A novel method for in-cylinder pressure prediction using the engine instantaneous crankshaft torque

Tsitsilonis, Konstantinos-Marios and Theotokatos, Gerasimos (2021) A novel method for in-cylinder pressure prediction using the engine instantaneous crankshaft torque. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment. ISSN 1475-0902

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    Current practices of condition assessment in large marine engines are largely based on the measurement of cylinder pressure using external kits, which poses challenges due to sensors synchronisation and durability issues, as well as the inability to perform continuous monitoring. For addressing these challenges, this study aims at developing a novel method to solve the inverse problem of predicting the pressure variations in all engine cylinders, by using the Instantaneous Crankshaft Torque (ICT) measurement for large internal combustion engines. This method is developed by considering the Initial Value Problem (IVP) technique along with the integration of a direct crankshaft dynamics model incorporating the sensitivity parameters and stability criteria calculation based on the Lyapunov Exponent (LE) as well as a state-of-the-art Nonmonotone Self-Adaptive Levenberg-Marquardt (NSALMN) optimisation algorithm. The method is tested for a number of case studies using different combustion models based on the Weibe and sigmoid functions, as well as for healthy, degraded and faulty engine conditions. The derived results demonstrate adequate accuracy exhibiting a maximum error of 0.3% in the prediction of the mean peak in-cylinder pressure. The analysis of the calculated sensitivity parameters resulted in the identification of the parameters that significantly impact the solution, thus providing improved insights for selecting the developed method settings. The developed method renders the continuous and non-intrusive in-cylinder pressures monitoring feasible, by using a permanently installed shaft power metre sensor with higher sample rates.

    ORCID iDs

    Tsitsilonis, Konstantinos-Marios ORCID logoORCID: https://orcid.org/0000-0002-1752-9440 and Theotokatos, Gerasimos ORCID logoORCID: https://orcid.org/0000-0003-3547-8867;