Model-Based Calibration Toolbox 4.0

Introduction

Model-Based Calibration Toolbox™ provides design tools for optimally calibrating complex powertrain systems using statistical modeling and numeric optimization. You can define test plans, develop statistical models, and generate calibrations and lookup tables for complex high-degree-of-freedom engines that would require exhaustive testing using traditional methods. By using the toolbox with MATLAB® and Simulink®, you can develop a process for systematically identifying the optimal balance of engine performance, emissions, and fuel economy, and reuse statistical models for control design, hardware-in-the-loop testing, or powertrain simulation.

Key Features

• Interactive workflow tools for designing experiments, fitting statistical models to engine data, and producing optimal calibrations
• Classical, space-filling, and optimal designs, based on Design-of-Experiments methodology, for creating optimized test plans
• Techniques for developing high-fidelity nonlinear statistical models from test data
• Linear regression and radial basis function modeling techniques for creating accurate fits to data
• Built-in and user-definable libraries of empirical model forms
• Boundary modeling to keep optimization results within the engine operating envelope
• Optimization and tradeoff tools for solving calibration problems at individual operating points or over drive cycles
• Generation of lookup tables from models, optimization results, or test data
• Calibration import and export links to ETAS INCA and ATI Vision