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KEYNOTE

Best Practices for Establishing a Model-Based Design Culture

Jim Tung, MathWorks Fellow

Adopting Model-Based Design requires planning and management, both to demonstrate immediate benefits and to enable an organization to maximize the ongoing ROI. In this session, we will discuss best practices for adopting Model-Based Design across an organization. These practices, which encompass technical, process, and organizational aspects, have been gleaned from successful and not-so-successful transformations to Model-Based Design at companies from a variety of industries.

Early Verification and Validation in Model-Based Design

Amory Wakefield, The MathWorks

This presentation will introduce some best practices for repeatable and exhaustive verification in the Simulink^® environment. You will learn how early verification and validation in Model-Based Design can improve the overall quality of products. Topics will include modeling standards, model testing, and model coverage. You’ll also learn how to prove the correctness of generated code using PolySpace^® code verifiers.

Developing AUTOSAR Software Components with Model-Based Design

Dr. Joachim Schlosser, The MathWorks

The development of AUTOSAR software components requires interaction with authoring tools used to develop a vehicle's architecture and ECU topology as well as RTE generation environments. This master class demonstrates how you can incorporate the development of AUTOSAR software components based on Simulink and Real-Time Workshop Embedded Coder™ into a workflow using these tool environments.

System-Level Design of Electrohydraulic and Mechatronic Systems

Steve Miller, The MathWorks

Responding to climbing fuel prices and environmental concerns, automakers and suppliers are scouring vehicles for ways to improve efficiency without sacrificing performance. Advances in mechatronic systems have created an efficient alternative to electrohydraulic systems, and companies are investigating those alternatives and replacing hydraulic pumps and cylinders with power electronics and electric motors. Due to the complex nature of these systems, it is critical to analyze them at the system level to understand the control and safety-critical requirements of these systems. This talk will focus on how simulation can help in the analysis and design of electrohydraulic and mechatronic systems using the specific example of power steering systems.

Panel Discussion: Best Practices for Establishing a Culture of Model-Based Design Within Automotive Organizations

The transition to Model-Based Design requires careful management to enable the full realization of its benefits. Establishing a culture that embraces the process is key to achieving the associated time and cost savings. In this panel discussion, representatives from leading automotive companies will discuss their experiences in establishing Model-Based Design within their organizations.

Panelists will discuss their organization’s progress in adopting a culture of Model-Based Design, how they measure the impact of Model-Based Design on the organization, and key lessons they have learned — both positive and negative — in transitioning to Model-Based Design.

Participants include:

• Christian Dziobek, Daimler AG
• Larry Michaels, General Motors
• Andreas Greff, IAV GmbH
• Ross James, John Deere
• Sascha Kovacevic, AUDI AG

Introduction to Practical Uses of the Plant Model in Model-Based Development

Takayuki Kubo, Aisin AW Co., Ltd.

This session introduces Aisin's model-based development applications. The first section will cover activities for HILS development and controller design. The second section explains the practical development of the plant model – an automatic transmission model – with SimDriveline™. The same example will be used for applying Simulink Parameter Estimation™ to analyze this model.

Takayuki Kubo is a senior specialist in the Advanced Engineering group of Aisin AW Co., Ltd.

Quality Improvement by Continuous Usage of PolySpace Products with Model-Based Design in the Area of Safety Systems

Dr. Almut Hochstädter and Jochen Retter, Conti Temic Microelectronic GmbH

Continental Passive Safety now uses a fast and secure front-loaded development process for safety-critical software. A main key to this development method is the systematic usage of PolySpace™ products for all existing and upcoming projects. PolySpace is also the key tool for the validation of third-party software being integrated into an airbag electronic control unit (ECU), for AUTOSAR-compliant and other components. For upcoming projects, a part of the airbag software will be modeled in Simulink^® and Stateflow^®. PolySpace Model Link™ SL (for Simulink) will be the key tool for validation of these models and the resulting generated code. In this session, Continental will reveal a seamless approach for front-loaded development using MATLAB^®, Simulink, Stateflow, and PolySpace products for production of new airbag ECU software.

