Experimental evaluation of gear-shift and internal-combustion engine variables on fuel consumption, noise and pollutant emissions

作者：Eloísa Macedo, Antonio Pascale, Elisabete Ferreira, Cláudio Guarnaccia, Margarida C. Coelho · 发表于：Transportation research procedia · 年份：2022 · DOI：10.1016/j.trpro.2022.02.087 · 被引用次数：12 · 研究领域：Vehicle emissions and performance、Air Quality and Health Impacts、Air Quality Monitoring and Forecasting

Although variability of noise and pollutant emissions are usually associated with vehicular speed and acceleration, driving style, mainly related to gear-shift and internal engine variables such as revolutions per minute (RPM) or engine load (EL), can also play a key role. Moreover, the contribution of each variable for fuel consumption, noise and pollutant emissions can vary for different vehicle-motorization types. However, the effect of such internal variables on noise and pollutant emissions is not fully exploited in the literature. Thus, this work aims to assess the impact of the gear selection, RPM, and EL on fuel consumption, and carbon dioxide (CO2), nitrogen oxides (NOx), and noise in terms of sound power level (Lw) emissions for a diesel passenger vehicle. This is focused on a speed and gear-based controlled on-road environment. Internal observable (fuel consumption, RPM, and EL) and kinematic (speed and acceleration) variables were recorded on a second-by-second time basis using an On-Board Diagnostic System, and noise data were recorded with a Sound Level Meter. Pollutant emissions were estimated using the Vehicle Specific Power (VSP) methodology with a 1Hz frequency. In this study, Clustering and Disjoint Principal Component Analysis is applied to find patterns hidden in data. An Ordered Logit model to predict the gear based on exploring kinetic and internal engine variables, that are influenced by driver’s driving style, is developed. Preliminary results highlig...