Optimal Battery Sizing and Stops’ Allocation for Electrified Fleets Using Data-Driven Driving Cycles: A Case Study for the City of Cairo

Abstract

Electrification of vehicular drivelines has been receiving increasing attention from researchers and governments. Despite the potential of electrified powertrains to improve propulsion efficiency and reduce environmental degradation, limited driving range, long recharging times, and short batteries’ lifetime are still major challenges of electromobility. Besides, the uncertainty of rapidly changing driving conditions contributes to the complexity of charge scheduling, driveline sizing, and infrastructural requirements. In this context, providing useful insights into trip conditions beforehand is an essential step to tackle the abovementioned challenges efficiently. This article presents a comprehensive approach for optimal battery sizing and stops’ allocation for electrified fleets using data-driven driving cycles within a case study for the city of Cairo, Egypt. The gathered information about commuted trips has been analyzed to reconstruct representative driving cycles. Generated speed profiles have been implemented for optimal battery sizing and stops’ allocation, achieving minimal energy consumption, dwell times, and battery degradation. The comparative evaluation of achieved results reveals a significant potential of route-oriented driveline sizing to improve the energy efficiency, mitigate the degradation rate of the batteries, and reduce dwell times compared to the conventional solution.