Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/107854
Title: Battery management technologies in hybrid and electric vehicles
Authors: Liu, W 
Chau, KT 
Issue Date: 2024
Source: In CHT Lee (Eds.). Emerging Technologies for Electric and Hybrid Vehicles, p. 219-248. Singapore: Springer Nature, 2024
Abstract: 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.
Publisher: Institute of Electrical and Electronics Engineers
ISBN: 978-981-99-3059-3 (Hardcover)
978-981-99-3062-3 (Softcover)
978-981-99-3060-9 (eBook)
DOI: 10.1007/978-981-99-3060-9_8
Appears in Collections:Book Chapter

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Embargo End Date 2025-01-28
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