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Real-Time Optimal Energy Management of Multimode...
Journal article

Real-Time Optimal Energy Management of Multimode Hybrid Electric Powertrain With Online Trainable Asynchronous Advantage Actor–Critic Algorithm

Abstract

An online updating framework of an energy management system (EMS) for a multimode hybrid electric powertrain is proposed via cooperation between the asynchronous advantage actor–critic (A3C)-based deep reinforcement learning (DRL) agent and the Markov chain model (MCM). In the overall framework, the DRL agent periodically updates the energy management policy. The MCM expedites the policy update process by generating plenty of probable future …

Authors

Biswas A; Anselma PG; Emadi A

Journal

IEEE Transactions on Transportation Electrification, Vol. 8, No. 2, pp. 2676–2694

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

June 1, 2022

DOI

10.1109/tte.2021.3138330

ISSN

2577-4212

Labels

Sustainable Development Goals (SDG)