Saehong Park

Reinforcement Learning-based Fast Charging Control Strategy for Li-ion Batteries

Michael Whitmeyer, Won Tae Joe, Scott Moura, 2020, 2020 IEEE Conference on Control Technology and Applications (CCTA).

A framework for baseline load estimation in demand response: Data mining approach

Hongseok Kim, Seunghyoung Ryu, Yohwan Choi, 2014, 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm).

Distributionally Robust Surrogate Optimal Control for Large-Scale Dynamical Systems

Scott J. Moura, Hyoung Jun Ahn, Geumbee Kim, 2020, 2020 American Control Conference (ACC).

Data-Driven Baseline Estimation of Residential Buildings for Demand Response

Hongseok Kim, Seunghyoung Ryu, Yohwan Choi, 2015 .

Hybrid electrochemical modeling with recurrent neural networks for li-ion batteries

Dong Zhang, Scott J. Moura, Saehong Park, 2017, 2017 American Control Conference (ACC).

Optimal Control of Battery Fast Charging Based-on Pontryagin’s Minimum Principle

Hyoung Jun Ahn, Scott Moura, Claire Tomlin, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Optimal Input Design for Parameter Identification in an Electrochemical Li-ion Battery Model

Scott Moura, Reinhardt Klein, Saehong Park, 2018, 2018 Annual American Control Conference (ACC).

Distributionally Robust Surrogate Optimal Control for High-Dimensional Systems pdf

Scott Moura, Saehong Park, Aaron Kandel, 2021, ArXiv.

Estimation of Cyclable Lithium for Li-ion Battery State-of-Health Monitoring

Scott J. Moura, Reinhardt Klein, Saehong Park, 2021, 2021 American Control Conference (ACC).

Optimal Experimental Design for Parameterization of an Electrochemical Lithium-Ion Battery Model

Scott J. Moura, Reinhardt Klein, Saehong Park, 2018 .

Efficient thermal management of Li-ion batteries with a passive interfacial thermal regulator based on a shape memory alloy

Jian Li, Scott Moura, Saehong Park, 2018, Nature Energy.