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Optimize Performance of Second-Life Batteries in an Electric Vehicle Charging Network
Author(s) -
Kaila Neigum,
Zhanle Wang,
Yili Tang,
Saman Shahrokhi
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3621351
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Electric vehicles (EVs) have become a hot topic driven by increasing climate change concerns. This method for decarbonizing transportation, although appealing, is accompanied by several challenges. The increased electricity demand required for EV charging may be seen as a transfer of emissions from one sector to another. The accumulation of EV batteries, which must eventually be retired from the EV, is another worry with this exponential growth. The objective of the study presented in this paper is to provide a contribution to addressing these concerns. The power and energy demands of driving are high; thus, the EV’s battery must be retired from the car once its state of health (SOH) cannot provide these demands. These retired batteries do retain some usable capacity and may be useful under less stringent conditions, introducing the concept of second-life batteries (SLBs). This study explores the use of SLBs for peak demand reduction in an EV charging station. This charging network will be modelled under a fixed-priced structure using the utility pricing scheme in Saskatchewan, Canada. With battery degradation being a presumption of SLBs, continued cycling and calendar degradation of the SLB will be integrated into the battery model. The multi-objective optimization framework minimizes the charging station’s operational costs to achieve maximum benefits from the energy storage system (ESS) while extending its remaining useful life (RUL). This is consummated by balancing battery degradation per day with the costs associated with peak demand. Optimal control of the ESS occurred when battery degradation was included as a cost in the objective function, resulting in an extended RUL of the ESS. The SLB was further compared to a new ESS using the same multi-objective approach. The new ESS generated lower operational costs and greater lifetime savings. The SLB had lower operational costs when compared to a charging station without ESS. In addition, the SLB resulted in significant savings at half the investment cost and had a higher internal rate of return (IRR) than the new ESS, reflecting a lower investment risk. This study provides charging station owners with a framework for assessing the feasibility of using SLBs in their respective charging stations.

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