TY - JOUR
T1 - Guest Editorial Introduction to the Focused Section on Real-Time Monitoring, Diagnosis, and Prognosis and Health Management for Electric Vehicles
AU - Gao, Zhiwei
AU - Huang, Victor
AU - Wu, Lifeng
AU - Al Janaideh, Mohammad
AU - Palhares, Reinaldo Martinez
PY - 2023/4/18
Y1 - 2023/4/18
N2 - Nowadays, industrial automation systems are becoming more complex and expensive, and having less tolerance for performance degradation, productivity decrease, and reliability and safety threats, which greatly necessitates to detect and identify any kinds of abnormalities as early as possible, predict the remaining useful life of a component or system, implement real-time resilient operation and health management to minimize performance degradation, improve reliability and safety, and reduce operation and maintenance costs during the life cycles in automation systems [A1], [A2].
AB - Nowadays, industrial automation systems are becoming more complex and expensive, and having less tolerance for performance degradation, productivity decrease, and reliability and safety threats, which greatly necessitates to detect and identify any kinds of abnormalities as early as possible, predict the remaining useful life of a component or system, implement real-time resilient operation and health management to minimize performance degradation, improve reliability and safety, and reduce operation and maintenance costs during the life cycles in automation systems [A1], [A2].
KW - Prognostics and health management
KW - Real-time systems
KW - State of charge
KW - Fault diagnosis
KW - Temperature measurement
KW - Lithium-ion batteries
KW - Estimation
UR - http://www.scopus.com/inward/record.url?scp=85148418051&partnerID=8YFLogxK
U2 - 10.1109/tmech.2023.3234361
DO - 10.1109/tmech.2023.3234361
M3 - Editorial
SN - 1083-4435
VL - 28
SP - 607
EP - 610
JO - IEEE/ASME Transactions on Mechatronics
JF - IEEE/ASME Transactions on Mechatronics
IS - 2
ER -
