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The MATLAB software include eficient tools for optimization and calibration models. The Model-Based Calibration Toolbox product contains tools for design of experiment, statistical modeling, and calibration of complex systems. The toolbox has two main apps: Model Browser for design of experiment and statistical modeling and CAGE Browser for analytical calibration. CAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables. CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE you fill and optimize lookup tables in existing ECU software using models from the Model Browser part of the Model-Based Calibration Toolbox product. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation. CAGE can optimize calibrations with reference to models, including single- and multi-objective optimizations, sum optimizations, user-defined optimizations, and automated tradeoff. You can compare your calibrations to experimental data for validation. For example, after completing a calibration, you can import experimental data from a spreadsheet. You can use CAGE to compare your calibration to the data.. This book develops the following topics: - "Model-Based Calibration Toolbox" - "What Is CAGE?" - "Set Up Calibrations" - "Import Models and Calibration Items" - "Setting Up Models" - "Setting Up Tables" - "Creating Tables from a Model" - "Calibration Manager" - "Importing and Exporting Calibrations" - "Feature Calibrations" - "Import a Strategy from Simulink" - "Tradeoff Calibration" - "Point-by-Point Model Tradeoffs"
The Model-Based Calibration Toolbox product contains tools for design of experiment, statistical modeling, and calibration of complex systems..The toolbox has two main apps: -Model Browser for design of experiment and statistical modeling-CAGE Browser for analytical calibrationThe Model Browser is a flexible powerful, intuitive graphical interface for building andevaluating experimental designs and statistical models: -Design of experiment tools can drastically reduce expensive data collection time.-You can create and evaluate optimal, space filling and classical designs, and constraints can be designed or imported.-Hierarchical statistical models can capture the nature of variability inherent in engine data, accounting for variation both within and between tests.-The Model Browser has powerful, flexibl tools for building, comparing, andevaluating statistical models and experimental designs.-There is an extensive library of prebuilt model types and the capability to build user-define models.-You can export models to CAGE or to MATLAB, or Simulink software. -There is an extensive library of prebuilt model types and the capability to build user-define models.-You can export models to CAGE or to MATLAB(R), or Simulink software.
MATLAB can create Experimental Design Models with Model-Based Calibration Toolbox. This models can be exported to Simulink(R) to support control design, hardware-in-the-loop testing, and powertrain simulation activities across the powertrain design team. The toolbox has two main user interfaces for model-based calibration workflows: - Model Browser for design of experiment and statistical modeling - CAGE Browser for analytical calibration The Model Browser part of the toolbox is a powerful tool for experimental design and statistical modeling. The models you build with the Model Browser can be imported into the CAGE Browser part of the toolbox to produce optimized calibration tables. The command-line interface to the Model-Based Calibration Toolbox product enables the design of experiments and modeling tolos available in the toolbox to be accessible from the test bed. You can use these commands to assemble your specific engine calibration processes into an easy to use script or graphical interface. Calibration technicians and engineers can use the custom interface without the need for extensive training. The Model Browser is a flexible, powerful, intuitive graphical interface for building and evaluating experimental designs and statistical models. This tools enables: - Design of experiment tools can drastically reduce expensive data collection time. - You can create and evaluate optimal, space-filling, and classical designs, and constraints can be designed or imported. - Hierarchical statistical models can capture the nature of variability inherent in engine data, accounting for variation both within and between tests. - The Model Browser has powerful, flexible tools for building, comparing, and evaluating statistical models and experimental designs. - There is an extensive library of prebuilt model types and the capability to build userdefined models. - You can export models to CAGE or to MATLAB or Simulink software. - Faster calibration - Improved calibration quality - Improved system understanding - Reduced development time CAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables. CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE, you fill and optimize lookup tables in existing ECU software using Model Browser models. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation. This book develops the following topics: - "Model-Based Calibration Toolbox" - "Design of Experiments" - "Design and Modeling Scripts" - "Model-Based Calibration Toolbox Command-Line Interface" - "Automate Design and Modeling With Scripts" - "Statistical Modeling and Optimization" - "Two-Stage Modeling" - "Create Multiple Models to Compare" - "Create a Constrained Space-Filling Design" - "Create Optimal and Classical Designs" - "Use the Design Evaluation Tool" - "Data Manipulation for Modeling" - "Match Data to Experimental Designs" - "Feature Calibration"
