Congratulations to Vijay on his first publication with our lab! Our latest paper, recently published in Applications in Energy and Combustion Science, successfully utilizes a bagged ensemble of ANN to predict the laminar flame speed of gasoline surrogate fuels and syngas blends. This not only highlights Vijay's excellent work but also marks our group's very first achievement in integrating machine learning techniques with fundamental combustion modeling.
https://www.sciencedirect.com/science/article/pii/S2666352X25000718
We are excited to share our latest research publication, "Electro-Thermal Modeling and Parameter Identification of an EV Battery Pack Using Drive Cycle Data," recently published in the journal Batteries. This paper leverages real-world drive cycle data to improve the accuracy of electro-thermal models for electric vehicles. This work provides valuable insights for developing safer and more efficient battery management systems for future mobility.