Pragmatic Strategies for Adopting Model-Based Design

Eric Dillaber, MathWorks
When transitioning to Model-Based Design, it is essential to consider an overall plan spanning people, development processes, and tools. Choosing the right first steps is key to a successful transition. This presentation provides a set of practical strategies for determining the first steps when deploying Model-Based Design and code generation in production development processes.

Eric Dillaber is a principal technical consultant for MathWorks specializing in helping organizations apply Model-Based Design to develop and verify embedded software in the automotive and aerospace industries. Prior to joining MathWorks in 2003, Eric worked for TRW as a lead developer of yaw stability control algorithms and for Applied Dynamics International as an application engineer for RPC, HIL, and code generation tools. His experience includes extensive work in control system design, embedded software and systems, and code generation tools. Eric holds a B.S. in physics and a B.S. in electrical engineering from Michigan State University and a M.S.E. in electrical engineering from University of Michigan.

Vehicle System Control Software Implementation and Validation for a Hybrid Powertrain

Yanan Zhao, Ford Motor Company
Through the use of hybrid technology, Ford Motor Company continues to realize enhanced vehicle fuel economy while meeting customer performance and drivability targets. As is characteristic of all Ford hybrid electric vehicles (HEVs), the basis for resolving these competing requirements resides with its Vehicle System Control (VSC) strategy. This strategy implements complex high-level executive controls to coordinate and optimize the desired operational state of the major HEV powertrain subsystems.

This session introduces the VSC software implementation and validation for a Dual Drive hybrid powertrain. The presentation provides an overview of the VSC software implementation architecture, and then details the steps involved in the validation process for the VSC software developed for the hybrid powertrain, with explanations of the validation tools and environment used.

Yanan Zhao is a controls engineer at Ford Motor Company. Prior to joining Ford in 2006, she worked as a research associate with Florida State University and as a control system engineer with GE Transportation Systems. Her research interest includes control system development, implementation, and validation for hybrid electric vehicles. She received her Ph.D. in controls and dynamic systems from Florida State University in 2001.

Large-Scale Modeling for Embedded Applications

Kerry Grand, MathWorks
Development teams for embedded applications have increased in size, and the models they develop have grown in complexity. To increase the efficiency of large-scale modeling throughout the development life cycle, a thorough understanding of the steps and techniques involved in successfully applying Model-Based Design is required. The approach includes a logical architecture to divide the model into components, the clear definition of the interfaces prior to component design, maintenance of those interfaces, production code generation, and the development infrastructure. This presentation recommends best practices for creating an infrastructure and deploying large-scale models for embedded applications using Model-Based Design.

Kerry Grand is a senior consultant for MathWorks responsible for providing large-scale modeling solutions with a focus on embedded applications. He has a diverse automotive and power conversion background with focus in embedded motor control for electric and hybrid vehicle applications as well as embedded control for three-phase active power generation. Kerry has both embedded and digital signal processor experience using Freescale, Infineon, Texas Instruments, and ARM.

Developing High-Integrity Automotive Controls to Meet ISO 26262 Using Model-Based Design

Tom Erkkinen, MathWorks
ISO 26262 is an emerging automotive safety standard currently in international draft form. It is based on the well-known IEC 61508 industrial automation standard but is being adapted for automotive systems. This presentation describes how MathWorks code generation and verification products support ISO 26262, including tool qualification. It will benefit ECU systems and software engineers developing safety-related systems, as well as anyone applying Model-Based Design who is interested in improving verification and validation tasks within their workflows.

Tom Erkkinen is the embedded application manager at MathWorks. He is leading a corporate initiative to foster industry adoption of embedded code generation technologies. Before joining MathWorks, Tom worked at Lockheed-Martin developing a variety of control algorithms and real-time software, including space shuttle flight software at NASA JSC. He has spent over a decade helping companies deploy Model-Based Design with embedded code generation and is currently focusing on industry standards and certification support. Tom holds a B.S. degree in aerospace engineering from Boston University and a M.S. degree in mechanical engineering from Santa Clara University.

Effective Verification Strategies for Distributed Body Control Applications Based on Plant Modeling and Test Case Reuse

Jason Bauman and Jinming Yang, Lear Corporation
Many of today’s body control applications are implemented across multiple ECUs developed by different suppliers. The challenge is to identify design and implementation errors prior to vehicle-level integration testing, at which time the cost of fixing errors would be high for each supplier involved. Any errors that are not discovered during integration testing will affect product quality and delivery time. Lear has established a methodology for developing body control applications based on the concept of the executable specification. In this presentation, we will provide an overview of this model-based methodology, which has been successfully applied to production projects. In addition, we will discuss unique aspects of our plant modeling and test case development strategies and their value. For example, to enable verification of distributed body control applications, we needed to incorporate behavior of other ECUs on the vehicle network, fault conditions, and commands from an external diagnostic device into the plant models. For verification, we will discuss the use of Stateflow for test case development and test case reuse for both requirements verification and ECU in-the-loop testing.

