Climate change, urban air quality, and dependency on crude oil are important societal challenges. In the transportation sector especially, clean and energy efficient technologies must be developed. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) have gained a growing interest in the vehicle industry. Nowadays, the commercialization of EVs and PHEVs has been possible in different applications (i.e., light duty, medium duty, and heavy duty vehicles) thanks to the advances in energy storage systems, power electronics converters (including DC/DC converters, DC/AC inverters, and battery charging systems), electric machines, and energy efficient power flow control strategies. This book is based on the Special Issue of the journal Applied Sciences on “Plug-In Hybrid Electric Vehicles (PHEVs)”. This collection of research articles includes topics such as novel propulsion systems, emerging power electronics and their control algorithms, emerging electric machines and control techniques, energy storage systems, including BMS, and efficient energy management strategies for hybrid propulsion, vehicle-to-grid (V2G), vehicle-to-home (V2H), grid-to-vehicle (G2V) technologies, and wireless power transfer (WPT) systems


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    Title :

    Plug-in Hybrid Electric Vehicle (PHEV)


    Contributors:

    Publication date :

    2019


    Size :

    1 Online-Ressource (230 p.)



    Type of media :

    Book


    Type of material :

    Electronic Resource


    Language :

    English


    Keywords :

    lithium-ion battery , measurements , reinforcement learning (RL) , efficient energy management strategies for hybrid propulsion systems , Markov decision process (MDP) , system modelling , adaptive neuron-fuzzy inference system (ANFIS) , marginal , emerging power electronics , LCA , simulated annealing , dual inverter , energy management strategy , Q-learning (QL) , CO2 , meta-analysis , losses model , group method of data handling (GMDH) , electric vehicle , attributional , range-extender , lithium-ion capacitor , time-delay input , Li-ion battery , air quality , engine-on power , power distribution , Paris Agreement , lithium polymer battery , multi-objective genetic algorithm , parallel hybrid electric vehicle , wide bandgap (WBG) technologies , voltage vector distribution , plug-in hybrid , open-end winding , Plugin Hybrid electric vehicle , life-cycle assessment (LCA) , energy management , plug-in hybrid electric vehicle , power sharing , energy storage systems , modified one-state hysteresis model , mobility needs , state of health estimation , dynamic programming , emerging electric machines , including wide bandgap (WBG) technology , hybrid energy storage system , consequential , Well-to-Wheel , state of charge , strong track filter , energy efficiency , novel propulsion systems , Energy Storage systems , energy system , artificial neural network (ANN) , plug-in hybrid electric vehicles (PHEVs) , hybrid electric vehicles , modelling , electricity mix , lifetime model , Li(Ni1/3Co1/3Mn1/3)O2 battery , battery power , convex optimization , capacity degradation , fuel consumption characteristics , interleaved multiport converte , electric vehicles (EVs) , regenerative braking



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