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Analysing the real-world fuel and energy consumption of conventional and electric cars in Europe

机译：Analysing the real-world fuel and energy consumption of conventional and electric cars in Europe

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摘要

The transport sector constitutes one of the main sources of greenhouse gas emissions in the European Union. Although the literature is rich in studies assessing the factors influencing energy consumption in real world driving, few analyse the divergence between certified and real-world consumption on a fleet level and annual temporal resolution. The present work builds on the findings of previous studies to provide a complete simulation-based approach for fleet-level projections in real-world scenarios. A tailored simulation framework for fleet-wide analysis has been updated and validated extensively for current vehicle configurations. In addition to modelling, the analysis used data describing real-world conditions and vehicle characteristics representative of the European passenger car fleet and operation profile. Validation demonstrates good accuracy in simulating the vehicle measured consumption values with a near-zero mean error when simulating laboratory and on-road measurements. The impact of the certification procedure was quantified at 6% for both the combustion engine and battery electric vehicles. The influence of real-world factors such as traffic, ambient temperature and cabin air conditioning was quantified, and the results show a greater energy impact in the cold than in warm conditions. Different operating conditions were simulated to investigate the model's capacity to estimate the distribution of the average sales-weighted gap in energy consumption between officially reported CO_2 values and the real-world ones. The study focuses on three scenarios: average European conditions, the best and worst case for assessing the extremes, and a Monte Carlo-based scenario to determine the impact of warm and cold periods. Results show average gap values of 13.5% (best case) and 34.5% (worst case) for conventional vehicles and -4.5% (best case) and 23.9% (worst case) for battery electric ones. Warm and cold weather conditions result in 5.5 and 7.5% increases for conventional and hybrids and 7.5 and 15% for electrics, respectively.

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