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Model-Based Calibration Toolbox

Model-Based Calibration Toolbox workflow

Data Analysis and Response Modeling

Model-Based Calibration Toolbox uses MATLAB functions for data analysis and visualization, statistics, and optimization to fit the models and generate a graphical representation of an engine's behavior. The toolbox provides the MBC Model Fitting app to help you ensure that test points taken in the laboratory match the original experimental design. Using the app, you can fit different model types to the collected data.

An optimized engine testing plan (left) and sophisticated engine model (right), developed with the Model-Based Calibration Toolbox

An optimized engine testing plan (left) and sophisticated engine model (right).

Preprocessing Data

The toolbox provides the Design Editor for analyzing engine data and transforming it into a form that is suitable for modeling. With the Design Editor you can perform a variety of preprocessing operations, including filtering to remove unwanted data, adding test notes to document findings, transforming or scaling raw data, grouping test data, and matching test data to experimental designs.

Using the Data Editor to select a subset of tests and view the data in different formats: 2D plots, 3D plots, and a table

Using the Data Editor to select a subset of tests and view the data in different formats: a 2D plot, a 3D plot, and a table.

Selecting and Fitting Models

Model-Based Calibration Toolbox provides a library of empirical model types for modeling engine behavior such as torque, fuel consumption, and emissions. Models include polynomials, splines, radial basis functions, growth models, user-defined MATLAB files, and Simulink models.

Using the Model Browser to fit and evaluate different model types for a gasoline engine

Using the MBC Model Fitting app to fit and evaluate different model types for a gasoline engine.

Next: Generating Optimal Calibrations

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