Electric trucks (ETs) offer a promising pathway for decarbonizing road freight transport, yet their integration into logistics company fleets presents significant challenges. Fleet managers must navigate complex trade-offs between investments in electric trucks (ETs) and conventional diesel trucks (DTs), assess the operational impacts of shifting fleet compositions, and plan strategically for depot charging infrastructure.
To support this decision-making, researchers introduce a mixed-integer programming model designed to optimize truck purchasing and retirement decisions over a multi-year horizon. A key innovation of the model is its explicit inclusion of depot charging infrastructure investments and the use of public fast charging for long-haul operations.
The researchers utilize this model to investigate the technical, economic, and organizational factors influencing the adoption of ET in heavy-duty fleets. The findings indicate that fleets incorporating ETs can achieve lower total costs compared to those relying solely on DTs. However, realizing these savings depends on access to sufficient capital for high upfront investments and upgrades to the depot’s electricity grid connection.
The adoption trajectory for ETs also varies significantly with customer geography. When ETs can rely exclusively on depot charging, rapid adoption is economically optimal. In contrast, dependence on public fast charging slows down adoption and introduces uncertainty. High costs associated with public fast-charging services remain a significant barrier, limiting the broader deployment of electric vehicles despite ongoing reductions in vehicle acquisition costs.