Model-Based Calibration Toolbox
Description
- Introduction and Key Features
- Designing and Managing Tests
- Modeling the Engine Envelope
- Data Analysis and Response Modeling
- Generating Optimal Calibrations
- Performing Simulations in Simulink
Performing Simulations in Simulink
You can export statistical models developed in Model-Based Calibration Toolbox to Simulink or use them for hardware-in-the-loop (HIL) testing.
Plant Modeling and Optimization
Use statistical models developed in the toolbox to capture real-world complex physical phenomena that are difficult to model using traditional mathematical and physical modeling. For example, you can export models for torque, fuel consumption, and emission (such as engine-out HC, CO, NOx, and CO2) to Simulink and perform powertrain-matching, fuel economy, performance, and emission simulations to improve powertrain component selections, drivability-related controls, and emission-related controls. Since the key physical components of your model have been derived from measured engine performance data, your models yield more accurate results than detailed physical models from theory that do not capture the complete physical phenomenon of the real-world system.
You can also reduce long-running or computationally intensive simulations by creating an accurate statistical surrogate model of an existing detailed high-fidelity engine model. For example, you can use the toolbox to generate accurate, fast-running models from complex Simulink models or subsystems over the design space of interest. The statistical surrogate can then replace the long-running subsystems in Simulink to speed up simulation time.
Hardware-in-the-Loop Testing
Model-Based Calibration Toolbox models exported to Simulink can be used in real-time simulations with hardware to provide fast, accurate plant model emulation to the ECU sensor and actuator harnesses. Since developing models in the toolbox takes advantage of a methodical process, you can reduce bottlenecks related to the current art of HIL plant model development, resulting in earlier validation of ECU algorithm designs.
