Using probability density function to evaluate the state of health of lithium-ion batteries

By Xuning Feng, Jianqiu Li, Minggao Ouyang, Languang Lu, Jianjun Li, Xiangming He. 2013

184 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/0a29805586cf4e5e81d385e91574211fb5ed5931

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Xuning Feng
2. Minggao Ouyang
3. Languang Lu
4. Xianke Lin
5. Xiaosong Hu
6. Jianqiu Li
7. Simona Onori
8. Yunhong Che

In Electrical and Electronic Engineering

1. Xuning Feng
2. Minggao Ouyang
3. Languang Lu
4. Xianke Lin
5. Xiaosong Hu
6. Jianqiu Li
7. Simona Onori
8. Yunhong Che

Citations in the corpus

• Battery Health Prediction Using Fusion-Based Feature Selection and Machine Learning (2020, methodology): “Based on the DV curve, the peak (DVP) [58]and valley (DVV) [35], the peak location (DVPL) [32], [59], and the valley location (DVVL) [34], [60] are extracted as HIs.”