TY - BOOK ID - 138336042 TI - Battery Management Systems of Electric and Hybrid Electric Vehicles PY - 2021 PB - Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute DB - UniCat KW - arrayed waveguide grating (AWG) KW - CMOS sensor KW - direct laser lithography KW - fiber Bragg grating (FBG) KW - lithium-ion battery KW - fault detection and isolation KW - sensor fault KW - battery model KW - battery management systems KW - battery degradation KW - electric vehicles KW - online parameter estimation KW - recursive least squares KW - parallel-connected cells KW - measuring test bench KW - current distribution KW - tab contact resistance KW - battery KW - ultracapacitor KW - supercapacitor KW - electric mobility KW - electric bus KW - SAFT lithium-ion battery KW - Simscape model KW - 3RC ECM Li-ion battery model KW - state of charge KW - adaptive EKF SOC estimator KW - adaptive UKF SOC estimator KW - particle filter SOC estimator KW - ADVISOR estimate UR - https://www.unicat.be/uniCat?func=search&query=sysid:138336042 AB - 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 ER -