Project Summary
Medium‐ and heavy‐duty trucks have lagged behind light‐duty vehicles in decarbonization efforts, necessitating more ambitious goals to reduce their emissions. A major limitation to electrifying the long‐haul segment is the need for large batteries to complete long routes, reducing cargo capacity and increasing ownership costs. Electrification decisions are also influenced by factors such as electricity pricing, investments in and availability of charging infrastructure, vehicle characteristics, and driving patterns. These factors lead to varying charging costs and increased total cost uncertainty, which can hamper fleets’ willingness to adopt battery electric trucks.
This project aims to analyze intra-day truck and cargo activity patterns along with renewable electricity availability and pricing to pinpoint optimal locations for charging infrastructure. The study will integrate a large sample of load/cargo data, a sample of fleet data, wholesale intra-day marginal price electricity data, spatial generation of renewable energy and availability, and other data sources. By analyzing these datasets, the project will generate charging models for different fleet segments, such as long-haul and middle-mile, considering their specific operational patterns and constraints. Additionally, the models will help identify critical hotspots locations for establishing charging stations.
