燃烧
环境科学
汽车工程
计算机科学
工程类
有机化学
化学
出处
期刊:Energies
[MDPI AG]
日期:2023-10-02
卷期号:16 (19): 6928-6928
被引量:1
摘要
Current emission models primarily focus on traditional combustion vehicles and may not accurately represent emissions from the increasingly diverse vehicle fleet. The growing presence of hybrid and electric vehicles requires the development of accurate emission models to measure the emissions and energy consumption of these vehicles. This issue is particularly relevant for low-emission zones within cities, where effective mobility planning relies on simulation models using continuously updated databases. This research presents a two-dimensional emission model for hybrid vehicles, employing artificial neural networks for low-emission zones. The key outcome is the methodology developed to create a CO2 emission model tailored for hybrid vehicles, which can be used to simulate various road solutions. The CO2 emission model achieved an R2 coefficient of 0.73 and an MSE of 0.91, offering valuable information for further advancements in emission modelling.
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