Electrochemical Energy Research from Modeling Laboratory at ELENTEK
Our research group, led by Assoc. Prof. Dr. Uğur ÖZVEREN, will be participating in the II. Electrochemical Energy Technologies Symposium at Gazi University in Ankara on 27–28 November. We are proud to present three full papers that bring together electrochemical energy technologies and machine learning–based modeling across photovoltaics, batteries and fuel cells.
PhD student Dicle EREN will present a data-driven ridge regression model for predicting the maximum power output of photovoltaic modules. MSc student Sahragul CHARYYEVA will share a Random Forest analysis using Ragone parameters and RC-equivalent circuit data to compare lithium and alternative battery systems. BSc student İdil Sena BAYRAK will present a gradient boosting approach to predict cell voltage and efficiency in fuel cell systems. All three studies are supervised by Assoc. Prof. Dr. Uğur ÖZVEREN, who serves as the advisor of the students and the principal investigator leading these projects.
These contributions reflect our lab’s core vision under the guidance of Doç. Dr. Uğur ÖZVEREN: combining strong physical and electrochemical insight with state-of-the-art AI tools, while empowering students at every academic level to take ownership of ambitious research problems in clean energy. If you will be at the symposium in Ankara and are interested in PV modeling, battery analytics, fuel cell optimization, or data-driven energy technologies, we would be happy to connect, exchange ideas, and explore potential collaborations.
