Energies, Volume 17, Issue 7
2024 April-1 - 282 articles
Cover Story: This study aims to conduct a comprehensive analysis of the CO2 emission data for LDVs and investigate key prediction model characteristics for the data. The results show that the linear models can achieve good prediction performance comparable to that of nonlinear models and provide superior interpretability and reliability. The non-linear generalized additive models exhibit enhanced accuracy but display varying performance with model and parameter choices. The results verify the strong impact of fuel consumption and powertrain attributes on emissions and their substantial influence on the prediction models. The paper uncovers crucial relationships between vehicle features and CO2 emissions from LDVs. These findings provide insights for model and parameter selections for effective and reliable prediction of vehicle emissions and fuel consumption. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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