An Optimization Model for Two-Way EV Battery-Swapping: Balancing Revenue and User Satisfaction

Electric vehicle (EV) battery-swapping is a timesaving alternative to conventional charging, but optimizing profitability and user satisfaction remains challenging. This paper presents a novel two-way EV battery-swapping model, where vehicles can act both as providers and customers. The model adjusts provider incentives and customer payments based on the State of Charge (SoC) and State of Health (SoH) of the battery. By utilizing EVs as providers, the model increases battery availability and reduces dependence on station-based charging. Key decision variables are optimized using an interiorpoint algorithm to maximize revenue while maintaining user satisfaction. The proposed model enhances the efficiency and scalability of EV battery-swapping stations, contributing to a green and economically viable transport network.

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Publication Details

Published
2025-06-18
DOI
https://doi.org/10.1109/itec63604.2025.11097930
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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article

An Optimization Model for Two-Way EV Battery-Swapping: Balancing Revenue and User Satisfaction

Ahmed H. Osman, Ahmed M. Benaya, Mohamed S. Hassan, Rami Zaino
1 citations
Electric Vehicles and Infrastructure
0.73
article

An Optimization Model for Two-Way EV Battery-Swapping: Balancing Revenue and User Satisfaction

Ahmed H. Osman, Ahmed M. Benaya, Mohamed S. Hassan, Rami Zaino
article en
1 citations

Abstract

Electric vehicle (EV) battery-swapping is a timesaving alternative to conventional charging, but optimizing profitability and user satisfaction remains challenging. This paper presents a novel two-way EV battery-swapping model, where vehicles can act both as providers and customers. The model adjusts provider incentives and customer payments based on the State of Charge (SoC) and State of Health (SoH) of the battery. By utilizing EVs as providers, the model increases battery availability and reduces dependence on station-based charging. Key decision variables are optimized using an interiorpoint algorithm to maximize revenue while maintaining user satisfaction. The proposed model enhances the efficiency and scalability of EV battery-swapping stations, contributing to a green and economically viable transport network.

American University of Sharjah (AE)
Openalex Percentile: Top 25%
Electric Vehicles and Infrastructure
0.73
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