Rapid Prediction of the Open-Circuit-Voltage of Lithium Ion Batteries Based on an Effective Voltage Relaxation Model

Jie Yang,Geping Yin,Bo Lei,Yunzhi Gao,Xinqun Cheng,Jiajun Wang,Jingying Xie,Chunyu Du,Pengjian Zuo,Ting Wang,Yulin Ma

doi:10.3390/en11123444

Abstract

The open circuit voltage of lithium ion batteries in equilibrium state, as a vital thermodynamic characteristic parameter, is extensively studied for battery state estimation and management. However, the time-consuming relaxation process, usually for several hours or more, seriously hinders the widespread application of open circuit voltage. In this paper, a novel voltage relaxation model is proposed to predict the final open circuit voltage when the lithium ion batteries are in equilibrium state with a small amount of sample data in the first few minutes, based on the concentration polarization theory. The Nernst equation is introduced to describe the evolution of relaxation voltage. The accuracy and effectiveness of the model are verified using experimental data on lithium ion batteries with different kinds of electrodes (LiCoO2/mesocarbon-microbead and LiFePO4/graphite) under different working conditions. The validation results show that the presented model can fit the experimental results very well and the predicted values are quite accurate by taking only 5 min or less. The satisfying results suggest that the introduction of concentration polarization theory might provide researchers an alternative model form to establish voltage relaxation models.

Highlights

Due to their unique advantages in energy/power density and cycle life, rechargeable lithium-ion batteries (LIBs) are preferred in energy storage devices for most applications in portable electronics, electric vehicles (EV) and grid energy storage [1,2,3]
It should be noted that the function of the ion concentration is deduced based some ideal assumptions and it’s infeasible and impractical here to still deduce the specific expression of f (t) in Equation (7) exactly based on the physical and chemical mechanism, since we aim to develop a simple and applicable voltage relaxation model to predict the open circuit voltage (OCV) within a short period of time
In order to verify the effectiveness of our model at low temperature, we studied the voltage relaxation process of cells discharged at different temperatures

Summary

Introduction

Due to their unique advantages in energy/power density and cycle life, rechargeable lithium-ion batteries (LIBs) are preferred in energy storage devices for most applications in portable electronics, electric vehicles (EV) and grid energy storage [1,2,3]. In order to ensure the reliable and safe operation of LIBs, accurate online estimation of battery states, including state of charge (SOC) [4,5,6], state of health (SOH) [7,8,9] and state of energy (SOE) [10,11,12], is the most crucial task for a battery management system (BMS). Energies 2018, 11, 3444 be employed to estimate the SOC of LIBs because the relationship between e-OCV and SOC is very apparent and nearly monotonous for most of LIBs [16,17]. OCV-SOC-T for SOC estimation [18]. The e-OCV -SOC curve or PEER REVIEW surface are obtained in the lab beforehand as a look-up

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Methods

Discussion

Conclusion