Running the Optimization :: Diesel Engine Calibration Case Study (Model-Based Calibration Toolbox™)

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Contents

Index

• Getting Started

• Introduction

Designs and Modeling in the Model Browser

Calibration Generation in CAGE

Examples of Engine Modeling and Calibration

Tutorials for Design and Modeling

Tutorials for Calibration Generation

Training Material

Operating System Requirements

Required MathWorks Products

Optional MathWorks Products

Waitbar May Have Transparent Background

• Gasoline Engine Calibration Case Study

Case Study Introduction

Why Use Design of Experiment and Engine Modeling?

Problem Definition

Introduction to Two-Stage Modeling

Overview of Design Process

Creating a Test Plan

Specifying the Model Inputs

Creating Designs

Import and View Data

Completing Model Setup

Specifying the Local Model Type

Selecting Data and Responses to Model

Inspect the Global Models

Create Multiple Models to Compare

Create a Two-Stage Model

Adding New Response Models

Problem Definition

Benefits of Automated Calibration

Altering Variable Ranges

Setting Up Tables

Setting Up the Optimization Initial Values and Objective

Creating Table Gradient Constraints

Running the Sum Optimization

What Is an Estimator?

View the Feature

Edit and Import Boundary Model

Use the Feature Fill Wizard

Inspect Results

CAGE Import Tool

• Diesel Engine Calibration Case Study

• Diesel Case Study Overview

Problem Definition

• Design of Experiment

Introducing Design of Experiment

Constraining the Design

Creating Candidate Designs

Data Collection

Overview of Modeling Process

Building Models

Building and Evaluating Alternative Models

Creating Boundary Models

• Optimized Calibration

Problem Definition

Benefits of Automated Calibration

Importing Models of Engine Responses into CAGE

Defining Additional Variables and Models

Setting Up Calibration Tables to Fill

Setting Up the Point Optimization

Setting Up Constraints

Defining Variable Values

Running the Optimization

• Setting Up the Sum Optimization

Setting Up Initial Values and Sum Objective

Creating the Brake Specific NOx Constraint

Setting Weights for the Sum Objective and Constraint

Set Parameters and Run Optimization

Filling Tables with Optimization Results

• Point-by-Point Diesel Engine Calibration Case Study

• Example Composite Models and Modal Optimizations

Gasoline Example with Four Cylinder and Eight Cylinder Modes

Diesel Example with Low and High EGR Modes

Composite Model Example with Separate Tables for Each Mode

• Design and Modeling Scripts

Processes You Can Automate

Scripting Demos

Projects and Test Plans for Model Scripting

Response Model Scripting

Boundary Model Scripting

• Tutorial: Model Quickstart

Creating the Test Plan

Setting Up the Local Model

Setting Up the Global Model

Specifying the Response Model

Verifying the Local Model

Verifying the Global Model

Selecting the Two-Stage Model

Comparing the Local Model and the Two-Stage Model

Maximum Likelihood Estimation

Methods For Creating More Models

Creating New Local Models

Adding New Response Features

Comparing Models

Creating New Global Models

Creating Multiple Models Using Build Models

• Tutorial: Design of Experiment

Why Use Design of Experiment?

Structure of This Design Editor Tutorial

Setting Up a Model

Starting the Design Editor

Creating a New Design

Introducing Optimal Designs

Start Point Tab

Candidate Set Tab

Introducing the Prediction Error Variance Viewer

Improving the Design

Adding a Classical Design

Classical Design Browser

Setting Up and Viewing a Classical Design

• Tutorial: Data Editor

Entering the Data Editor

Loading a Data File

Using Notes to Sort Data for Plotting

Removing Outliers and Problem Tests

Reordering and Editing Data

Adding New Variables

Applying a Filter

Sequence of Variables

Deleting and Editing Variables and Filters

Introducing Matching Data to Designs

Tolerances and Cluster Information

Understanding Clusters

• Tutorial: Feature Calibration

Setting Up Variables

Setting Up Models

Setting Up a New Feature

Setting Up the Strategy

Setting Up the Tables

Process For Feature Calibration

Calibrating the Normalizers

Calibrating the Tables

Calibrating the Feature

• Tutorial: Tradeoff Calibration

Creating a Tradeoff

Adding Tables to a Tradeoff Calibration

Displaying the Models

Process Overview

Checking the Normalizers

Setting Values for Other Variables

Filling Key Operating Points

Filling the Table by Extrapolation

Exporting Calibrations

• Tutorial: Data Sets

Tutorial Overview

Opening an Existing Calibration

Importing Experimental Data into a Data Set

Adding an Item to a Data Set

Viewing the Data Set as a Table

Viewing the Data Set as a Plot

Displaying the Error

Coloring the Display

• Tutorial: Filling Tables from Data

Tutorial Overview

Adding Variables

Adding a New Table

Importing Experimental Data

• Tutorial: Optimization and Automated Tradeoff

Tutorial Problem Definitions

The Optimization View

Import Models to Optimize

Process Overview

Using the Create Optimization from Model Wizard

Setting Constraints and Operating Points

Running the Optimization

Using Optimization Results to Fill Tables

Using a Custom Fill Routine to Fill Tables

Setting Up and Running the Multiobjective Optimization

Optimization Output View

Selecting Best Solutions

What Is a Sum Optimization?

Example Overview

Using the Worked Example Optimization

Process Overview

Step 1: Verify the Algorithm

Step 2: Create a CAGE Optimization Function

Step 3: Define the Optimization Options

Step 4: Add the Algorithm to the Optimization Function

Step 5: Register Your Optimization Function with CAGE

Step 6: Verify Your New Optimization

• User's Guide

• Release Notes

Running the Optimization

Now you can run the optimization. You have set up objectives, constraints and a set of operating points.

Click Run Optimization in the toolbar.
When the optimization is complete, the view switches to the new child node, bsfc_Optimization_Output, in the Optimization tree under the bsfc_Optimization node. View the results.
Look through the solutions at different operating points by clicking cells in the output table. Compare with the gasoline example, where regions that do not meet the constraint are yellow in the graphs — in this case the torque equality constraint causes all the graphs to be yellow, because this constraint produces a feasible contour in the free variable space, and any deviation off this contour is infeasible.
Split the view to display the constraint graphs, and scroll through them to see each constraint in relation to the solutions.

Defining Variable Values

Defining Variable Values

Setting Up the Sum Optimization

Setting Up the Sum Optimization

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