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Using artificial neural networks to represent a diesel–biodiesel engine

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Abstract

In this work, six computational models based on artificial neural networks were developed to simulate an operating diesel engine fuelled with 8% biodiesel in order to predict performance and emissions of a diesel–biodiesel engine in a group generator. The ANN models were used to simulate a diesel–biodiesel engine that has four cylinders with a volume of 3.9 l, a compression ratio of 17:1, direct injection, and a rated power of 49 kW. The models were validated against experimental data for 10 kW, 20 kW, and 30 kW loads. The models were capable of accurately predicting the output power, thermal efficiency, and emissions of CO2, CO, NO, and NOx. Their comparison with experimental results showed a satisfactory agreement and the reliability of their predicted results for new operating conditions.

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Acknowledgements

The authors thank the Brazilian National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES), the Foundation of Support Research of the State of Minas Gerais (FAPEMIG), and the Pontifical Catholic University of Minas Gerais (PUC Minas) for the financial support of this project.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Pontifical Catholic University of Minas Gerais, Av. Dom José Gaspar, 500, Belo Horizonte, MG, CEP 30535-610, Brazil

    Cecília Souto Lage & Sérgio de Morais Hanriot

  2. Department of Computing Science, Pontifical Catholic University of Minas Gerais, Av. Dom José Gaspar, 500, Belo Horizonte, MG, CEP 30535-610, Brazil

    Luis Enrique Zárate

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  1. Cecília Souto Lage
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  3. Luis Enrique Zárate
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Correspondence to Sérgio de Morais Hanriot.

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Lage, C.S., de Morais Hanriot, S. & Zárate, L.E. Using artificial neural networks to represent a diesel–biodiesel engine. J Braz. Soc. Mech. Sci. Eng. 42, 575 (2020). https://doi.org/10.1007/s40430-020-02666-y

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