PDF

Lithium iron phosphate electrode semi em

B. Rajabloo, A. Jokar

2026enlithium-ion batterieslithium iron phosphateelectrode modelingsingle particle modelelectrochemistrydiffusion

Abstract

Language:

The galvanostatic performance of a pristine lithium iron phosphate (LFP) electrode is investigated to address the challenge of its poor intrinsic electronic conductivity. The objective of this study is to propose an empirical variable resistance approach for the single particle model (SPM) to better understand the behavior of LFP batteries. Methodologically, the model is validated against two different laboratory-made Li/LFP coin cell configurations: a high-energy and a high-power setup. Experimental results are compared with the model predictions to assess its accuracy. The findings reveal that the variable resistance model effectively captures the increasing resistance encountered at the end of the discharge process, which is attributed to the increased ohmic resistance associated with LFP active materials. These insights contribute to a deeper understanding of performance dynamics in LFP electrodes, thus enhancing their application in lithium-ion battery technologies.

Download

Cite This Work

@article{f2d42aac-23ae-4387-8701-0c39b7bddaef,
  title={Lithium iron phosphate electrode semi em},
  author={B. Rajabloo and A. Jokar},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - Lithium iron phosphate electrode semi em
AU  - B. Rajabloo
AU  - A. Jokar
PY  - 2026
LA  - en
ER  -

Similar Items

Electrochemical techniques for a cleaner

Important advances in electrochemical engineering technology over the last three decades have fostered the development of a lternative methods to alle

2026enPDF

640069

Roger Rumbu

2025enPPTX

Nanotechnology Perceptions

Venkata Sai Chandra Prasanth Narisetty, Tejaswi Maddineni

The global shift towards electric vehicles (EVs) as a sustainable alternative to traditional gasoline-powered cars has triggered a significant rise in

2024EnglishPDF

Causal Anomaly Detection for Lithium-Ion Battery Degradation

Dieter W. Heermann, Hagen Heermann

Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c

2026EnglishPDF

Causal Anomaly Detection for Lithium-Ion Battery Degradation

Dieter W. Heermann, Hagen Heermann

Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c

2026EnglishPDF

Page 1 of 46

Song Zhang, Ruohan Guo

This comprehensive review focuses on the experimental methods, health indicators, and diagnostic strategies pertinent to retired lithium-ion batteries

2025EnglishPDF