An ML-Based Fleet Management System for Electric Vehicles

Considering the general trend towards electric mobility and the higher costs of electric vehicle ownership, the popularity of fleet operations of electric vehicles is on the rise. Fleet operators provide car sharing and/or rental and taxi services to customers. However, the major concerns of such operators are the battery health as well as the electric vehicle range, in other words, the distance the car can travel with the given battery charge. The scope covers the design of a management software for efficient deployment of fleet vehicles, taking into account the health of battery packs as well as driver behaviour, the latter of which is determined via machine learning by receiving acceleration patterns of the drivers. Hence, the goal of the fleet management system is to provide significant value addition to fleet owners in terms of economic benefits and ease of management.