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Data from portable emissions measurement systems (PEMS) and other sources have allowed the discrepancy between type approval and real-world fuel economy and nitrogen oxides (NOx) emissions to be both identified and quantified. However, a gap in the knowledge persists because identifying this discrepancy does not allow us to predict real-world fuel economy and emissions accurately. We address this gap in the knowledge using a bottom-up approach: a PEMS is used across a range of Euro 6 petrol and diesel vehicles, from which internally-consistent powertrain models are derived. These training vehicles are simulated over 20 real-world and regulated driving cycles. 26 metrics representing driving, vehicle and ambient characteristics are used to develop quantile regression (QR) models for three vehicle groups: direct-injection petrol vehicles with three way catalysts; diesel vehicles with selective catalytic reduction; and diesel vehicles with lean NOx traps. 95% prediction intervals are used to assess the predictive accuracy of the QR models from a set of validation vehicles. Across the vehicle groups, QR models for both fuel economy and NOx emissions depended on the dynamics of the driving cycles more than the engine characteristics or ambient conditions. The 95% prediction interval for fuel economy enclosed most of the observed values from the PEMS test, with similar prediction error to COPERT in most cases. The bene ts of the QR approach were more pronounced for NOx emissions, where the majority of PEMS observed data was enclosed in the 95% PI and median prediction error was up to two times lower than COPERT.

Air pollution problems persist in many cities throughout the world, despite drastic reductions in regulated emissions of criteria pollutants from vehicles when tested on standardised driving cycles. New vehicle emissions regulations in the European Union and United States require the use of OBD and portable emissions measurement systems (PEMS) to confirm vehicles meet specified limits during on-road operation. The resultant in-use testing will yield a large amount of OBD and PEMS data across a range of vehicles. If used properly, the availability of OBD and PEMS data could enable greater insight into the nature of real-world emissions and allow detailed modelling of vehicle energy use and emissions. This paper presents a methodology to use this data to create engine maps of fuel use and emissions of nitrous oxides (NOx), carbon dioxide (CO2) and carbon monoxide (CO). Effective gear ratios, gearbox shift envelopes, candidate engine maps and a set of vehicle configurations are simulated over driving cycles using the ADVISOR powertrain simulation tool. This method is demonstrated on three vehicles – one truck and two passenger cars – tested on a vehicle dynamometer and one driven with a PEMS. The optimum vehicle configuration and associated maps were able to reproduce the shape and magnitude of observed fuel use and emissions on a per second basis. In general, total simulated fuel use and emissions were within 5% of observed values across the three test cases. The fitness of this method for other purposes was demonstrated by creating cold start maps and isolating the performance of tailpipe emissions reduction technologies. The potential of this work extends beyond the creation of vehicle engine maps to allow investigations into: emissions hot spots; real-world emissions factors; and accurate air quality modelling using simulated per second emissions from vehicles operating in over any driving cycle.