Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
3 results
Search Results
Now showing 1 - 3 of 3
Article Citation - WoS: 1Citation - Scopus: 2Investigation of the Effects of Various Parameters on Wireless Power Transfer Efficiency(Elsevier Gmbh, 2025) Yilmaz, Mert; Cetkin, Erdal; Akca, HakanElectric vehicles have dominated the automotive market, especially in recent years. However, the charging problem that stresses drivers continues. Although conductive charging is an established technology, it still needs to meet user expectations fully. On the other hand, wireless charging technology attracts users' attention with dynamic charging features. Although this technology improves daily, efficiency is not at the desired level. In this study, a wireless power transfer system was designed for electric vehicles, and the factors affecting the charging efficiency were investigated. This system consists of an inverter, a compensation system, and a load. The efficiency of the system according to cable type, air gap, cooling, and pulse-width modulation parameters was observed through 40 experiments, each lasting 20 min. In addition to efficiency, the frequency behavior was also investigated. Experimental results were compared with models designed in MATLAB and ANSYS software. The average errors between the experimental and simulation results are 1.75, 2.03, 1.85, 1.58, and 2.00% for air gaps of 19-20, 55-56, 91-92, 127-128, and 145-146 mm, respectively. Power was transferred wirelessly with a minimum efficiency of 59.25% at a 145 mm air gap and a maximum efficiency of 85.74% at a 56 mm air gap in 300 W tests.Article Citation - WoS: 1Citation - Scopus: 1High Accuracy and Applicability Battery Aging Models for Electric Vehicle Applications(Electrochemical Soc inc, 2025) Yarimca, Gulsah; Jensen, Anders Christian Solberg; Cetkin, ErdalBatteries have gained significant attention due to their numerous advantages in applications such as electric vehicles. One of the factors limiting industry adoption is the aging of batteries. The characteristics of battery aging vary depending on many factors such as battery type, electrochemical reactions and operating conditions. Here we document the comparison of semi-empirical aging models (SEM), highlighting limitations and challenges. In addition, four SEMs are proposed. The usability and compatibility of these models are evaluated using experimental data from various sources including the Horizon 2020 Helios Project. The optimized parameters of each model are documented via linear regression and genetic algorithms. The results show that the genetic algorithm approach provides higher accuracy in comparison to the linear regression. The documented SEMs reveal better prediction performance than the literature of calendar obsolescence with SEM-3 and 7 performing particularly well in predicting capacity loss for the Helios dataset with low errors, i.e. 0.43 and 0.79 RMSE, respectively. The range of RMSE values for model predictions across all the datasets ranges from 0.196 to 3.903. This study aims to document the accuracy of SEMs both from the literature and proposed in the paper relative to battery ageing data from distinct sources.Review Citation - WoS: 13Citation - Scopus: 18Review of Cell Level Battery (calendar and Cycling) Aging Models: Electric Vehicles(Mdpi, 2024) Yarimca, Gulsah; Cetkin, ErdalElectrochemical battery cells have been a focus of attention due to their numerous advantages in distinct applications recently, such as electric vehicles. A limiting factor for adaptation by the industry is related to the aging of batteries over time. Characteristics of battery aging vary depending on many factors such as battery type, electrochemical reactions, and operation conditions. Aging could be considered in two sections according to its type: calendar and cycling. We examine the stress factors affecting these two types of aging in detail under subheadings and review the battery aging literature with a comprehensive approach. This article presents a review of empirical and semi-empirical modeling techniques and aging studies, focusing on the trends observed between different studies and highlighting the limitations and challenges of the various models.