A novel fractional order model based state-of-charge estimation method for lithium-ion battery

By Hao Mu, Rui Xiong, Hongfei Zheng, Yuhua Chang, Zeyu Chen. 2017

156 citations recorded by the source corpus.

Subfields: Automotive Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/479f1bff3d5996c1464ac81323ede04a27c333dd

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. Xiaosong Hu
2. Lei Zhang
3. Zhenpo Wang
4. Michael G. Pecht
5. Changfu Zou
6. Torsten Wik
7. Moh Yamani Idna Idris
8. Nicolás Muñoz-Galeano

In Electrical and Electronic Engineering

1. Xiaosong Hu
2. Zhenpo Wang
3. Michael G. Pecht
4. Changfu Zou
5. Lei Zhang
6. Torsten Wik
7. Moh Yamani Idna Idris
8. Nicolás Muñoz-Galeano

Citations in the corpus

• SoC Estimation for Lithium-ion Batteries: Review and Future Challenges (2017, methodology): “To estimate the SoC of a LiB, [59] deduces a fractional order Kalman filter and establishes a battery model that cannot be classified into the next two categories, but it is based on the two techniques presented here.”
• Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries (2019, methodology): “The performance of the ECIM with one CPE is similar to the fifth-order RC model [31].”
• A review of fractional-order techniques applied to lithium-ion batteries, lead-acid batteries, and supercapacitors (2018, methodology): “By extending these estimation approaches to FOMs, some initial work has recently been attempted to estimate the SoC of Li-ion cells [65, 114] and of supercapacitors [30].”