The increasing adoption of electric vehicles in the commercial sector is creating opportunities in terms of sustainability as well as cost reduction and climate-friendly transportation. However, the effective planning of vehicle fleets utilizing electric vehicles presents unique challenges due to their limited range and dependency on charging infrastructure. The presented work highlights the necessity of a universal metric for route description, considering the context data, to enhance the usability of electric vehicles in commercial fleets. The proposed metric aims to provide fleet managers and planners with valuable insights to make informed decisions regarding electric vehicle deployment, potential charging infrastructure placement, and operational efficiency. This metric is introduced as a stress rating, which aims to condense context information into the schedule planning. The stress rating should consider various factors such as road elevation, weather conditions, charging station availability, and energy consumption patterns. By integrating these contextual elements, the metric can holistically evaluate routes and assist fleet planners in identifying optimal paths and vehicles, considering range limitations and charging requirements. It allows fleet managers to evaluate routes comprehensively and identify potential challenges that could affect the feasibility of certain powertrain technologies. The stress rating also facilitates data-driven decision-making. It enables fleet managers to analyze historical data on routes, energy consumption, and charging patterns, allowing them to identify trends and patterns that can inform long-term fleet planning and optimization.
Context-Aware Policy for Route Planning and Feasible Vehicle Technologies
2023-10-16
2154888 byte
Conference paper
Electronic Resource
English
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