Explore the inner workings of environmental processes using a mathematical approach. Environmental Systems Analysis with MATLAB® combines environmental science concepts and system theory with numerical techniques to provide a better understanding of how our environment works. The book focuses on building mathematical models of environmental systems, and using these models to analyze their behaviors. Designed with the environmental professional in mind, it offers a practical introduction to developing the skills required for managing environmental modeling and data handling. The book follows a logical sequence from the basic steps of model building and data analysis to implementing these concepts into working computer codes, and then on to assessing their results. It describes data processing (rarely considered in environmental analysis); outlines the tools needed to successfully analyze data and develop models, and moves on to real-world problems. The author illustrates in the first four chapters the methodological aspects of environmental systems analysis, and in subsequent chapters applies them to specific environmental concerns. The accompanying software bundle is freely downloadable from the book web site. It follows the chapters sequence and provides a hands-on experience, allowing the reader to reproduce the figures in the text and experiment by varying the problem setting. A basic MATLAB literacy is required to get the most out of the software. Ideal for coursework and self-study, this offering: Deals with the basic concepts of environmental modeling and identification, both from the mechanistic and the data-driven viewpoint Provides a unifying methodological approach to deal with specific aspects of environmental modeling: population dynamics, flow systems, and environmental microbiology Assesses the similarities and the differences of microbial processes in natural and man-made environments Analyzes several aquatic ecosystems’ case studies Presents an application of an extended Streeter & Phelps (S&P) model Describes an ecological method to estimate the bioavailable nutrients in natural waters Considers a lagoon ecosystem from several viewpoints, including modeling and management, and more
Model-Based Calibration Toolbox contains tools for design of experiment, statistical modeling, and calibration of complex systems. The toolbox has two main user interfaces:* Model Browser for design of experiment and statistical modeling* CAGE Browser for analytical calibrationCAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookuptables.CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE you fill and optimize lookup tables in existing ECU software using models from the Model Browser part of the Model-Based Calibration Toolbox product. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation.
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, missions, and fuel economy, and reuse statistical models for control design, hardware-in-the-loop testing, or powertrain simulation.
The Model-Based Calibration Toolbox product contains tools for design of experiment, statistical modeling, and calibration of complex systems..The toolbox has two main apps: -Model Browser for design of experiment and statistical modeling-CAGE Browser for analytical calibrationThe Model Browser is a flexible powerful, intuitive graphical interface for building and evaluating experimental designs and statistical models.CAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables. CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE you fill and optimize lookup tables in existing ECU software using models from the Model Browser part of the Model-Based Calibration Toolbox product. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation.A feature calibration compares a model of an estimated signal with a lookup table (or algebraic collection of tables) that estimates the same signal in the ECU. CAGE finds the optimum calibration for the lookup table(s). For example, a typical engine subsystem controls the spark angle to produce the peak torque; that is, the Maximum Brake Torque (MBT) spark. Using the Model Browser, you can build a statistically sound model of MBT spark, over a range of engine speeds and relative air charges, or loads. Use the feature calibration to fill a lookup table by comparing the table to the model.A tradeoff calibration fills lookup tables by comparing models of different engine characteristics at key operating points. For example, there are several models of important engine characteristics, such as torque and nitrous oxides (NOX) emissions. Both models depend on the spark angle. At a particular operating point, a slight reduction of torque can result in a dramatic reduction of NOX emissions. Thus, the calibrator uses the value of the spark angle that gives this reduction in NOX emissions instead of the spark angle that generates maximum torque.CAGE can optimize calibrations with reference to models, including single- and multiobjective optimizations, sum optimizations, user-defined optimizations, and automated tradeoff.
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.
Model-Based Calibration Toolbox contains tools for design of experiment, statistical modeling, and calibration of complex systems. The toolbox has two main user interfaces:* Model Browser for design of experiment and statistical modeling* CAGE Browser for analytical calibrationCAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables.CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE you fill and optimize lookup tables in existing ECU software using models from the Model Browser part of the Model-Based Calibration Toolbox product. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation. CAGE can optimize calibrations with reference to models, including single- and multi-objective optimizations, sum optimizations, user-defined optimizations, and automated tradeoff.
Model-Based Calibration Toolbox contains tools for design of experiment, statistical modeling, and calibration of complex systems. The toolbox has two main user interfaces:* Model Browser for design of experiment and statistical modeling* CAGE Browser for analytical calibrationCAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables.CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE you fill and optimize lookup tables in existing ECU software using models from the Model Browser part of the Model-Based Calibration Toolbox product. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation. CAGE can optimize calibrations with reference to models, including single- and multi-objective optimizations, sum optimizations, user-defined optimizations, and automated tradeoff.