Promoting the use of public transportation may play a key role in achieving zero-carbon emissions and sustainable development goals. Due to the ability to cut down greenhouse gas emissions, electric buses have emerged as promising alternatives to pave the way for shaping sustainable cities. Therefore, it is essential to evaluate the performance of electric buses in terms of their energy consumption, design optimization, and other management, which in turn depends on factors such as type and geometric conditions of the road, driver behavior, etc. The driving cycle is a time series of vehicle speeds that reflects the typical driving pattern of any given region/city. To the best of author’s knowledge, no studies have developed driving cycles for Electric buses plying on urban and rural roads in India. For this, on-road trajectory data of approximately 650 km data were collected from electric buses using a VBOX sport device at a frequency of 10 Hz. Collected data were analyzed to characterize the specific driving patterns and segmented the entire data into micro-trips. Then, Patna Electric Bus Driving Cycle (PEBDC) was developed by selecting the representative micro-trips using kmeans clustering technique. The developed driving cycle was also compared with international driving cycles, and it was observed that PEBDC is considerably different from selected international bus driving cycles. In comparison with other driving cycles developed for Indian cities, it was observed that buses driving in Patna exhibit relatively lower average speeds and percentage of time involved in acceleration and deceleration activities. The driving cycle developed in this study can be used to compute energy consumption, electricity grid analysis, and economic and life cycle analysis of electric buses.
Development of Driving Cycles for Electric Buses in Patna, India
2023-06-14
1073327 byte
Conference paper
Electronic Resource
English
Multimode Energy Management for Plug-In Hybrid Electric Buses Based on Driving Cycles Prediction
Online Contents | 2016
|