechanical power, brake specific fuel consumption).

Putting measured data into simple MBC-compatible Microsoft® Excel® format

Importing data to the MBC Data Editor

Filtering bad data by test and record

Adding meta variables

**Statistical Modeling of Measured Engine Data**

**Objective:** Develop accurate statistical engine models required for calibration development. Export those models to MATLAB and Simulink so that others can reuse them in HIL and powertrain simulation models.

Associating the engine data set with the engine test plan

Generating statistical response models

Removing outlier data

Refining response models

Visually reviewing response models

Exporting response models to MATLAB and Simulink

*Day 2 of 2*

**Set Up and Run Calibration Optimization Problem in CAGE Tool**

**Objective:** Import models into the Calibration Generator tool (CAGE) in Model-Based Calibration Toolbox, set up empty lookup table structures, and enter the optimization problem definition.

Import engine models into the CAGE tool

Set up calibration lookup tables

Set up calibration optimizer objective function and constraints for operating-point optimization and operating mode optimization

Add table-gradient and sum constraints to operating-point optimization for drive-cycle-based optimization

Run optimizations for point and sum

**Fill Calibration Tables, Judge Results, and Export for ECU Implementation**

**Objective:** Fill the optimal calibration tables, judge the sensitivity of the final calibrations and their validity relative to a validation data set, and export calibration tables for ECU implementation.

Use the Fill Tables button to fill the empty calibration tables with optimal results

Use the Tradeoff tool to judge the sensitivity of the final calibration tables and determine if additional constraints are needed in the optimization process

Use the Dataset tool to import test points measured at optimal settings and compare to predicted engine emissions, performance, and fuel economy to validate the calibration tables

Export calibration tables to ATI Vision, INCA .DCM, and MATLAB formats for ECU implementation

**Student Walk-In Example Application Support**

**Objective:** Work with the instructor to solve specific calibration problems using the skills learned in the formal course.