A Data-Driven Method with Feature Enhancement and Adaptive Optimization for Lithium-Ion Battery Remaining Useful Life Prediction

Data-driven methods are widely applied to predict the remaining useful life (RUL) of lithium-ion batteries, but they generally suffer from two limitations: (i) the potentials of features are not fully exploited, and (ii) the parameters of the prediction model are difficult to determine. To address t...

पूर्ण विवरण

में बचाया:
ग्रंथसूची विवरण
मुख्य लेखकों: Jun Peng, Zhiyong Zheng, Xiaoyong Zhang, Kunyuan Deng, Kai Gao, Heng Li, Bin Chen, Yingze Yang, Zhiwu Huang
स्वरूप: Artigo
भाषा:Inglês
प्रकाशित: MDPI AG 2020-02-01
श्रृंखला:Energies
विषय:
lithium-ion battery
remaining useful life
gradient boosting decision trees
the box-cox transformation
time window
particle swarm optimization
ऑनलाइन पहुंच:https://www.mdpi.com/1996-1073/13/3/752
टैग : टैग जोड़ें
कोई टैग नहीं, इस रिकॉर्ड को टैग करने वाले पहले व्यक्ति बनें!

समान संसाधन