An Adaptable Framework For Strategic Optimal Planning For EV Charging Technologies

Abstract

A Doctor of Philosophy Dissertation in Engineering Systems Management by Sarah Mahmoud Atef Hosny Kandil entitled, “An Adaptable Framework for Strategic Optimal Planning for EV Charging Technologies”, submitted in April 2025. Dissertation advisor is Dr. Akmal Abdelfatah and dissertation co-advisor is Dr. Maher Azzouz. Soft copy is available (Dissertation, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).This thesis presents a comprehensive planning framework designed for large-scale highway networks, aiming to strategically allocate various electric vehicle (EV) charging technologies, including Fast Charging (FC), Battery Swapping Stations (BSS), and Wireless Charging Lanes (WCL), alongside renewable energy resources. This adaptable and scalable framework facilitates the deployment of charging technologies to extend the driving range of EVs with minimal downtime. The research adopts a multidisciplinary approach that combines dynamic traffic simulations and electrical grid optimization. This integration ensures the efficient placement and operation of charging infrastructures, effectively minimizing the waiting time for EV users and maintaining traffic flow and grid functionality at minimal costs. A critical finding is that in high congestion and penetration scenarios, EV load can exceed typical demands by up to 36%, highlighting the significance of EV future demands. Moreover, FCS and BSS can fully satisfy the charging demand. However, BSS incurs higher costs at increased penetration and congestion levels but offers significantly reduced waiting times compared to FC. Conversely, WCL alone fails to meet over 30% of vehicle charging needs, illustrating its limitations as a standalone option and emphasizing the need for its integration with other technologies. Strategically combining FC, BSS, and WCL offers the best balance of cost, service level, and load management. This combination achieves a cost reduction of 13.53% compared to the combined use of BSS and WCL and 2.2% compared to BSS alone. It also enhances service levels by 51.61% compared to FC alone and reduces peak load by 16.31% compared to FC alone, demonstrating a balanced approach that optimizes infrastructure efficiency and responsiveness. The integrated use of these technologies ensures a more equitable distribution of load across the grid, presenting a robust solution for managing the growing demands of EV charging in diverse traffic and congestion scenarios. Additionally, the framework validates the suitability of highway and transmission line settings for robust EV infrastructure deployment. It lays the foundation for future research and development in smart transportation networks, emphasizing the need for an integrated approach to support sustainable energy and transportation systems.College of EngineeringDepartment of Industrial EngineeringPhD in Engineering - Engineering Systems Management (PhD-ESM