Abstract
The driving cycle is a critical factor in measuring fuel consumption and exhaust emissions. Because vehicle exhaust emissions from road transport are the primary contributors to emissions around the world, so the study of the driving cycle is a vital way to solve the difficulties of environmental pollution. This paper presents a new real-world driving cycle for Nasiriyah, Iraq. A simple electronic device is designed to build the driving cycle after collecting speed data; the system consists of Arduino and a Global Positioning System (GPS) sensor connected to a computer. The technique involves producing micro-trips extracted from real-world driving. Using the K-means clustering method, the Statistical Package for the Social Sciences (SPSS) was used to design this driving cycle. The built driving cycle has a 1568 s speed time series, with an average velocity of 26.7 km/h and a distance of 11.64 km, according to the results. The effectiveness and accuracy of the proposed method were verified when the drive cycle was compared to other types of driving cycles. These results findings strongly support the use of hybrid electric vehicles (HEVs) in Nasiriyah city.
Keywords
driving cycle
Exhaust emission
fuel consumption
K-means Clustering
Micro-trip
SPSS
Statistical method