An graduated from Beihang University with a Bachelor's degree in Aircraft Propulsion Engineering in 2019. Following the completion of undergraduate studies, An embarked on a career as a technical researcher at a reputable company. An pursued a Master's degree at Beihang University, focusing on the cooling and heat exchange systems within aircraft engines.
An employed entropy analysis to compute and fit multi-modal bleed air structure equations. Proficient in the analysis and modelling of thermophysical phenomena, An adeptly constructed systems of partial differential equations to calculate fitted formulas under specified boundary conditions. An possesses a strong passion for programming and aspires to create a personal gaming project in their spare time.
An's enthusiasm for mathematical analysis and programming led her to join the AAPS CDT, where she aims to establish a comprehensive lithium-ion degradation model. This endeavour aligns with An's aspiration to leave a profound mark in advancing the electrified future.
Lithium-ion batteries (LIB) have become core technology for energy storage and electric vehicle applications due to key advantages like high energy density, long cycle life, and low self-discharge rates. However, they inevitably degrade over time due to irreversible physical and chemical changes, ultimately leading to the end of their usable life. An accurate and comprehensive degradation model would unlock new opportunities for battery use and optimization.
This research will apply a physics-based electrochemical-thermal battery degradation model coupled a data-driven neural network model to predict the State of Health (SOH) and Remaining Useful Life (RUL) of LIBs.
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