Hello, I am an engineer/researcher in energy storage technology, with a focus on control and machine learning. My previous work was a good mix of software, system, and hardware.
Check out my resumé and portfolio below
A neural network to estimate pack state of charge (SOC) during charging, deployed on a embedded controller. Onboard vehicle testings show promising results (< 3%).
A new data-driven method to detect battery thermal anomaly at the early stage, based on shape-similarity. Robust to data loss, pack configurations and battery aging.
We have developed a data platform for battery data monitor, analyzing and machine learning.
A high accuracy (<5%) battery state of health estimation method based on the differential voltage (DVA) and incremental capacity analysis (ICA) for electric vehicles at various temperatures.
Design and implemented a centeral pattern generator on FPGA !
LVTRC is a LabVIEW based data acquisition system, with a complete software and hardware solution. The project is sponsored by Turbomachinery Research Consortium. Notable features includes temporal-frequency signal analysis, ML-based machinery diagnosis etc.
A energy storage flywheel with doubled energy density (100 Kwh, 140k cycles). See the flywheel being magleved !