Health prognostics for lithium-ion batteries: mechanisms, methods, and prospects
Lithium-ion battery aging mechanism analysis and health prognostics are of great
significance for a smart battery management system to ensure safe and optimal use of the …
significance for a smart battery management system to ensure safe and optimal use of the …
Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives
The wide application of lithium-ion batteries makes their lifecycle prognosis a challenging
and hot topic in the battery management research field. Feature extraction is a key step for …
and hot topic in the battery management research field. Feature extraction is a key step for …
Impedance-based forecasting of lithium-ion battery performance amid uneven usage
Accurate forecasting of lithium-ion battery performance is essential for easing consumer
concerns about the safety and reliability of electric vehicles. Most research on battery health …
concerns about the safety and reliability of electric vehicles. Most research on battery health …
Machine learning-assisted self-powered intelligent sensing systems based on triboelectricity
Z Tian, J Li, L Liu, H Wu, X Hu, M **e, Y Zhu, X Chen… - Nano Energy, 2023 - Elsevier
The advancement of 5G and the Internet of Things (IoT) has ushered in an era of super-
interconnected intelligence, which promises high-quality social development. Triboelectric …
interconnected intelligence, which promises high-quality social development. Triboelectric …
Analyzing electric vehicle battery health performance using supervised machine learning
Lithium-ion batteries having high energy and power densities, fast depleting cost, and
multifaceted technological improvement lead to the first choice for electric transportation …
multifaceted technological improvement lead to the first choice for electric transportation …
Selecting the appropriate features in battery lifetime predictions
Data-driven models are being developed to predict battery lifetime because of their ability to
capture complex aging phenomena. In this perspective, we demonstrate that it is critical to …
capture complex aging phenomena. In this perspective, we demonstrate that it is critical to …
Battery aging mode identification across NMC compositions and designs using machine learning
A comprehensive understanding of lithium-ion battery (LiB) lifespan is the key to designing
durable batteries and optimizing use protocols. Although battery lifetime prediction methods …
durable batteries and optimizing use protocols. Although battery lifetime prediction methods …
Experimental degradation study of a commercial lithium-ion battery
In this study, we analyze data collected during the aging of 196 commercial lithium-ion cells
with a silicon-doped graphite anode and nickel-rich NCA cathode. The cells are aged over a …
with a silicon-doped graphite anode and nickel-rich NCA cathode. The cells are aged over a …
In-situ battery life prognostics amid mixed operation conditions using physics-driven machine learning
Accurately predicting in-situ battery life is critical to evaluate the system's reliability and
residual value. The high complexity of battery aging evolution under variable conditions …
residual value. The high complexity of battery aging evolution under variable conditions …
Multi-level data-driven battery management: From internal sensing to big data utilization
A battery management system (BMS) is essential for the safety and longevity of lithium-ion
battery (LIB) utilization. With the rapid development of new sensing techniques, artificial …
battery (LIB) utilization. With the rapid development of new sensing techniques, artificial …