Research Article
Charging Strategies, Charger Location, Battery Degradation, and RES Integration for Electric Freight Vehicles Availability: A Systematic Review
@INPROCEEDINGS{10.1007/978-3-032-38705-9_1, author={Ricardo Carvajal-Arango and Gilberto Osorio-G\^{o}mez}, title={Charging Strategies, Charger Location, Battery Degradation, and RES Integration for Electric Freight Vehicles Availability: A Systematic Review}, proceedings={Intelligent Transport Systems. 9th EAI International Conference, INTSYS 2025, Marietta, GA, USA, December 10, 2025, Proceedings}, proceedings_a={INTSYS}, year={2026}, month={10}, keywords={Optimization Charging Strategies Electric Freight Vehicles (EFV) Electric Trucks Charger Location RES Integration Trade-offs Battery Degradation}, doi={10.1007/978-3-032-38705-9_1} }- Ricardo Carvajal-Arango
Gilberto Osorio-Gómez
Year: 2026
Charging Strategies, Charger Location, Battery Degradation, and RES Integration for Electric Freight Vehicles Availability: A Systematic Review
INTSYS
Springer
DOI: 10.1007/978-3-032-38705-9_1
Abstract
The paper presents a systematic mapping review of computational models, charging strategies, charger location, battery degradation, and integration of renewable energy for electric freight vehicles (EFVs), based on 87 articles from 2015 to 2025. The study finds that mathematical modeling, especially mixed-integer linear programming, is prevalent, with growing interest in simulation and data-driven methods. Charging strategies balance cost, efficiency, and battery health, while optimizing the location of the charger considers spatial planning and network performance. Battery degradation is identified as a significant but underexplored factor in operational costs and fleet availability. The shift towards detailed techno-economic analyses in the integration of renewable energy sources (RES) highlights potential reductions in carbon emissions and grid dependency, but poses challenges in scheduling and reliability. The paper identifies research gaps, suggesting the need for integrated models that address charging logistics, battery management, and renewable variability under uncertainty. Conclusions by advocating for interdisciplinary methods, advanced analytics, and empirical data to support sustainable EFV operations and decarbonization goals.