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Multi-Agent Learning-based Control of Hybrid Battery Management Systems

Busch, Bastian (2021) Multi-Agent Learning-based Control of Hybrid Battery Management Systems. Master's, Technische Universität München.

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Abstract

The proliferation of electrically powered vehicles has not proceeded as quickly as climate pacts aiming to reduce greenhouse gas emission would require it. Alongside improvements in battery technology, optimizing the management of battery systems can empower the switch from internal combustion engines to electric vehicles. As the performance of battery systems can be limited by the weakest individual battery cells, maintaining balance among the cells is a primary goal of battery management systems. The smart hybrid battery system developed at the Institute of System Dynamics and Control at the German Aerospace Center (DLR) augments a traditional battery storage system with dedicated power converters and supercapacitors, allowing it to redistribute energy between battery cells. Through intelligent control, this system is capable of balancing cell states efficiently and protecting weak cells from aggressive use. In this thesis, the task of generating the setpoints of the balancing currents is solved by a decentralized multi-agent reinforcement learning approach. Each of the battery modules is afforded a separate control element, which is aimed at providing scalability to battery systems of realistic sizes.

Item URL in elib:https://elib.dlr.de/142290/
Document Type:Thesis (Master's)
Title:Multi-Agent Learning-based Control of Hybrid Battery Management Systems
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Busch, BastianUNSPECIFIEDUNSPECIFIED
Date:31 March 2021
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:83
Status:Published
Keywords:Reinforcement learning, deep learning, artifical intelligence, neural network, control, battery, battery management, battery storage, system, hybrid battery, supercapacitor
Institution:Technische Universität München
Department:Department of Informatics
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Road Transport
DLR - Research area:Transport
DLR - Program:V ST Straßenverkehr
DLR - Research theme (Project):V - NGC Antriebssystem und Energiemanagement
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of System Dynamics and Control > Vehicle System Dynamics
Deposited By: Mirwald, Jonas
Deposited On:17 May 2021 15:44
Last Modified:17 May 2021 15:44

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