PROFESSIONAL EDITION | August 2012 | Issue 8

Mathematics-Based Modeling of a Series-Hybrid Electric Vehicle
Thursday, September 27th at 10:00 am EDT

The automotive industry is in transformation. The complexity of the automobile has increased exponentially in the past decades and has triggered a design revolution that stresses detailed modeling and simulation steps prior to committing to metal and plastic. With new generation vehicles deploying hybrid (HEV), fully electric (EV), and fuel cell powerplants, the need for advanced physical modeling solutions is considerably greater due to increasing system complexity. This webcast covers new approaches to modeling and simulation for HEV and EV vehicle applications with emphasis on the development of high-fidelity physical models of automotive batteries. To speed up the design and prototyping processes of HEVs, a method that automatically generates mathematics equations governing the vehicle system response in an optimized symbolic form is desirable. To achieve this goal, the physical modeling tool MapleSim was employed to develop the multidomain model of a series-HEV, using the symbolic computing algorithms of the Maple software package to generate an optimized set of governing equations. The HEV model consists of a mean value internal-combustion engine, a Li-ion battery pack, and a multibody vehicle model. Simulations are then used to demonstrate the performance of the HEV system. Simulation results show that the model is viable and the number of governing equations is reduced significantly, resulting in a computationally efficient system. Webcast attendees will be invited to interact with the speakers during the program's live Q&A segment.

Dr. John McPhee, Professor, Systems Design Engineering, University of Waterloo, and NSERC/Toyota/Maplesoft Industrial Research Chair, Mathematics-based Modeling and Design
Dr. John McPhee's main area of research is multibody system dynamics, with principal application to the analysis and design of vehicles, mechatronic devices, and biomechanical systems. He has won many awards, including a Premier's Research Excellence Award and the I.W. Smith Award from the Canadian Society of Mechanical Engineers. He completed his term in 2009 as the Executive Director of the Waterloo Centre for Automotive Research, spending a sabbatical year at the Toyota Technical Center in Ann Arbor, Michigan. He holds a Ph.D. in mechanical engineering from the University of Waterloo, Canada.
Dr. Sam Dao, Application Engineer, Maplesoft
Dr. Sam Dao received his Ph.D. degree in mechatronics from the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. He is currently an Application Engineer at Maplesoft. He has been involved in many research projects including multiple robot networking, hybrid electric vehicle modeling, and battery modeling.




Maplesoft Events
9th International Modelica Conference 2012
September 3-5
Munich, Germany
MSO-Tools 2012
September 24-26
Berlin, Germany

For further details about these events, click here.

Information Sheets
Maple Training Datasheet
Detailed course outline for Maple onsite training
MapleSim Training Datasheet
Detailed course outline for MapleSim onsite training

To access all Maplesoft Information sheets, click here.

Social Networks

Modern techniques bring system-level modeling to the automation industry

With industry experiencing ever increasing pressure for shorter and shorter engineering design cycles, engineers are finding that they can save significant time by determining the properties of their system before building a physical prototype. For example, knowing the expected forces and accelerations present within a system allows for proper sizing of actuators. While system-level modeling is becoming increasingly common for mechatronic designs in the automotive and aerospace industries, it has yet to proliferate in the automation industry. This is likely due to perceptions that system-level modeling is time-consuming and requires a high level of mathematical expertise for model derivations. Traditionally, this has been true: the typical “signal-flow” process required lengthy, error-prone, hand-derivation of system equations and usually resulted in a complex block diagram. Recent advances in engineering design technology, however, have enabled a better, modern approach to system-level modeling and simulation.

This whitepaper explores this new technology, using applications in MapleSim™ together with Automation Studio from B&R Automation to illustrate the approach and explore some of the resulting benefits. This paper then highlights how the modern technologies incorporated in MapleSim benefit system-level design in general.

For more information, click here to read the full whitepaper.


Symbolic Computation Techniques for Multibody Model Development and Code Generation

Multibody models can generate large systems of differential algebraic equations (DAEs). These equations can take a significant amount of time to solve numerically and often the modeller needs to make difficult decisions between model fidelity and simulation speed.

This webinar presents some of the benefits of a general purpose symbolic computation environment when constructing and generating simulation code for multibody, multi-domain systems. Specifically, it considers how tools provided by these environments can be harnessed to generate highly efficient simulation code through coordinate selection, symbolic manipulation, and expression optimization.



Revamped MapleSim Model Gallery

The MapleSim Model Gallery has been dramatically revamped and now includes over 100 models. Discover the breadth and depth of MapleSim by browsing the real-world application examples from the MapleSim Model Gallery. The gallery currently contains examples from the following industries: Academic, Aerospace, Motion Control, Power Industries, Vehicle Engineering.

If your industry is not listed, or you want to discover more application examples, speak to our MapleSim experts for a personalized demonstration of how MapleSim can benefit you in your industry.

Video: Amir Khajepour talking about his rover project
  Dr. Amir Khajepour, Professor, Mechanical and Mechatronic Engineering, University of Waterloo, and Canada Reserach Chair in Mechatronic Vehicle Systems, describes his use of MapleSim and Maple in his research project with the Canadian Space Agency, in which he is designing models of autonomous space rovers for Mars exploration.
NASA Jet Propulsion Laboratory to Land Rover on Mars on Monday
  JPL recently began a widespread adoption of Maplesoft technology, and Maplesoft’s products are expected to help JPL save time and reduce cost by providing more efficient and smarter methods for mathematical analysis, modeling, and simulation.
Live Webinars
SAE Webinar: Mathematics-Based Modeling of a Series-Hybrid Electric Vehicle
Thursday, September 27 at 10:00 am EDT
Physical Modeling and Simulation with MapleSim
Thursday, September 6 at 10:00 am EDT
Industry Applications of Maple 16
Wednesday, September 12 at 10:00 am EDT
A Guide to Evaluating Maple 16
Thursday, September 20 at 2:00 pm EDT
Recorded Webinars
Présentation Maple 16
New Technology for Modelling HEVs and EVs
Space Equipment Gets in the Loop - MapleSim breaks new ground in HIL real-time simulation for planetary rovers
Desktop Engineering, August 7, 2012

“Dr. Amir Khajepour, Canada Research Chair in Mechatronic Vehicle Systems and a professor of engineering in the Mechanical and Mechatronics Engineering department at the University of Waterloo (UW), and his team worked with the Canadian Space Agency (CSA) and Maplesoft, to develop a hardware-in-the-loop (HIL) test platform for solar-powered planetary rovers... the main advantage of their approach is that it significantly reduces the overall development time in the project.”
Transmission modeling and simulation: key to reducing power loss
Automotive Engineering Online, July 18, 2012

“Over the last decade there has been a remarkable push toward acausal modeling environments, such as MapleSim from Maplesoft, which takes a different approach to modeling. Rather than representing mathematics directly, models use components that contain governing equations, and it is incumbent on the solver to perform the mathematical manipulation.”
Battery Design is Charging Ahead
Desktop Engineering, July 2, 2012

“...the industry is turning increasingly to math-based modeling techniques that allow engineers to accurately describe the behavior of the system--and the constraints on the system--in physical terms. These model equations are then used to develop, test and refine designs quickly, without building physical prototypes. Hence, having a good virtual model of the battery is essential so that both battery behavior and the physical interaction of the battery with all the other components are properly reflected in the model.”

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