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            <title xml:lang="fr">Hybrid Electric Vehicles : Classification, Modeling And Energy Management</title>
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                <term xml:lang="en">ENERGETIC MACROSCOPIC REPRESENTATION</term>
                <term xml:lang="en">HYBRID ELECTRIC VEHICLES</term>
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              <p>Hybrid Electric Vehicles (HEVs) are developed for reduction of consumption and pollutant emissions of road vehicles. Different topologies and hybridization ratios have been studied and different vehicles are now proposed by manufacturers . Because of the complexity of their power trains, the energy management is a key issue in order to ensure dynamic performances and low-consumption operations. In order to perform an advanced control of the HEV including high performance energy management, a systemic approach using simulation is a necessary step. A lot of simulation packages have been developed for the design and the energy management of HEVs. Among the scientific communities working on these aspects, the French MEGEVH network on Hybrid Electric Vehicles (HEVs) is developing generic methodologies for the development of efficient energy management of different kinds of vehicles . This presentation aims to share the experience get from the MEGEVH network concerning energetic modelling and energy management of HEVs. First, a state of the art will be given about existing methodologies of representation used as a support in vehicle software development. Examples of worldwide software will be also showed and commented. A special focus will be made on Energetic Macroscopic Representation developed at Lille University and on VEHLIB software performed by IFSTTAR -LTE . In a second part, an overview of the energy management strategies used in the HEVs control is presented. Basically, the energy management of a HEV could be performed using different methods. The simplest and most known methods use rule based techniques that require a deep expertise for each topology and each components sizing of the HEV . Optimization based methods could be more appropriate when a minimum of consumption and/or emission is needed . In the future, HEVs are going to be more and more complex, most likely toward two directions: the complexity of the storage system and the drive train integration. The use of high performance representation and simulation tools as well as advanced control methods becomes more vital. Two examples, one concerning a hybrid storage system and the other dealing with an integrated Electric Variable Transmission will be given to substantiate the usefulness of the MEGEVH's proposed generic methods.</p>
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