@prefix dcat: <http://www.w3.org/ns/dcat#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix vcard: <http://www.w3.org/2006/vcard/ns#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00863541v1> a dcat:Dataset ;
    dct:description """
              Hybrid electric vehicle have known a quickly grow in the last 10 years.Between conventional vehicles which are criticized for their CO2 emissionand electric vehicles which have a big issue about autonomy, hybrid electricones seems to be a good trade of. No standard has been set yet, and the architecturesresulting of theses productions vary between brands. Nevertheless,all of them are design as a thermal vehicle with battery added which leadsto bad sizing of the component, specially internal combustion engine andbattery capacity. Consequently, the control strategy applied to its componentshas a lot of constraints and cannot be optimal.This thesis investigate a new methodology to design and control a hybridelectric vehicle. Based on statistical description of driving cycle and the generationof random cycle, a new way of sizing component is presented. Thecontrol associate is then determined and apply for different scenarios : firstlya heavy vehicle : A truck and then a lightweight vehicle. An offline controlbased on the optimization of the power split via a dynamic programmingalgorithm is presented to get the optimal results for a given driving cycle.A real time control strategy is then define with its optimization for a givenpatterns and compared to the offline results. Finally, a new control of plug inhybrid electric vehicle based on destination predictions is presented.
            """ ;
    dct:identifier "NNT: 2012BELF0192" ;
    dct:issued "2026-05-09T16:50:32.184356"^^xsd:dateTime ;
    dct:language "en" ;
    dct:modified "2026-05-09T16:50:32.184361"^^xsd:dateTime ;
    dct:publisher <https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> ;
    dct:title "Design and control strategy of powertrain in hybrid electric vehicles" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "CCSD" ] ;
    dcat:distribution <https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00863541v1/resource/c3648057-9eac-475d-8d42-1352aaa9ec3c> ;
    dcat:keyword "algorithme-genetique",
        "chaine-de-traction-hybride",
        "control-strategy",
        "dynamic-programming",
        "fuel-cell",
        "genetic-algorithm",
        "gestion-de-lenergie",
        "hybrid-electric-powertrain",
        "hybrid-electric-vehicle",
        "infoeu-reposemanticsdoctoralthesis",
        "physcondcm-genphysics-physicscondensed-matter-cond-matother-cond-matother",
        "pile-a-combustible",
        "programmation-dynamique",
        "theses",
        "vehicules-hybrides-electriques" ;
    dcat:landingPage <https://theses.hal.science/tel-00863541> .

<https://rec.harvest-normandie.data4citizen.com/dataset/oai-hal-tel-00863541v1/resource/c3648057-9eac-475d-8d42-1352aaa9ec3c> a dcat:Distribution ;
    dct:format "HTML" ;
    dct:issued "2026-05-09T16:50:32.193709"^^xsd:dateTime ;
    dct:modified "2026-05-09T16:50:32.168446"^^xsd:dateTime ;
    dct:title "Design and control strategy of powertrain in hybrid electric vehicles" ;
    dcat:accessURL <https://theses.hal.science/tel-00863541> .

<https://rec.harvest-normandie.data4citizen.com/organization/cce9db95-46d9-4dc2-84b6-764215d0a002> a foaf:Agent ;
    foaf:name "test_moissonnage_selune" .

<https://theses.hal.science/tel-00863541> a foaf:Document .