A Deep Reinforcement Learning Framework for Fast Charging of Li-Ion Batteries-Reference-Cited by-同舟云学术

A Deep Reinforcement Learning Framework for Fast Charging of Li-Ion Batteries

Published:2022-06 Issue:2 Volume:8 Page:2770-2784
ISSN:2332-7782
Container-title:IEEE Transactions on Transportation Electrification
language:
Short-container-title:IEEE Trans. Transp. Electrific.

Author:

Park Saehong¹^ORCID,Pozzi Andrea²^ORCID,Whitmeyer Michael¹,Perez Hector¹^ORCID,Kandel Aaron¹,Kim Geumbee³,Choi Yohwan³,Joe Won Tae³,Raimondo Davide M.²^ORCID,Moura Scott¹^ORCID

Affiliation:

1. Energy, Controls and Applications Laboratory (eCAL), University of California at Berkeley, Berkeley, CA, USA

2. Department of Industrial and Information Engineering, University of Pavia, Pavia, Italy

3. BMS Advanced SW Project Team, LG Chem, Daejeon, South Korea

Funder

LG Chem Battery Innovative Contest

Italian Ministry for Research in the Framework of the 2017 Program for Research Projects of National Interest

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Transportation,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6687316/9761278/09668843.pdf?arnumber=9668843

Reference49 articles.

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4. Mathematical Modeling of Lithium Batteries

5. Deterministic policy gradient algorithms;silver;Proc Int Conf Mach Learn,2014

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