Evaluation and improvement of road vehicle pollutant emission factors based on instantaneous emissions data processing

Resumen

Introduction Current instrumentation makes it possible to measure vehicle emissions with high temporal resolution. But the increased resolution of emissions signals does not equate with increased accuracy. A prerequisite for the derivation of accurate emission factors from instantaneous vehicle emissions data is a fine allocation of measured mass emissions to recorded engine or vehicle states. This poses a technical challenge, because vehicle emission test facilities are not designed to support instantaneous emissions modelling, and they introduce distorting effects that compromise the instantaneous accuracy of the measured signals. Methodology These distorting effects can be compensated through a combination of physical modelling and data post-processing. The main original contribution of this dissertation is a novel methodology for the compensation of instantaneous emission signals, which is fully described herein. Whereas previous methodologies relied on systems theory modelling, and on comprehensive testing to model the sub-systems of the measurement setup, the alternative approach uses CO2 as a tracer of the distortions brought about by the measurement setup, which is modelled as a 'lump' system. Conclusions The main benefits of this methodology are its low burden of experimental work and its flexibility. Furthermore, it has been fully implemented in the 'esto' software tool, which can perform the compensation of emission signals with minimal user intervention and speed up the creation of engine emission maps.