The success of battery electric trucks in logistics depends on efficient and cost-effective charging practices at logistic terminals during loading, unloading, and overnight parking. However, as fleets of electric trucks expand, the charging process at terminals can become complex. Maintaining transport efficiency within the electric grid’s limits and

available chargers is crucial. Challenges arise from weak terminal grid connections, necessitating a need to manage peak power usage. The aim of this master’s thesis is to develop optimization algorithms for fleet charging at terminals. It involves modeling and evaluating algorithm(s) against strategies and exploring potential implementation within existing transport systems. Delving into various areas, such as energy integration (including photovoltaic & battery energy storage systems), system integration of charg- ing stations, terminal layout and implementation of algorithm(s). This thesis work will contribute to the innovation project ”Local Energy Systems for Electrified Logistic Applications” (LEELA). Modeling will rely on empirical research, industry data and research from companies involved within the project LEELA. The simulations from the algorithms showed the importance of evaluating viable choices for implementation, such as integrated charging systems, photovoltaic systems, battery energy storage systems and megawatt charging systems.