Development of a Comprehensive Model for the Coulombic Efficiency and Capacity Fade of LiFePO4 Batteries under Different Aging Conditions

Abstract

In this paper, a comprehensive model for LiFePO4 batteries is proposed to ensure high efficiency and safe operation. The proposed model has a direct correlation between its parameters and the electrochemical principles to estimate the state of charge (SoC) and the remaining capacity of the LiFePO4 battery. This model was based on a modified Thévenin circuit, Butler–Volmer kinetics, the Arrhenius equation, Peukert’s law, and a back propagation neural network (BPNN), which can be divided into two parts. The first part can be represented by the dual exponential terms, responsive to the Coulomb efficiency; the second part can be described by the BPNN, estimating the remaining capacity. The model successfully estimates the SoC of the batteries that were tested with an error of 1.55%. The results suggest that the model is able to accurately estimate the SoC and the remaining capacity in various environments (discharging C rates and temperatures).

Cobalt and oxygen double doping induced C@MoS2–CoS2–O@C nanocomposites with an improved electronic structure and increased active sites as a high-performance anode for sodium-based dual-ion batteries

“…This may be because coulombic efficiency is related to voltage fluctuation and discharge time. 51 And the greater the voltage fluctuation, the lower the coulombic efficiency. Meanwhile, the charge–discharge profiles of S-DIBs (Fig.…”

Battery Management System for Future Electric Vehicles

“…The third paper, authored by Kuo [3], presents a battery model based on a modified Thévenin circuit, Butler-Volmer kinetics, Arrhenius equation, Peukert's law, and a back propagation neural network (BPNN). The model can estimate the coulombic efficiency and the remaining capacity of the battery, as analyzed experimentally under various environmental conditions.…”

An improved feedforward-long short-term memory modeling method for the whole-life-cycle state of charge prediction of lithium-ion batteries considering current-voltage-temperature variation

“…The influence of the increase in resistance due to capacity decay is analyzed to establish a global self-discharge model for lithium-ion batteries [60]. By considering the capacity attenuation, the capacity decay of the long battery life is analyzed for the buffer application of EV superchargers [61]. The electric bus fleet is dispatched optimally by the dynamic mathematical programming, as it experiences capacity decays and thermal stability after overcharging [59].…”