TY - CHAP
T1 - Battery Management Technologies in Hybrid and Electric Vehicles
AU - Liu, Wei
AU - Chau, K. T.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.
PY - 2024/1
Y1 - 2024/1
N2 - Hybrid electric vehicles (HEVs) and electric vehicles (EVs) have been advocated by global governments’ policies in recent decades. Besides combating the climate crisis and urban air pollution, great contributions of developing the HEVs and EVs have been identified to accelerate the process of green transportation and smart city. Battery management is one of the most crucial functions for HEVs and EVs. It can ensure safe operation and optimize the performance of EV batteries. This chapter discusses the mainstream technologies of battery management in HEVs and EVs. Wherein, battery management technologies, including battery modeling, battery state estimation, safety prognostic (such as thermal management), and fault diagnosis, are elaborated in detail. Among them, the data-driven method is most effective and promising for battery state estimation (such as for state of charge and state of temperature) and health diagnosis or prognostics with impressive accuracy. Besides, some emerging management technologies, including multi-model co-estimation, artificial intelligence, cloud computing technology, and blockchain technology, are briefed, which can play a significant role in coordinating the information and energy flows in a vehicular information and energy internet.
AB - Hybrid electric vehicles (HEVs) and electric vehicles (EVs) have been advocated by global governments’ policies in recent decades. Besides combating the climate crisis and urban air pollution, great contributions of developing the HEVs and EVs have been identified to accelerate the process of green transportation and smart city. Battery management is one of the most crucial functions for HEVs and EVs. It can ensure safe operation and optimize the performance of EV batteries. This chapter discusses the mainstream technologies of battery management in HEVs and EVs. Wherein, battery management technologies, including battery modeling, battery state estimation, safety prognostic (such as thermal management), and fault diagnosis, are elaborated in detail. Among them, the data-driven method is most effective and promising for battery state estimation (such as for state of charge and state of temperature) and health diagnosis or prognostics with impressive accuracy. Besides, some emerging management technologies, including multi-model co-estimation, artificial intelligence, cloud computing technology, and blockchain technology, are briefed, which can play a significant role in coordinating the information and energy flows in a vehicular information and energy internet.
UR - http://www.scopus.com/inward/record.url?scp=85183583773&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-3060-9_8
DO - 10.1007/978-981-99-3060-9_8
M3 - Chapter in an edited book (as author)
AN - SCOPUS:85183583773
T3 - Green Energy and Technology
SP - 219
EP - 248
BT - Green Energy and Technology
PB - Springer Science and Business Media Deutschland GmbH
ER -