Functional Variants Handling in Simulink Models

Wojciech Przystas, Daimler AG R&D

Today’s cars are characterized by a multitude of functional variants. There are numerous sources of variability – starting with the adaptation to diverse markets, ending with offering different technical features, and thus, different ECUs. Inevitably, this is reflected in model-based function development using Simulink.

Simulink models describe, in particular, the functional algorithm of real-time systems. In practice, the aspects of modeling and configuration of functional variants overlay the “basic” algorithm. This happens in the context of the creation of reusable and configurable functional modules. These two aspects, the modeling and configuration, lack the necessary means of variability description, and thus cannot be unambiguously described through a reliable process. As a consequence, a reliable classification by the modeler, or the code generator, is not always possible.

There is a demand for concepts that systematically describe variability handling in Simulink, for example:

• Which information concerning basic blocks must be available to describe functional variants?
• Where and how can this information be stored?

This session describes an approach for handling functional variants in Simulink models. It is based on the separation of general and block-specific variability information, thus allowing:

• A uniform description (and therefore a uniform configuration) of functional variants
• Variant-specific presentation/visualization of these variants in Simulink models (showing the difference between “regular” and “variant specific” blocks), as well as the recognition of dependencies between the variants

This approach was developed within a research project and is currently being applied in a series project in the development of Mercedes-Benz cars. Its scope comprises the implementation of a variant blockset, a variant-specific application programming interface (API) based on MATLAB functions, and a configuration tool.

Wojciech Przystas studied computing science and computational linguistics at the University of Stuttgart. Since 2007 he has been with Daimler AG R&D, working as a Ph.D. student in the area of variant configuration of model-based embedded software.

Using Model-Based Calibration Toolbox Multimodels for Cycle-Optimized Diesel Calibration

Joshua Styron, Ford Motor Company

Modern diesel engines have many degrees of freedom that must be simultaneously adjusted to optimize efficiency, emissions, and performance. Due to the complexity of the interactions among the input parameters, it is not possible to decompose the calibration process into a set of smaller, simpler models. Further complicating the calibration process, there is a strong desire to make tradeoffs among different speeds and loads to meet various cycle-based emissions and fuel economy targets. Simply building models with two more inputs to represent the entire engine map may result in a loss of fidelity as input parameters may interact differently across the engine operating range. Model-Based Calibration Toolbox™ can now generate multimodels, which essentially select the best local model at each speed and load operating point. These global models retain all of the fidelity of the local models, while allowing real-time tradeoffs at discrete speed and load points in cycle optimizations.

In CAGE, toolbox multimodels were used to generate steady-state calibration set points for an entire engine map that minimize fuel consumption while simultaneously meeting cycle emissions and global NVH targets. In addition, many constraints were utilized to ensure the calibration was realistic. Map gradient constraints helped to ensure the resulting optimized maps would be smooth enough. Boundary constraints were used to limit the optimization to attainable points, while models of critical engine limits like peak cylinder pressure and turbine inlet temperature ensure the calibration remains within the critical engine limits.

Joshua Styron received his Ph.D. from the University of Illinois at Urbana-Champaign, where he developed a novel laser-diagnostic technique to quantify vapor fuel distributions of multicomponent fuels inside an optically accessible spark ignition engine. This technique was used to minimize hydrocarbon emissions during cold-start conditions due to poor mixture preparation. Upon graduation, Joshua was hired by Ford Motor Company for a brief rotation through Powertrain Systems Engineering.  He then moved on to Ford Research, where he invented and developed variable compression ratio engine mechanisms as well as sensing concepts, control strategies, and calibrations. Joshua then moved on to diesel engine development, where he worked to develop a new combustion system starting from CFD and proceeding through single-cylinder engine testing and multicylinder engine validation. He is currently leading mapping efforts for Ford's North American diesel engine programs to optimize steady-state calibrations.