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Current political and environmental concerns are driving renewed efforts to develop techniques for improving the efficiency of internal combustion engines. A detailed thermodynamic analysis of an engine and its components from a 1st and 2nd Law perspective is necessary to characterize system losses and to identify efficiency opportunities. We have developed a method for performing this analysis using simulation results from commercially available engine-modeling software packages such as WAVE® from Ricardo, Inc., and GT-Power™ from Gamma Technologies, Inc. Results from the simulation are post-processed to compute thermodynamic properties such as internal energy, enthalpy, entropy, and availability (or exergy) which are required to perform energy and availability balances for the system. This analysis is performed for all major engine components (turbocharger, intercooler, EGR cooler, etc.) and for the engine as a whole as a function of crank angle over an entire engine cycle.

Large cyclic variability along with increased combustion noise present in low temperature combustion (LTC) modes of internal combustion engines has driven the need for fast response, robust sensors for diagnostics and feedback control. Accelerometers have been shown as a possible technology for diagnostics and feedback control of advanced LTC operation in internal combustion engines. To make better use of this technology, an improved understanding is necessary of the effect of energy release from the combustion process on engine surface vibrations. This study explores the surface acceleration response for a single-cylinder engine operating with homogeneous charge compression ignition (HCCI) combustion. Preliminary investigation of the engine surface accelerations is conducted using a finite element analysis of the engine cylinder jacket along with consideration of cylindrical modes of the engine cylinder.

We investigate lean-fueling cyclic dispersion in spark ignition engines in terms of experimental nonlinear mapping functions representing the connection between past and future combustion events. Nonlinear mapping functions provide a relatively easy method for identifying the deterministic dynamics associated with lean combustion instability, even in the presence of very high levels of noise. Observed experimental maps appear to have strong similarities to those predicted by an existing nonlinear spark ignition engine model. Differences between the observed map and model predictions become more pronounced at very lean fueling and high residual fraction. Map function details are shown to be useful in model validation, identifying model deficiencies, and comparing the characteristics of different engines. We expect that such maps will also be useful for developing real-time control strategies.

Advances in engine controls and sensor technology are making advanced, direct, high-speed control of engine combustion more feasible. Control of combustion rate and phasing in low-temperature combustion regimes and active control of cyclic variability in dilute SI combustion are being pursued in laboratory environments with high-quality data acquisition systems, using metrics calculated from in-cylinder pressure. In order to implement these advanced combustion controls in production, lower-quality data will need to be tolerated even if indicated pressure sensors become available. This paper examines the effects of several data quality issues, including phase shifting (incorrect TDC location), reduced data resolution, pressure pegging errors, and random noise on calculated combustion metrics that are used for control feedback.