Practical Capacity Fading Model for Li-Ion Battery Cells in Electric Vehicles
By L. Lam, Pavol Bauer. IEEE transactions on power electronics, 2013
269 citations recorded by the source corpus.
Subfields: Automotive Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/570700d48f2483f9ec897e4067d5a5a501dd0982
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
- Xiaosong Hu
- Shengbo Eben Li
- Guangzhao Luo
- Yalian Yang
- Fei Gao
- Jinhao Meng
- Seungmin Jeong
- Young Jae Jang
In Electrical and Electronic Engineering
- Xiaosong Hu
- Shengbo Eben Li
- Guangzhao Luo
- Yalian Yang
- Fei Gao
- Jinhao Meng
- Kailong Liu
- Michael G. Pecht
Citations in the corpus
- Advanced Machine Learning Approach for Lithium-Ion Battery State Estimation in Electric Vehicles (2016, background): “Traction battery packs are currently the most common electric energy carrier onboard and thus play an imperative role in the performance, economy, and acceptance of EVs [4]–[7].”
- Economic Analysis of the Dynamic Charging Electric Vehicle (2015, background): “The battery life prediction in EV system has been the most important research area to make decisions for commercializing EVs [30], [31].”
- Lithium Polymer Battery State-of-Charge Estimation Based on Adaptive Unscented Kalman Filter and Support Vector Machine (2016, background): “Since ageing of the battery leads to changes in battery internal characteristics [23], and the parameters of the model vary with SOC level in charging and discharging processes, the battery model should vary with operating time for better accuracy.”