State of Charge Estimation for Li-ION LFP Cell
Bijit Kalita* and R Jayaganthan
Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India
*Corresponding Author: Bijit Kalita, Department of Engineering Design, Indian Institute of Technology Madras, Chennai, India.
Published: May 31, 2024
Abstract
SOC(State of Charge) estimation for Lithium ion cell with LFP(Lithium iron phosphate) chemistry using different methods. The aim of this study was to get practically accurate results of SOC while tackling the hyped flat curve characteristics of LFP chemistry li-ion cells. Hence the project is divided in two phases the first one focuses on the literature review & the second one on selecting the best method and then implementing & comparing it in real cell dataset to predict the SOC accurately. The study was conducted using smart control algorithms to predict SOC. Data was collected from Kaggle. The results of the study (first phase) showed that double RC model and EKF are the most common techniques which were successfully used for industry R&D. The findings of this study contribute to the existing knowledge by applying the ideas/techniques from different papers & concluding on the best control algorithms to get accurate SOC for LFP cells. The results also have practical implications for how the flatness of Vocv vs SOC curve of LFP affects the prediction. The comparison of the NMC chemistry to LFP then gives clarity on problems with flat curve & possible solutions using filtering techniques like EKF, UKF etc. Overall, this project provides a comprehensive examination of characteristics of LFP and the results have the potential to be applied in industry and further could be used to make strategies for using LFP cells in battery pack.
Keywords: LFP; Li-ION; EV
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