Multi-Phased Integration of Charging Infrastructure and Shared Charging Networks

Sammanfattning

The transition to electric heavy-duty vehicles presents significant challenges, with many studies identifying the lack of charging infrastructure as the key factor restricting the adoption of battery electric trucks. This thesis develops an mixed integer program optimization framework for identifying optimal charging station locations based on empirical truck route data, focusing on incremental deployment strategies to accommodate for limitations in the initial development phase. The optimization problem is structured to maximize the utility of available charging infrastructure stepwise, and integrate pre-existing charging stations into each expansion process. Additionally, the model is extended into a multi-company co-optimization setting, for potential shared charging locations, with the incentive to reduce total investments through joint ventures. Results show that strategically placed charging stations can significantly improve electrification rates, with shared infrastructure yielding additional benefits. Committing to larger installations in each expansion phase leads to more effectively placed sites across the total charging network over time. Deciding on any particular strategy is a matter of balancing immediate feasibility with overall scalability to maximize efficiency and profitability. The findings provide actionable insights into freight charging infrastructure integration based on optimal charging station placement, and provide comparative evaluation of short- and long-term consequences between different electrification strategies.