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Autore: | VAN Mierlo Joeri |
Titolo: | Plug-in Hybrid Electric Vehicle (PHEV) |
Pubblicazione: | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica: | 1 electronic resource (230 p.) |
Soggetto non controllato: | hybrid energy storage system |
plug-in hybrid electric vehicle | |
Li-ion battery | |
emerging electric machines | |
lithium-ion capacitor | |
electric vehicles (EVs) | |
efficient energy management strategies for hybrid propulsion systems | |
plug-in hybrid | |
attributional | |
electric vehicle | |
energy system | |
energy efficiency | |
modified one-state hysteresis model | |
air quality | |
adaptive neuron-fuzzy inference system (ANFIS) | |
Markov decision process (MDP) | |
simulated annealing | |
Paris Agreement | |
mobility needs | |
interleaved multiport converte | |
dynamic programming | |
state of health estimation | |
strong track filter | |
LCA | |
modelling | |
consequential | |
losses model | |
voltage vector distribution | |
parallel hybrid electric vehicle | |
electricity mix | |
time-delay input | |
convex optimization | |
lifetime model | |
artificial neural network (ANN) | |
Li(Ni1/3Co1/3Mn1/3)O2 battery | |
battery power | |
CO2 | |
capacity degradation | |
regenerative braking | |
open-end winding | |
novel propulsion systems | |
group method of data handling (GMDH) | |
state of charge | |
Well-to-Wheel | |
energy storage systems | |
including wide bandgap (WBG) technology | |
wide bandgap (WBG) technologies | |
marginal | |
lithium polymer battery | |
life-cycle assessment (LCA) | |
energy management | |
dual inverter | |
lithium-ion battery | |
measurements | |
plug-in hybrid electric vehicles (PHEVs) | |
emerging power electronics | |
Q-learning (QL) | |
fuel consumption characteristics | |
Plugin Hybrid electric vehicle | |
Energy Storage systems | |
meta-analysis | |
range-extender | |
engine-on power | |
reinforcement learning (RL) | |
multi-objective genetic algorithm | |
power sharing | |
energy management strategy | |
power distribution | |
hybrid electric vehicles | |
system modelling | |
Sommario/riassunto: | 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. |
Altri titoli varianti: | Plug-in Hybrid Electric Vehicle |
Titolo autorizzato: | Plug-in Hybrid Electric Vehicle (PHEV) |
ISBN: | 3-03921-454-3 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910367565103321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |