IIUM Gombak Driving Cycle for Motorcycle

One such method can be used to assess the fuel rate for an internal combustion engine (ICE) vehicle within a specific area is to develop the driving cycle. For a full-battery electric vehicle (BEV), driving cycle is an important instrument for the evaluation of vehicle characteristics like energy consumption and range estimation. This research aims to experience the actual on-road driving of the selected routes and apply proper methods to construct a significant driving cycle that closely represents local driving patterns to evaluate the fuel rate of certain vehicles within the area. The study area was IIUM Gombak, and speed-time data was collected among selected local routes using a motorcycle. Two machine learning methods were used to construct the driving cycle which are k-means clustering and Markov chain. Results showed that the former method was better suited for the study area as it considered road geography as a significant aspect of traffic flow, where a fuel consumption of 4.50 L per 100 km was required. The study highlighted the importance of determining major aspects of traffic flow such as, but not limited to, road geography, work zones, and traffic volume, when choosing the method outcomes for a representative driving cycle.