Yue-Yun Wang, General Motors Company
Engine downsizing using turbochargers is a key strategy for lowering emissions and increasing fuel economy. However, engineers face great challenges in designing these control systems due to their nonlinearities, multivariable nature, system coupling, and calibration complexity. This presentation describes a model-based solution to this complicated control problem using advanced concepts such as inverse model control and quantitative feedback design with a calibration toolset built on System Identification Toolbox and Control System Toolbox™. Using this approach for designing a robust high-performance control system represents a paradigm shift from test cell calibration to a virtual desktop environment.
Yue-Yun is a staff researcher leading advanced diesel controls development at the Propulsion Systems Research Lab in General Motors’ R&D group. Before joining GM in 2005, he worked for 10 years at Cummins Engine Company as a technical advisor in charge of control and diagnostic projects for next-generation powertrain. He also spent eight years in research and teaching at several academic institutions. Yue-Yun has over 50 U.S. patents and many international patents for product innovations in automotive applications. He is an associate editor of IEEE Transactions on Vehicular Technology, a member of SAE, and a senior member of IEEE.
Russell Watts, Robert Bosch LLC
The current production version of the Bosch OCS would not exist if it had not been for Model-Based Design with MATLAB and Simulink products. This presentation is an account of how this approach contributed to the successful evolution of the Bosch OCS from concept to production. In particular, Model-Based Design was instrumental in providing a solution that was significantly more efficient than conventional heavyweight, software development methods while also enhancing quality.
Russell has over 30 years of experience in embedded system design and sensor system development. He has been working in automotive safety electronics for the last 16 years at Robert Bosch, with a primary emphasis on occupant sensing. He has experienced firsthand the power of Model-Based Design to manage complexity through automation of the development process.
Lev Vitkin, Delphi Corporation
Generating production embedded software requires a well-defined environment for Model-Based Design. This environment ensures the model complies with industry and company standards. It enforces standardized model architectures, predefines interfaces, and allocates all artifacts in accordance with project partitioning and software architecture. The environment also insulates model developers from software specifics that are needed for creation of production code. This presentation identifies the components of the Simulink based Model-Based Design environment that are proven to be effective in practice. Model-Based Design streamlines development and enables automation. This facilities the execution of a lean process, increases the robustness of the processes, and leads to high-quality final software.
Lev has over 20 years of experience in embedded software development, from assembly language to C code to automatic code generation. He has spent the last 10 years developing multiple production control applications using MATLAB and Simulink. Lev’s primary focus is on development of model-based environment and processes for production code generation and modeling using MATLAB, Simulink, and Stateflow. He is the author of a number of SAE papers on modeling and code generation topics. Lev has a M.S. in electrical engineering from St. Petersburg State Polytechnic University and Ph.D. in computer science from St. Petersburg State Electrotechnical University.
Alan Brown and Doris Kotori, HELLA Electronics Corp.
Decreasing time to market for advanced technologies requires alternative methodologies for efficient vehicle testing, calibration, and research. This session demonstrates the complete modeling of a vehicle with an electrical system for integrating fuel-saving technologies, including stop/start, coasting, and regenerative braking using MATLAB, Simulink, Simscape™, and Stateflow. A modified vehicle model as well as real-time execution, S-Function Builder, MATLAB scripts, and supporting hardware are used to display capabilities. It is evident that advanced engineering will include modeling and systems simulation in order to remain competitive in the future.
Alan is a senior hardware systems engineer for HELLA Electronics Corp. His responsibilities include developing hardware systems solutions for energy storage, innovating applications for hybrid vehicles, and modeling and simulating fuel economy strategies using MATLAB and Simulink. He is recognized for his collaborative work with OEMs, devising energy management solutions for micro-hybrid electrical systems, isolation monitoring, lithium-ion battery electronics, hybrid/electric vehicle high-voltage charging, and current-sensing applications.
Doris is in his senior year at the University of Michigan-Dearborn, studying computer engineering and Spanish. His areas of expertise are automotive embedded devices and vehicle powertrain systems. He plans to pursue a master’s degree in automotive engineering from the University of Michigan-Dearborn upon completion of his bachelor’s. During his internship at HELLA, he acquired invaluable hands-on experience with embedded fuel pump controllers and vehicle models using MATLAB. He also became highly knowledgeable with several other key tools for simulating engine, transmission, and electrical systems and fuel consumption.
Dennis Craggs, Chrysler Group LLC
Data acquisition boxes are installed in Chrysler cars and trucks to measure their usage. The data is transmitted wirelessly and stored for future analysis. The resulting individual vehicle files are large, with about 20 million time-stamped records for 40 to 50 data channels collected at a rate of one and five readings per second for about a year. Traditionally, engineers have used tools like Microsoft® Excel® to analyze this data, but Excel is limited to 1,048,576 rows of data. This presentation discusses how Chrysler uses MATLAB to read and analyze the data and project customer usage.
Dennis works in Chrysler’s Duty Cycle group analyzing customer usage. Prior to working in the quality office, he worked as a reliability engineer in electrical engineering. He has previously worked in the aerospace industry for NASA and Teledyne CAE and in automotive for Ford. Dennis has master’s degrees in operations research and engineering mechanics and a bachelor’s degree in mechanical engineering. He is a PE, CRE, and CQE.
