2024
DOI: 10.3390/en17081850
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Modelling CO2 Emissions from Vehicles Fuelled with Compressed Natural Gas Based on On-Road and Chassis Dynamometer Tests

Maksymilian Mądziel

Abstract: In response to increasingly stringent global environmental policies, this study addresses the pressing need for accurate prediction models of CO2 emissions from vehicles powered by alternative fuels, such as compressed natural gas (CNG). Through experimentation and modelling, one of the pioneering CO2 emission models specifically designed for CNG-powered vehicles is presented. Using data from chassis dynamometer tests and road assessments conducted with a portable emission measurement system (PEMS), the study … Show more

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Cited by 4 publications
(3 citation statements)
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“…These models offer a promising approach to microscale environmental analysis. Another similar study utilizing artificial intelligence methods for modeling is [62]. This study addresses the urgent need for accurate prediction models of CO2 emissions from vehicles powered by compressed natural gas (CNG) in light of increasingly stringent global environmental policies.…”
Section: Discussionmentioning
confidence: 99%
“…These models offer a promising approach to microscale environmental analysis. Another similar study utilizing artificial intelligence methods for modeling is [62]. This study addresses the urgent need for accurate prediction models of CO2 emissions from vehicles powered by compressed natural gas (CNG) in light of increasingly stringent global environmental policies.…”
Section: Discussionmentioning
confidence: 99%
“…These models offer a promising approach to microscale environmental analysis. Another similar study utilizing artificial intelligence methods for modeling is [62]. This study responds to the pressing demand for precise prediction models of CO 2 emissions from vehicles powered by compressed natural gas (CNG), given the escalating stringency of global environmental policies.…”
Section: Discussionmentioning
confidence: 99%
“…The validation indicators for summer conditions showed an R² of 86% and an MSE of 1.4, while for winter conditions, these were 89% and 2.8, respectively. Other examples of works that similarly describe the modeling methodology but related to alternative fuels and their emissions are works [43][44][45].…”
Section: Discussionmentioning
confidence: 99%