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Co-modelling Strategy for Development of Airpath Metamodel on Multi-physics Simulation Platform

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Advances in Computational Intelligence Systems (UKCI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1043))

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Abstract

Dynamic modelling techniques are intensively studied to generate alternative solutions for engine mapping and calibration problem, aiming to address the need to increase productivity (reduce development time) and to develop better models for the actual behaviour of the engine under real-world conditions. There are many dynamic experiment and modelling techniques available in the literature and the trend is to select either a dynamic experiment or modelling technique in advance. The preselection of either a dynamic experiment or modelling technique does not allow for the analysis of the effect of such a choice on the modelling task and there exists a possibility that a different combination of experiment or modelling technique might perform better.

This paper presents an investigation of a co-modelling strategy which allows to select a signal and modelling technique combination suitable for the system modelling task. The proposed strategy was implemented on 2.0-L diesel engine using modelling techniques (neural network and neuro-fuzzy models) based on Multi-Physics simulation platform. The model selected via this strategy models the system behaviour accurately and enhances the real-time performance.

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Authors and Affiliations

  1. University of Bradford, Bradford, UK

    Gaurav Pant, Felician Campean, Aleksandrs Korsunovs & Daniel Neagu

  2. University of La Laguna, Tenerife, Spain

    Oscar Garcia-Afonso

Authors
  1. Gaurav Pant
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  2. Felician Campean
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  3. Aleksandrs Korsunovs
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  4. Daniel Neagu
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  5. Oscar Garcia-Afonso
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Corresponding author

Correspondence to Gaurav Pant .

Editor information

Editors and Affiliations

  1. School of Computing, University of Portsmouth, Portsmouth, UK

    Zhaojie Ju

  2. Department of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, UK

    Longzhi Yang

  3. Bristol Robotics Laboratory, University of the West of England, Bristol, UK

    Chenguang Yang

  4. School of Computing, University of Portsmouth, Portsmouth, Hampshire, UK

    Alexander Gegov

  5. School of Computing, University of Portsmouth, Portsmouth, UK

    Dalin Zhou

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Pant, G., Campean, F., Korsunovs, A., Neagu, D., Garcia-Afonso, O. (2020). Co-modelling Strategy for Development of Airpath Metamodel on Multi-physics Simulation Platform. In: Ju, Z., Yang, L., Yang, C., Gegov, A., Zhou, D. (eds) Advances in Computational Intelligence Systems. UKCI 2019. Advances in Intelligent Systems and Computing, vol 1043. Springer, Cham. https://doi.org/10.1007/978-3-030-29933-0_42

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