Jason Bauman is a supervisor for the Electronics Systems Division for Lear Corporation. His main areas of focus at Lear are requirements modeling, production code generation and integration, and system verification and validation for automotive body control applications. Before joining Lear in 2003, he designed and developed audio and telematics Systems for DaimlerChrysler. He has a B.S. and M.E. from University of Detroit Mercy and an MBA from Oakland University.

Jinming Yang is a principal engineer for the Electronics Systems Division at Lear Corporation. His areas of focus and research interests are development of automotive body control ECUs using Model-Based Design, including requirements modeling, automatic code generation, software integration, and system validation. Before joining Lear in 2005, he worked as a hardware engineer involved in design and development of ECUs for electronic stability control systems at Valeo Inc. He earned a doctorate in Electrical Engineering from the University of Windsor, where he specialized in neural networks and artificial intelligent systems, and earned his master’s and bachelor's degrees in Automatic Control and Instrumentation from Tsinghua University, China.

Combustion Controller Development and Application Using Model-Based Design

Klaus Rothbart, AVL List GmbH
Engine calibration involves controlling an engine to its optimum combustion position, which has traditionally been a slow process of trial and error with an engine running on the test bed. To address this challenge, a new combustion controller that drastically reduces test bed time for engine calibration teams has been developed. The presentation gives insight into the development project and the application with the resulting advantages by using Model-Based Design.

Klaus Rothbart started to work for AVL List GmbH in the area of engine test beds in 2005 and is currently working as product manager for control and simulation solutions for engine and powertrain test systems. He received a Ph.D. in electrical engineering from Graz University of Technology, Austria, in 2005.

Generating Optimal Engine Calibrations Using Model-Based Calibration Toolbox

Pete Maloney, MathWorks
Emissions, fuel economy, and performance are often competing objectives, yet they each need to be satisfied for the engine to meet regulatory and customer requirements. The increasing number of sensors, actuators, and control parameters is having a dramatic effect on calibration time. Relying solely on experience has proved to be no longer sufficient. This presentation outlines how design-of-experiment, statistical, and optimization methods can be applied to powertrain calibration with the objective of achieving optimized calibration values and establishing a consistent calibration process.

Pete Maloney is a principal consulting engineer for MathWorks. His main areas of focus are powertrain calibration tool development and application, large-scale control modeling, and physical system modeling for automotive customers. Before joining MathWorks in 2000, he designed and developed electronic engine control algorithms for Ford Motor Company and Delphi Automotive Systems over a 10-year period, resulting in 15 related patents. Pete has a B.S.M.E. from Texas Tech University and an S.M.M.E. from the Massachusetts Institute of Technology.

Moving from Rapid Prototyping to Production

Ren Sang Nah, MathWorks
Automotive engineers are often introduced to Model-Based Design through the use of rapid controller prototyping. Later, as an organization matures in its use of modeling and code generation technologies, they seek ways to do more and better leverage their investment in Model-Based Design. Generating code for deployment on production ECUs is a natural next step. This presentation provides some insight into how to make this transition. Topics include model checking, floating-point to fixed-point conversion, algorithm export and scheduling techniques, target optimized code, and code verification.

Ren Sang Nah is a senior pilot engineer at MathWorks. Focusing in modeling and code generation using the Simulink tool chain, his primary role is to help organizations in the automotive and aerospace industries adopt Model-Based Design via pilot program engagements. Ren holds a B.S. and a M.S. in aerospace engineering from Texas A&M University, specializing in guidance, controls, and astrodynamics.

Real-Time Simulation of Physical Systems Using Simscape

Wit Nursilo, MathWorks
Real-time simulation of multidomain physical system models requires finding a combination of model complexity, solver choice, solver settings, and real-time target that permits execution in real time. This presentation outlines the steps in moving from desktop to real-time simulation, and illustrates this process using models built using Simscape and other MathWorks physical modeling products.

Wit Nursilo is a senior application engineer based in the MathWorks Novi, Michigan, office. He supports physical modeling application for customers in the automotive and other industries. Including Delphi Corporation and MathWorks, Wit has over 10 years of industry experience in hydraulics/pneumatics component and system modeling. Wit has bachelor’s and master’s degrees in mechanical engineering from Tokai University, Japan, and received his Ph.D. in mechanical engineering from The University of Texas at Arlington in the area of hydraulics transmission line dynamics.