Statistical analysis of CO2emission based on road grade, acceleration and vehicle specific power for public utility vehicles: An IoT application

摘要

In the Philippine transport, the public utility vehicles (PUVs) are one of the top emitters of CO₂emissions (CO₂e). Moreover, the need of quantifying the CO₂e of PUV is important in reducing the emission. Hence, this paper focuses on the statistical evaluation of CO₂e of PUV based on the parameters affecting it - road grade, acceleration, and vehicle specific power (VSP). An Internet of Things (IoT) system with onboard CO₂sensors, GPS receivers, wireless communication nodes and a base station, online elevation query, cloud server, and an online IoT monitoring dashboard were used to remotely gather, store and visualize the needed measurements. The correlations of CO₂e according to these parameters were analyzed using statistical tools - histograms, box plots, and scatter plots. Results have shown that the correlation of PUV CO₂e with respect to downhill roads, uphill roads, and acceleration follows a U-shaped curves with the trough from the ranges of -19% to -3% at -16%, 3% to 22% at around 13% to 16%, and from -4m/s2 to 3m/s2 at -2m/s2, respectively. Likewise, significant changes of CO₂e were observed at different levels of VSP. Evidently, the mentioned factors have significantly affected the CO₂e of the PUVs.