no code implementations • 4 Jul 2024 • Rahul Bhadani, Satyaki Banik, Hao Tu, Srdjan Lukic, Gabor Karsai
This paper presents a faster method for simulating the electromagnetic transient response of microgrid components using SystemC-AMS.
no code implementations • 30 May 2024 • Hao Tu, Xinfan Lin, Yebin Wang, Huazhen Fang
Essential to various practical applications of lithium-ion batteries is the availability of accurate equivalent circuit models.
no code implementations • 23 Apr 2024 • Hao Tu, Manashita Borah, Scott Moura, Yebin Wang, Huazhen Fang
In this paper, we present the first study on predicting the remaining energy of a battery cell undergoing discharge over wide current ranges from low to high C-rates.
no code implementations • 5 Apr 2024 • Zehui Lu, Hao Tu, Huazhen Fang, Yebin Wang, Shaoshuai Mou
A state-feedback model predictive control algorithm is then developed for optimal fast charging and active thermal management.
no code implementations • 8 Nov 2022 • Hao Tu, Hui Yu, Srdjan Lukic
We derive a closed-form stability criterion that can be used to evaluate the impact of virtual inertia on the system stability, and demonstrate that, given a set of system parameters, the stability of a DC grid powering CPLs can be improved for a range of virtual inertia designs.
no code implementations • 24 Dec 2021 • Hao Tu, Scott Moura, Yebin Wang, Huazhen Fang
This paper proposes two new frameworks to integrate physics-based models with machine learning to achieve high-precision modeling for LiBs.
no code implementations • 22 Mar 2021 • Hao Tu, Scott Moura, Huazhen Fang
Mathematical modeling of lithium-ion batteries (LiBs) is a central challenge in advanced battery management.