Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine

This paper presents an innovative engine optimization model integrated with a friction fitting tool to enhance the accuracy of computed performance for a marine dual-fuel engine. The focus is on determining the terms of the Chen–Flynn correlation—an empirical engine friction model—to improve the precision of friction and performance predictions. The developed model employs WAVE, a 1D engine simulation software, coupled with a nonlinear optimizer to identify the optimal configuration of key parameters, including the turbocharger, injection system, combustion behavior, and friction model. The optimization procedure maximizes the air–fuel ratio (AFR) within the engine while adhering to various predefined constraints. The model is applied to four operational points along the propeller curve, with the optimized results subsequently integrated into a friction fitting tool. This tool predicts the terms of the Chen–Flynn correlation through an updated procedure, achieving highly accurate results with a coefficient of determination (R2) value of 99.88%, eliminating the need for experimental testing. The optimized friction model provides a reliable foundation for future studies and applications, enabling precise friction predictions across various engine types and fuel compositions.