Design Of Experiments And Calibration Models Examples With Matlab

With today's ever-increasing complexity of models, design of experiment has become an essential part of the modeling process. The Design Editor within the Model-Based Calibration Toolbox product is crucial for the efficient collection of engine data. Dyno-cell time is expensive, and the savings in time and money can be considerable when a careful experimental design takes only the most useful data. Dramatically reducing test time is growing more and more important as the number of controllable variables in more complex engines is growing. With increasing engine complexity, the test time increases exponentially.Model-Based Calibration Toolbox provides apps and design tools for optimally calibrating complex engines and powertrain subsystems. You can define optimal test plans, automatically fit statistical models, and generate calibrations and lookup tables for complex high-degree-of-freedom engines that would otherwise require exhaustive testing using traditional methods. Calibrations can be optimized at individual operating points or over drive cycles to identify the optimal balance of engine fuel economy, performance, and emissions. Using apps or MATLAB functions, you can automate the calibrationprocess for similar engine types.Models created with Model-Based Calibration Toolbox can be exported to Simulink to support control design, hardware-in-the-loop testing, and powertrain simulation activities across the powertrain design team. Calibration tables can be exported to ETAS INCA and ATI Vision. This book develops examples of design of experiments and calibration models.