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description Publicationkeyboard_double_arrow_right Article , Other literature type 2022 FrancePublisher:MDPI AG Mehdi Sellali; Alexandre Ravey; Achour Betka; Abdellah Kouzou; Mohamed Benbouzid; Abdesslem Djerdir; Ralph Kennel; Mohamed Abdelrahem;doi: 10.3390/en15041318
The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key part to enhance optimal power distribution. Indeed, the most recent works are focusing on optimizing hydrogen consumption, without taking into consideration the degradation of embedded energy sources. In order to overcome this lack of knowledge, this paper describes a new health-conscious EMS algorithm based on Model Predictive Control (MPC), which aims to minimize the battery degradation to extend its lifetime. In this proposed algorithm, the health-conscious EMS is normalized in order to address its multi-objective optimization. Then, weighting factors are assigned in the objective function to minimize the selected criteria. Compared to most EMSs based on optimization techniques, this proposed approach does not require any information about the speed profile, which allows it to be used for real-time control of FCHEV. The achieved simulation results show that the proposed approach reduces the economic cost up to 50% for some speed profile, keeping the battery pack in a safe range and significantly reducing energy sources degradation. The proposed health-conscious EMS has been validated experimentally and its online operation ability clearly highlighted on a PEMFC delivery postal vehicle.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/4/1318/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversité de Franche-Comté (UFC): HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15041318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 30 citations 30 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/4/1318/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversité de Franche-Comté (UFC): HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15041318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 France, Denmark, FrancePublisher:Institute of Electrical and Electronics Engineers (IEEE) Mehdi Sellali; Achour Betka; Abdesslem Djerdir; Yongheng Yang; Imene Bahri; Said Drid;The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.
Aalborg University R... arrow_drop_down IEEE Transactions on Energy ConversionArticle . 2021 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tec.2020.3017811&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 14 citations 14 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Aalborg University R... arrow_drop_down IEEE Transactions on Energy ConversionArticle . 2021 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tec.2020.3017811&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu
description Publicationkeyboard_double_arrow_right Article , Other literature type 2022 FrancePublisher:MDPI AG Mehdi Sellali; Alexandre Ravey; Achour Betka; Abdellah Kouzou; Mohamed Benbouzid; Abdesslem Djerdir; Ralph Kennel; Mohamed Abdelrahem;doi: 10.3390/en15041318
The Energy Management Strategy (EMS) in Fuel Cell Hybrid Electric Vehicles (FCHEVs) is the key part to enhance optimal power distribution. Indeed, the most recent works are focusing on optimizing hydrogen consumption, without taking into consideration the degradation of embedded energy sources. In order to overcome this lack of knowledge, this paper describes a new health-conscious EMS algorithm based on Model Predictive Control (MPC), which aims to minimize the battery degradation to extend its lifetime. In this proposed algorithm, the health-conscious EMS is normalized in order to address its multi-objective optimization. Then, weighting factors are assigned in the objective function to minimize the selected criteria. Compared to most EMSs based on optimization techniques, this proposed approach does not require any information about the speed profile, which allows it to be used for real-time control of FCHEV. The achieved simulation results show that the proposed approach reduces the economic cost up to 50% for some speed profile, keeping the battery pack in a safe range and significantly reducing energy sources degradation. The proposed health-conscious EMS has been validated experimentally and its online operation ability clearly highlighted on a PEMFC delivery postal vehicle.
Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/4/1318/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversité de Franche-Comté (UFC): HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15041318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 30 citations 30 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Energies arrow_drop_down EnergiesOther literature type . 2022License: CC BYFull-Text: http://www.mdpi.com/1996-1073/15/4/1318/pdfData sources: Multidisciplinary Digital Publishing InstituteUniversité de Franche-Comté (UFC): HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)Université de Bretagne Occidentale: HALArticle . 2022Full-Text: https://hal.univ-brest.fr/hal-03708192Data sources: Bielefeld Academic Search Engine (BASE)add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.3390/en15041318&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Journal 2021 France, Denmark, FrancePublisher:Institute of Electrical and Electronics Engineers (IEEE) Mehdi Sellali; Achour Betka; Abdesslem Djerdir; Yongheng Yang; Imene Bahri; Said Drid;The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.
Aalborg University R... arrow_drop_down IEEE Transactions on Energy ConversionArticle . 2021 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tec.2020.3017811&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 14 citations 14 popularity Top 10% influence Top 10% impulse Top 10% Powered by BIP!
more_vert Aalborg University R... arrow_drop_down IEEE Transactions on Energy ConversionArticle . 2021 . Peer-reviewedLicense: IEEE CopyrightData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1109/tec.2020.3017811&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu