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Evolutionary Optimization of Parametric Models: the Test Case of Combustion in a Diesel Engine

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Soft Computing: Methodologies and Applications

Part of the book series: Advances in Soft Computing ((AINSC,volume 32))

Summary

The tuning of parameter values in parametric modelling can be viewed as an optimization problem where the outcome of the optimal model is to be as similar as possible to the experimental data. We give a general formulation of the problem with different fitness function definitions, both in terms of single-objective and multi-objective evolutionary optimization. As a test case we show results on a parametric model of combustion in a combustion chamber of a diesel engine. Such an optimal model will therefore be used for a controller design. The outputs (pressure inside combustion chamber versus rotation angle) of the resulting optimal models are compared to experimental data. Results of different optimization runs with Differential Evolution (DE) and Evolution Strategy (ES) as search algorithms and with different fitness definitions are compared.

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Author information

Authors and Affiliations

  1. STMicroelectronics, SST Corporate R&D, Via C. Olivetti, 2, 20041, Agrate(MI), Italy

    M. Farina

  2. STMicroelectronics, SST Corporate R&D, Via Remo De Feo 1, 80022, Arzano (NA), Italy

    N. Cesario, D. Ruggiero & P. Amato

Authors
  1. M. Farina
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  2. N. Cesario
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  3. D. Ruggiero
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  4. P. Amato
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Editor information

Editors and Affiliations

  1. Fakultät für Elektrotechnik und Informationstechnik, Lehrstuhl für Elektrische Steuerung und Regelung, Universität Dortmund, Otto-Hahn-Str. 4, 44227, Dortmund, Germany

    Frank Hoffmann

  2. Fraunhofer IPK, Berlin

    Mario Köppen

  3. Institut für Sicherheits-/Prüftechnik, Pascalstr. 8-9, 10587, Berlin, Germany

    Mario Köppen

  4. FH Braunschweig/Wolfenbüttel, Salzdahlumer Str. 46/48, 38302, Wolfenbüttel, Germany

    Frank Klawonn

  5. Enterprise Integration, Cranfield University, Cranfield, Bedford, MK43 0AL, UK

    Rajkumar Roy

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© 2005 Springer-Verlag Berlin Heidelberg

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Farina, M., Cesario, N., Ruggiero, D., Amato, P. (2005). Evolutionary Optimization of Parametric Models: the Test Case of Combustion in a Diesel Engine. In: Hoffmann, F., Köppen, M., Klawonn, F., Roy, R. (eds) Soft Computing: Methodologies and Applications. Advances in Soft Computing, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32400-3_13

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  • DOI: https://doi.org/10.1007/3-540-32400-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25726-4

  • Online ISBN: 978-3-540-32400-3

  • eBook Packages: EngineeringEngineering (R0)

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