Pedrosa et al 2016a - Revision history

Scipediacontent at 15:21, 21 January 2021

2021-01-21T15:21:11Z

Scipediacontent: Scipediacontent moved page Draft Content 574349314 to Pedrosa et al 2016a

2020-10-14T10:56:11Z

Scipediacontent moved page Draft Content 574349314 to Pedrosa et al 2016a

Scipediacontent: Created page with " == Abstract == Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and pl..."

2020-10-14T10:56:09Z

Created page with " == Abstract == Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and pl..."

New page

== Abstract ==

Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and plug-in hybrid electric vehicles. Since these vehicles are parked when the batteries are being charged, it is possible to use the traction power converter as on-board charger, also allowing to reduce weight, volume and costs of components in the vehicle. In this context, this paper presents a model predictive control algorithm for an on-board fast battery charging that uses the traction power converter of an electric vehicle. Simulation results and system implementation are depicted, and finally, are presented some experimental results obtained with the proposed control system. (undefined) info:eu-repo/semantics/publishedVersion

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_574349314-beopen244-7500-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/1822/48149 http://hdl.handle.net/1822/48149]

* [http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf]

← Older revision		Revision as of 15:21, 21 January 2021
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	Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and plug-in hybrid electric vehicles. Since these vehicles are parked when the batteries are being charged, it is possible to use the traction power converter as on-board charger, also allowing to reduce weight, volume and costs of components in the vehicle. In this context, this paper presents a model predictive control algorithm for an on-board fast battery charging that uses the traction power converter of an electric vehicle. Simulation results and system implementation are depicted, and finally, are presented some experimental results obtained with the proposed control system. (undefined) info:eu-repo/semantics/publishedVersion		Under the necessities of reducing emissions and air pollution, and also for increasing fuel economy, automotive companies have been developing electric and plug-in hybrid electric vehicles. Since these vehicles are parked when the batteries are being charged, it is possible to use the traction power converter as on-board charger, also allowing to reduce weight, volume and costs of components in the vehicle. In this context, this paper presents a model predictive control algorithm for an on-board fast battery charging that uses the traction power converter of an electric vehicle. Simulation results and system implementation are depicted, and finally, are presented some experimental results obtained with the proposed control system. (undefined) info:eu-repo/semantics/publishedVersion
−
−	~~Document type: Part of book or chapter of book~~
−
−	~~== Full document ==~~
−	~~<pdf>Media:Draft_Content_574349314-beopen244-7500-document.pdf</pdf>~~


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	* [http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf]		* [http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf http://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf]
		+
		+	* [http://link.springer.com/content/pdf/10.1007/978-3-319-43671-5_57 http://link.springer.com/content/pdf/10.1007/978-3-319-43671-5_57],
		+	: [http://dx.doi.org/10.1007/978-3-319-43671-5_57 http://dx.doi.org/10.1007/978-3-319-43671-5_57] under the license http://www.springer.com/tdm
		+
		+	* [https://link.springer.com/chapter/10.1007/978-3-319-43671-5_57 https://link.springer.com/chapter/10.1007/978-3-319-43671-5_57],
		+	: [https://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf https://repositorium.sdum.uminho.pt/bitstream/1822/48149/1/CONTROLO_2016_MPC_EV_fast.pdf],
		+	: [https://www.scipedia.com/public/Pedrosa_et_al_2016a https://www.scipedia.com/public/Pedrosa_et_al_2016a],
		+	: [http://repositorium.sdum.uminho.pt/handle/1822/48149 http://repositorium.sdum.uminho.pt/handle/1822/48149],
		+	: [https://rd.springer.com/chapter/10.1007/978-3-319-43671-5_57 https://rd.springer.com/chapter/10.1007/978-3-319-43671-5_57],
		+	: [https://academic.microsoft.com/#/detail/2507668390 https://academic.microsoft.com/#/detail/2507668390]

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