Fuzzy-Based Model Predictive Control for Bidirectional Charging of EV: An Adaptive Weighting Factor Algorithm

He, T; Wu, M; Lu, DDC; Wang, S; Zhu, J

Fuzzy-Based Model Predictive Control for Bidirectional Charging of EV: An Adaptive Weighting Factor Algorithm

He, T Wu, M Lu, DDC Wang, S Zhu, J

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Conference Proceeding
Citation:: 2023 International Future Energy Electronics Conference, IFEEC 2023, 2023, 00, pp. 284-287
Issue Date:: 2023-01-01

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Field	Value	Language
dc.contributor.author	He, T
dc.contributor.author	Wu, M
dc.contributor.author	Lu, DDC
dc.contributor.author	Wang, S
dc.contributor.author	Zhu, J
dc.date	2023-11-20
dc.date.accessioned	2024-05-29T07:29:21Z
dc.date.available	2024-05-29T07:29:21Z
dc.date.issued	2023-01-01
dc.identifier.citation	2023 International Future Energy Electronics Conference, IFEEC 2023, 2023, 00, pp. 284-287
dc.identifier.isbn	9798350339888
dc.identifier.uri	http://hdl.handle.net/10453/179327
dc.description.abstract	Model predictive control strategy is an advanced control algorithm for bidirectional active and reactive power flow in electric vehicles. However, tuning the weighting factor is a time-consuming process and its value is constant for various working conditions. To solve this problem, fuzzy control is applied to generate an adaptive weighting factor to meet all unexpected requirements. A two-stage bidirectional charger is built in Matlab/Simulink with the proposed fuzzy model predictive control. Simulation results show that dynamic performance can be achieved in the proposed method. The total harmonic distortion of the grid current is limited to 5%. The weighting factor can be adjusted online according to different demands. No tuning procedure of the weighting factor is required.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	2023 International Future Energy Electronics Conference, IFEEC 2023
dc.relation.ispartof	2023 IEEE International Future Energy Electronics Conference (IFEEC)
dc.relation.isbasedon	10.1109/IFEEC58486.2023.10458447
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Fuzzy-Based Model Predictive Control for Bidirectional Charging of EV: An Adaptive Weighting Factor Algorithm
dc.type	Conference Proceeding
utslib.citation.volume	00
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	closed_access	*
dc.date.updated	2024-05-29T07:29:19Z
pubs.finish-date	2023-11-23
pubs.publication-status	Published
pubs.start-date	2023-11-20
pubs.volume	00

Abstract:

Model predictive control strategy is an advanced control algorithm for bidirectional active and reactive power flow in electric vehicles. However, tuning the weighting factor is a time-consuming process and its value is constant for various working conditions. To solve this problem, fuzzy control is applied to generate an adaptive weighting factor to meet all unexpected requirements. A two-stage bidirectional charger is built in Matlab/Simulink with the proposed fuzzy model predictive control. Simulation results show that dynamic performance can be achieved in the proposed method. The total harmonic distortion of the grid current is limited to 5%. The weighting factor can be adjusted online according to different demands. No tuning procedure of the weighting factor is required.

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http://hdl.handle.net/10453/179327