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Non-Invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review

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  • Norah Nadia Sánchez Torres

    (Interdisciplinary Postgraduate Program in Energy & Sustainability (PPGIES), Federal University of Latin American Integration—UNILA, Av. Tancredo Neves, 3147, Foz do Iguaçu 85867-000, PR, Brazil)

  • Jorge Gomes Lima

    (Smart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), Jardim Universitário, s/n, João Pessoa 58051-900, PB, Brazil)

  • Joylan Nunes Maciel

    (Interdisciplinary Postgraduate Program in Energy & Sustainability (PPGIES), Federal University of Latin American Integration—UNILA, Av. Tancredo Neves, 3147, Foz do Iguaçu 85867-000, PR, Brazil)

  • Mario Gazziro

    (Information Engineering Group, Department of Engineering and Social Sciences (CECS), Federal University of ABC (UFABC), Av. dos Estados, 5001, Santo André 09210-580, SP, Brazil)

  • Abel Cavalcante Lima Filho

    (Department of Mechanical Engineering (DEME), Technology Center (CT), Federal University of Paraiba (UFPB), Jardim Universitário, s/n, João Pessoa 58051-900, PB, Brazil)

  • Cicero Rocha Souto

    (Smart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), Jardim Universitário, s/n, João Pessoa 58051-900, PB, Brazil)

  • Fabiano Salvadori

    (Smart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), Jardim Universitário, s/n, João Pessoa 58051-900, PB, Brazil)

  • Oswaldo Hideo Ando Junior

    (Interdisciplinary Postgraduate Program in Energy & Sustainability (PPGIES), Federal University of Latin American Integration—UNILA, Av. Tancredo Neves, 3147, Foz do Iguaçu 85867-000, PR, Brazil
    Smart Grid Laboratory (LabREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), Jardim Universitário, s/n, João Pessoa 58051-900, PB, Brazil
    Research Group on Energy & Energy Sustainability (GPEnSE), Academic Unit of Cabo de Santo Agostinho (UACSA), Federal Rural University of Pernambuco (UFRPE), Rua Cento e Sessenta e Três, 300, Cabo de Santo Agostinho 54518-430, PE, Brazil
    Program in Energy Systems Engineering (PPGESE), Academic Unit of Cabo de Santo Agostinho (UACSA), Federal Rural University of Pernambuco (UFRPE), Rua Cento e Sessenta e Três, 300, Cabo de Santo Agostinho 54518-430, PE, Brazil)

Abstract

This article provides a detailed analysis of non-invasive techniques for the prediction and diagnosis of faults in internal combustion engines, focusing on the application of the Proknow-C and Methodi Ordinatio systematic review methods. Initially, the relevance of these techniques in promoting energy sustainability and mitigating greenhouse gas emissions is discussed, aligning with the Sustainable Development Goals (SDGs) of Agenda 2030 and the Paris Agreement. The systematic review conducted in the subsequent sections offers a comprehensive mapping of the state of the art, highlighting the effectiveness of combining these methods in categorizing and systematizing relevant scientific literature. The results reveal significant advancements in the use of artificial intelligence (AI) and digital signal processors (DSP) to improve fault diagnosis, in addition to highlighting the crucial role of non-invasive techniques such as the digital twin in minimizing interference in monitored systems. Finally, concluding remarks point towards future research directions, emphasizing the need to develop the integration of AI algorithms with digital twins for internal combustion engines and identify gaps for further improvements in fault diagnosis and prediction techniques.

Suggested Citation

  • Norah Nadia Sánchez Torres & Jorge Gomes Lima & Joylan Nunes Maciel & Mario Gazziro & Abel Cavalcante Lima Filho & Cicero Rocha Souto & Fabiano Salvadori & Oswaldo Hideo Ando Junior, 2024. "Non-Invasive Techniques for Monitoring and Fault Detection in Internal Combustion Engines: A Systematic Review," Energies, MDPI, vol. 17(23), pages 1-20, December.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:6164-:d:1538514
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    References listed on IDEAS

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    1. Paulo Gabriel Martins Leandro & Fabiano Salvadori & José Enrique Eirez Izquierdo & Marco Roberto Cavallari & Oswaldo Hideo Ando Junior, 2024. "The Advancements and Challenges in Organic Photovoltaic Cells: A Focused and Spotlight Review Using the Proknow-C," Energies, MDPI, vol. 17(17), pages 1-18, August.
    2. Theofanis D. Hountalas & Maria Founti & Theodoros C. Zannis, 2023. "Experimental Investigation to Assess the Performance Characteristics of a Marine Two-Stroke Dual Fuel Engine under Diesel and Natural Gas Mode," Energies, MDPI, vol. 16(8), pages 1-19, April.
    3. Helton Rogger Regatieri & Oswaldo Hideo Ando Junior & José Ricardo Cezar Salgado, 2022. "Systematic Review of Lithium-Ion Battery Recycling Literature Using ProKnow-C and Methodi Ordinatio," Energies, MDPI, vol. 15(4), pages 1-23, February.
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