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Battery Management System for Future Electric Vehicles



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Autore: Söffker Dirk Visualizza persona
Titolo: Battery Management System for Future Electric Vehicles Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica: 1 electronic resource (154 p.)
Soggetto topico: History of engineering & technology
Soggetto non controllato: state of charge (SOC)
joint estimation
lithium-ion battery
variational Bayesian approximation
dual extended Kalman filter (DEKF)
measurement statistic uncertainty
electric vehicles
renewable energy sources
microgrid
economic dispatching
capacity allocation
cooperative optimization
SOC
second-order RC model
model parameter optimization
AUKF
small-signal modeling
battery energy storage system
battery management system
control
stability
dynamic response
wireless power
state-of-charge
electric vehicle
LiFePO4 batteries
state of charge (SoC)
Butler-Volmer equation
Arrhenius
Peukert
coulomb efficiency
back propagation neural network (BPNN)
torque and battery distribution
particle swarm optimization
air-cooled BTMS
compact lithium ion battery module
ANN
battery electric vehicles
battery management
hybrid energy storage
Persona (resp. second.): MoulikBedatri
SöffkerDirk
Sommario/riassunto: The future of electric vehicles relies nearly entirely on the design, monitoring, and control of the vehicle battery and its associated systems. Along with an initial optimal design of the cell/pack-level structure, the runtime performance of the battery needs to be continuously monitored and optimized for a safe and reliable operation and prolonged life. Improved charging techniques need to be developed to protect and preserve the battery. The scope of this Special Issue is to address all the above issues by promoting innovative design concepts, modeling and state estimation techniques, charging/discharging management, and hybridization with other storage components.
Titolo autorizzato: Battery Management System for Future Electric Vehicles  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557625603321
Lo trovi qui: Univ. Federico II
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