R.J. Kromer, The Ohio State University Center for Automotive Research
Over the last decade, the Buckeye Bullet Program at The Ohio State University has set numerous international and national land speed records for electric vehicles, using both battery and fuel cell power systems. Designing and controlling these systems for a land speed racing application provides unique challenges that are not encountered in normal operation. This session presents an overview of the challenges and solutions for data analysis, modeling, and simulation of the 2009 and 2010 vehicles. Case studies of particularly interesting problems are covered, with a focus on the new 2013 400 mph vehicle.
R.J. is a dual master’s student in electrical and computer engineering and mechanical engineering at The Ohio State University. R.J. has been a member of OSU’s Buckeye Bullet Program since 2007, serving in various roles including electrical team lead, and is currently a graduate fellow at OSU’s Center for Automotive Research. He wrote an article entitled “Lightning Fast” about the Buckeye Bullet that appeared in the ETAS Real Times in 2011. R.J. belongs to the Eta Kappa Nu and Texnikoi honor societies. He received his bachelor of science in electrical and computer engineering from OSU in 2010.
Reza Sahba, Magna Electronics
Modern driver assistance systems implement the comprehension and judgment capabilities of a driver to interpret the events and observations on the road. This introduces a new form of complexity in the software to model the cognitive capabilities of a human. Traffic Sign Recognition and Display is an example of such a system. Observing the current traffic sign and vehicle maneuvers, retrieving the memory of what has been observed in the past, and considering the regional road and traffic rules all affect the logic behind selecting the valid traffic signs to display. This presentation outlines the creation of a configurable and reusable mathematical model in MATLAB and Simulink for logical interpretation of traffic signs and vehicle maneuvers. The benefits of using MATLAB and Simulink in the verification of this model are also discussed.
Reza works in the Driver Assistance Systems division of Magna Electronics in Michigan. He has been working in the automotive industry for 11 years. Before joining Magna Electronics, he worked on model-based control algorithms for engine management at Continental Automotive. He also worked on model-based software development concepts and the development of a series of production control units at the R&D center of Bosch in Germany. Reza holds a master of science degree in communication engineering from the University of Stuttgart in Germany.
Zhijun Tang and Xubin Song, Eaton Corporation
When working to improve vehicle energy efficiency, engineers must consider how the vehicle is operated. Different drivers and driving styles can create significant differences in actual fuel economy from the same type of vehicles. Eaton is developing LookAhead technology to minimize the drive odds for achieving the driving consistency for better fuel economy. The modularized system includes a GPS-based map database, mobile broadband traffic information, and on-board vehicular radar. With the application of Vehicle Network Toolbox™ and a single board computer, the LookAhead system can be integrated seamlessly into the Eaton UltraShift Plus powertrain system on a Class 8 long-haul truck. This presentation shows the details of system integration including related test data to demonstrate the effectiveness of this technology for improving the fuel economy.
Zhijun is a manager of research and technology at Eaton Corporation. His specialties include signal processing, sensor fusion, data mining, intelligent systems, and controls. His research interests include autonomous and semi-autonomous vehicles, energy management systems for mobile and stationary applications, and diagnostics and prognostics. Zhijun received his Ph.D. in electrical and computer engineering from The Ohio State University and M.S. and B.S. degrees from Zhejiang University, China. He has been published in IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Robotics, and International Journal of Nonlinear and Robust Control, as well as proceedings from the IEEE Conference on Intelligent Transportation Systems, IEEE Conference on Decision and Control, American Control Conference, and ITS World Congress. Zhijun is a member of IEEE and SAE.
Xubin works on advanced powertrain controls for commercial vehicles at Eaton Corporation. His research interest is vehicle-related nonlinear and nonsmooth dynamics and control, especially advanced powertrain and chassis systems for ground vehicles; he holds six U.S. patents and one European patent and has published more than 50 papers. Prior to joining Eaton in 2004, his industry experience in the U.S. includes the development of chassis system controls (2000–2004) with Visteon Corporation and the iBOT human transporter (1999–2000) with MSX International. He worked as engineer for the China Academy of Launch Vehicle from 1988 to 1994. Xubin received his Ph.D. from Virginia Polytechnic Institute & State University, B.S. from Nanjing University of Aeronautics & Astronautics, and M.S. from China Academy of Launch Vehicle. He is an active member of IEEE, ASME, and SAE, holding membership of several technical committees. Currently he is working as a founding editor-in-chief of International Journal of Powertrains, published by Inderscience.
Sam Lee, General Motors Company
Model-Based Design has become the preferred approach for developing automotive embedded software. This presentation describes the development of an engine setpoint controller using Model-Based Design and xPC Target™ Turnkey. The engine setpoint controller is designed to monitor engine rotation and other engine parameters and to control fuel, spark, and other engine actuators. The engine setpoint controller also allows control algorithms developed using Model-Based Design to be implemented and executed. Specific topics include the I/O driver designed with Simulink blocks, deployment of our custom VHDL® code to the I/O module of xPC Target, and a human machine interface design for the engine setpoint controller.
Sam is a control algorithm engineer for General Motors. He is responsible for engine setpoint controller development and deployment within GM R&D for combustion research and early engine development. He has a Ph.D. in electrical engineering from Wayne State University.