SAE 2014 Commercial Vehicle Engineering Congress

Technical Session Schedule

Thursday, October 9

Model Based Design - Part 2 of 2
(Session Code: CV407)

Room 45  1:00 p.m.

To manage design complexity and deliver innovations while reducing development time and improving quality, companies are turning to math-based models and a process known as Model-Based Design. Engineers use an executable specification to iterate through design concepts for the system and/or embedded controls using simulation. The specification then serves as the basis for model-based early verification, in-the-loop testing, and production code generation.

Organizers - Wensi Jin, MathWorks Inc.

Time Paper No. Title
1:00 p.m. 2014-01-2392
ORAL ONLY
Model Based System Engineering (MBSE) approach for the investigation and the development of a new excavator.
Hidekazu Niu, Yanmar Co. Ltd.; Nicolas Arrigoni, Lionel Broglia Patron, LMS Imagine
1:30 p.m. 2014-01-2391
Using a Statistical Machine Learning Tool for Diesel Engine Air Path Calibration
Farraen Mohd Azmin, Richard K. Stobart, Loughborough University; John Rutledge, Caterpillar Inc.; Edward Winward, Loughborough University
2:00 p.m. ORAL ONLY
COR (Custom Output Range) DoE iterative online test planning as a solution for tough modeling tasks
Today Design of Experiment (DoE) methods are heavily applied to powertrain calibration tasks in order to reduce the testing effort despite of the increasing engine complexity. Newest developments which are actually running in parallel at different OEMs use the idea of iterative test planning. You start with a very small test plan and use the gained measurement results to add test candidates online during the test which give more useful information for the particular application task. COR DoE uses this principle and has proven in different practical examples that the quality especially of tricky models like eg. Particulate matters (PM) could be increased by a factor of 5 in combination with semi-physical model building! At the same time the testing effort could be reduced by 15%.
Jun Wang, AVL Test Systems Inc.

Planned by Electrical and Electronics Group / Commercial Vehicle Activity