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http://hdl.handle.net/2080/3635
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DC Field | Value | Language |
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dc.contributor.author | Rath, Abinash | - |
dc.contributor.author | Srungavarapu, Gopalakrishna | - |
dc.date.accessioned | 2022-03-04T05:56:52Z | - |
dc.date.available | 2022-03-04T05:56:52Z | - |
dc.date.issued | 2021-12 | - |
dc.identifier.citation | 10th National power Electronics Conference(NPEC)2021, IIT Bhubaneswar | en_US |
dc.identifier.uri | http://hdl.handle.net/2080/3635 | - |
dc.description | Copyright of this paper is with proceedings publisher | en_US |
dc.description.abstract | he usage of the Li-ion batteries in different applications like UPS, electric vehicles (EVs), and other energy storage devices are growing day by day. A delicate charging system is needed for long battery life which should operate at high power quality. Because of its fast dynamic response, the Direct Power Control (DPC) is an excellent alternative to the ac- dc converter in grid-connected charging systems. Traditional DPC-based charging systems operate in two stages, with a dc-dcbuck converter accurately managing the charging voltage to ensure rapid charging. This work presents a dead beat predictive control strategy that eradicates the dc-dc converter from the conventional system by using a dynamical dc-link voltage reference in the ac-dc converter itself. As the system's hardware requirements are lowered, the overall size, weight, and cost are reduced. MATLAB simulation models have been built for the proposed method and it is further extended to real- time simulation in the RT-LAB environment to ensure that the proposed strategy is feasible | en_US |
dc.subject | Direct power control (DPC) | en_US |
dc.subject | EV Battery Charging | en_US |
dc.subject | Dead Beat Predictive DPC (DB-DPC) | en_US |
dc.subject | Real-time Simulation | en_US |
dc.title | Dead Beat Predictive DPC based Battery Charging System Using Dynamic DC-link Reference | en_US |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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RathA_NPEC-2021.pdf | 945.68 kB | Adobe PDF | View/Open |
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