Determination of Optimal Engine Parameters for Exhaust Emissions Reduction Using the Taguchi Method

Abstract

In order to meet the ever more stringent exhaust emissions regulations and improve fuel consumption, heavy-duty Diesel engines (HDDE) have been equipped with electronically controlled components, including Exhaust Gas Recirculation systems (EGR), Variable Geometry Turbochargers (VGT) and advanced Fuel Injection Equipment (FIE) allowing for more flexible engine optimization. The introduction of such components increased the number of parameters influencing the optimization procedure; thus, significantly increasing the required amount of test-cell time to achieve an optimal engine calibration. Moreover, the adoption of aftertreatment systems, such as Selective Catalytic Reduction (SCR) technology or Diesel Particulate Filter (DPF) systems, required to comply with latest US-2010 and EURO V emissions legislations, requires flexible engine calibrations to address their efficiency dependency upon the thermodynamic conditions of the engine exhaust. The primary objective of this study was to develop and implement a simple multivariate optimization technique to program any given engine with multiple calibrations, both for steady-state and transient conditions, capable of modifying exhaust properties in order to guarantee optimal aftertreatment efficiencies during a wide range of engine operation. Four engine parameters, each at three levels, were selected for the optimization process, namely, EGR rate, VGT position, Start of Injection (SOI) and Nozzle Opening Pressure (NOP) as a surrogate for fuel injection pressure. Changes in control parameters which lead to an improvement in one specific emissions component may however often result in the deterioration of another. Thus, a good understanding of the relationship between individual control parameter effects is of utmost importance to correctly attain the optimum condition in short time and simultaneously reduce the number of experiments to be performed. Therefore, Design of Experiment (DOE) via factorial design, using the Taguchi method, was adopted to simultaneously study multiple factors and isolate the effects of changes in a single engine parameter on exhaust emissions. Different engine calibrations were obtained for an 11-liter Volvo engine by performing a set of only nine experiments for each engine speed/load point, which were selected to be equally distributed underneath the engine’s lug-curve. The main engine calibrations proved to be test cycle independent since comparable emission levels were observed over the European Steady-State Cycle (ESC) as well as the Federal Test Procedure (FTP). Reductions in Oxides of Nitrogen (NOx) on the order of 20% were achieved, while limiting the fuel consumption penalty to below 3%. Several high-efficiency calibrations were generated, achieving fuel consumption reductions close to 6%. Thus, the Taguchi method was found to be a viable way for simultaneous optimization of key engine parameters leading to a significant reduction in test-cell time; hence, relative development costs.