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Battery Management Systems of Electric and Hybrid Electric Vehicles



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Autore: Tudoroiu Nicolae Visualizza persona
Titolo: Battery Management Systems of Electric and Hybrid Electric Vehicles Visualizza cluster
Pubblicazione: Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica: 1 online resource (146 p.)
Soggetto topico: Technology: general issues
Soggetto non controllato: 3RC ECM Li-ion battery model
adaptive EKF SOC estimator
adaptive UKF SOC estimator
ADVISOR estimate
arrayed waveguide grating (AWG)
battery
battery degradation
battery management systems
battery model
CMOS sensor
current distribution
direct laser lithography
electric bus
electric mobility
electric vehicles
fault detection and isolation
fiber Bragg grating (FBG)
lithium-ion battery
measuring test bench
online parameter estimation
parallel-connected cells
particle filter SOC estimator
recursive least squares
SAFT lithium-ion battery
sensor fault
Simscape model
state of charge
supercapacitor
tab contact resistance
ultracapacitor
Persona (resp. second.): TudoroiuNicolae
Sommario/riassunto: The topics of interest in this book include significant challenges in the BMS design of EV/HEV. The equivalent models developed for several types of integrated Li-ion batteries consider the environmental temperature and ageing effects. Different current profiles for testing the robustness of the Kalman filter type estimators of the battery state of charge are used in this book. Additionally, the BMS can integrate a real-time model-based sensor Fault Detection and Isolation (FDI) scheme for a Li-ion cell undergoing degradation, which uses the recursive least squares (RLS) method to estimate the equivalent circuit model (ECM) parameters. This book will fully meet the demands of a large community of readers and specialists working in the field due to its attractiveness and scientific content with a great openness to the side of practical applicability. This covers various interesting aspects, especially related to the characterization of commercial batteries, diagnosis and optimization of their performance, experimental testing and statistical analysis, thermal modelling, and implementation of the most suitable Kalman filter type estimators of high accuracy to estimate the state of charge
Titolo autorizzato: Battery Management Systems of Electric and Hybrid Electric Vehicles  Visualizza cluster
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910557598003321
Lo trovi qui: Univ. Federico II
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