Performance analysis of a novel eco-friendly internal combustion engine cycle

Abstract

The Miller cycle applications have been performed to diminish NOx released from internal combustion engines (ICEs), in recent years. The Miller cycle provides decreased compression ratio and enhanced expansion ratio; hereby, maximum in-cylinder combustion temperatures diminish, and NOx formations slow down remarkably. Another less-known method is Takemura cycle application, which provides heat addition into engine cylinder at constant combustion temperatures. In this study, a novel cycle including the Miller cycle and the Takemura cycle has been developed by using novel numerical models and computing methods with seven processes and a novel way to decrease NOx emissions at higher levels compared with the single applications of known cycles. A comprehensive performance examination of the proposed cycle engine in terms of performance characteristics such as effective power (EFP), effective power density (EFPD), exergy destruction (X), exergy efficiency (epsilon), and ecological coefficient of performance (ECOP) has been conducted. The impacts of engine operating and design parameters on the performance characteristics have been computationally examined. Furthermore, irreversibilities depending on incomplete combustion loss (INCL), exhaust output loss (EXOL), heat transfer loss (HTRL), and friction loss (FRL) have been considered in the performance simulations. The minimum exergy destruction and maximum performance specifications have been observed with 30 of the compression ratio. Maximum effective power values have been obtained at range between 1 and 1.2 of equivalence ratio. The optimum range for exergy efficiency is between 0.8 and 1 of equivalence ratio. Increasing engine speed has provided enhancing effective power. However, an optimum range has been found for the exergy efficiency that is interval of 3000 to 4000 rpm. The results obtained can be assessed by researchers studying on modeling of the engine systems and designs.