Online Optimization

Siemens VDO, Regensburg

From 01/2000 - 02/2002: Calibration Methods and Tools (partly 50% with other offline activity)

03/2002 to 01/2008 : Test Center, Engine Test Bench

Technical Project Leader for Online Optimization and Online Design of Experiments

Motivation:

"Manufacturers of modern internal combustion engines are confronted with increasing challenges: The legal restrictions concerning exhaust emissions are getting stricter, fuel is becoming more expensive and customers are demanding powerful and comfortable engines with low fuel consumption. As a result, engine complexity has greatly increased, as has the number of adjustable parameters. Tuning the engine thus results in a complex optimisation problem, whose solution requires the aid of computers. The application of computer-aided offline optimisation has become common. (...) They rely on the following principle: On the basis of an experimental plan, a sufficiently large number of measurements are performed at the test bed. This data, possibly combined with previous knowledge, is used to calculate a computer model that simulates the engine. This model can then be optimised by appropriate algorithms. The optima are again verified at the test bed and finally used for tuning the engine. In the online optimisation, the optimisation system directly interacts with the test bed, which means that, in the ideal case, the process is fully automatic. This approach carries the further advantage that information gained by measurement can be evaluated immediately. (...) Offline optimisation, on the other hand, has the advantage that the computation time can be completely separated from the test bed, i.e. the test bed can be used manually during the computations. The automatic test bed control with appropriate limit handling poses new challenges to the algorithms."

Publications / Conferences:

ENBIS (European Netwrok for Business and Industrial Statistics ) Conference 2007: Abstract

• Paper
• Slides

Workshop on Parameter Estimation and Optimal Design of Experiments - PARAOPE in Heidelberg in 2004 entitled: "The Use of intelligent Experimental Designs for Optimal Automotive Engine Calibration Online at Engine Test Bench"

Optimisation en ligne de moteurs automobiles sur bancs d'essais. Revue Techniques Avancées, June 2004. French

Second Workshop on Non-linear Optimization “Theoretical Aspects of Surrogate Optimization”, Coimbra 2002-05-16  I made a presentation entitled: “The Use of Surrogate-based Optimization in Engine Automatic Calibration on Test Bench”.
See https://www.gerad.ca/Charles.Audet/PUB/OPTE.doc. 

http://studylib.net/doc/7449127/2-the-engine-calibration-optimization-problem OPTE Special Issue on Surrogate Optimization

Bibliography:

Full bibliography (.bib file, last update 2007)

IAV DOE Conference

BMW MTZ Paper 05/2003

Model-Based Online Optimisation of Modern Internal Combustion Engines

Part 1: Active Learning (Deutsch)

Part 2: Limits of the Feasible Search Space   (Deutsch)

Modellbasierte Online-Optimierung in der Simulation und am Motorenprüfstand MTZ 01/2007

Mark Abramson PhD Thesis, Pattern Search Algorithms for Mixed Variable General Constrained Optimization Problems. (2002)

Related Software:

NOMADm Optimization Software  (see Acknowledgements) Mark Abramson

Acknowledgements

I owe a special debt of gratitude to my colleagues, John Dennis and Charles Audet, whose assistance in this project has been invaluable. I would also like to thank Keith Berrier, Olga Brezhneva, Ana Custodio, Gilles Couture, Thierry Dalon, John Dunlap, Nikolaus Hansen, Arantzazu Garcia-Lekue, Alison Marsden, Rachael (Pingel) Robison, Jacob Sondergaard, and Luis Vicente for numerous suggestions for correcting and improving the code. Also, thanks to Rakesh Kumar at MathWorks, Inc. for helpful discussions, and thanks to several other users, who have identified bugs and patiently waited for the fix.

DACE: http://www2.imm.dtu.dk/projects/dace/ Jacob Søndergaard, Hans Bruun Nielsen

https://github.com/l2/Biblio-code/blob/master/meta/dace/changelog

Version 1.3, July 3, 2002

 c  We would like to acknowledge the comments and suggestions from Thierry Dalon, from Siemens VDO Automotive AG, which is a great help in improving this software.

Commercial Software:

Engine Test Bench Automation Software:

• AVL CAMEO
• A&D ORION in cooperation with IAV
• D2T Morphée

MathWorks Genetic Algorithm and Direct Search Toolbox

MathWorks Model-Based Calibration Toolbox

Keywords: 

DOE: Design of Experiment

Model-based Calibration

Surrogate-based optimization

GPS: Generalized Pattern Search

FrontPage

Back to Engine Test Bench