Planning Charging Infrastructure for Electric Freight Corridors

With the rapid development of electric vehicles, electric freight transportation is gradually increasing. However, the construction of charging infrastructure on expressways has lagged far behind, becoming a key bottleneck in the development of new energy freight transportation. This paper proposes an optimization system for the layout of charging stations in the rest areas of the Beijing–Hong Kong–Macao Expressway, based on freight logistics information. The system combines the Flow Capturing Location-Allocation Model (FCLM) with an improved genetic algorithm to dynamically analyze traffic flow, service area distribution, and charging demand, thereby achieving an optimized layout of charging stations. By simulating traffic flow variations under different scenarios, the study analyzes the spatiotemporal distribution of charging demand and optimizes the selection of charging station sites and charger allocation. Experimental results demonstrate that the proposed optimization method effectively enhances the coverage and service quality of charging stations, meets the charging demands of electric freight vehicles, and ensures that construction costs remain within reasonable limits. This study provides scientific decision support to address the shortage of charging facilities on expressways, promoting the development of green logistics and a low-carbon economy.