Coupled electrochemical-thermal model for LiFePO₄ -graphite lithium-ion batteries

Abstract

LiFePO₄-graphite lithium-ion batteries are promising candidates for the electric vehicles and energy storage systems because of their excellence on cycling performance and temperature tolerance comparing with other commercial rechargeable batteries. However, the thermal management of a LiFePO₄-graphite lithium-ion battery pack is still a challenge due to the cell diversity and the strong interaction between the temperature and electrochemical reactions. The systematic investigation of the electrochemical and thermal behaviors of LiFePO₄-graphite lithium-ion batteries is therefore in imminent demand. In present thesis, porous electrode theory was used to build the electrochemical model. In the thermal model, charge transfer resistance, mass transport resistance, reaction kinetic resistance and entropic heating were considered as the heat source of lithium-ion battery. Temperature dependent parameters, including Li⁺ diffusion coefficients, exchange current density and charge conductivity, were used to couple the electrochemical and thermal model. Simulation results showed that coupling the electrochemical model with the thermal model could improve the accuracy meaningfully. At 4 C discharge, single electrochemical model had a relative error of 5.2% for capacity prediction while that of the coupled model was almost 0. Relative errors of temperature prediction at 0.2 C, 1 C and 4 C discharge were 1%, 4% and -6%. This coupled model investigated the interaction between the electrochemical and thermal behaviors of LiFePO₄-graphite lithium-ion batteries. For a 10 Ah LiFePO₄-Graphite battery, with natural convection as boundary condition, electrochemical discrepancy exists among cells located in different location of the battery due to the temperature gradient formed in their operation. At 450 s of 4 C discharge, cells closer to the center exhibit 0.2% lager intercalation rate current density and heat generation rate. Electrochemical properties, including current density and reaction rate, heat generation and temperature formed a positive feedback loop. Sensitivity analysis was conducted to examine the effect of electrochemical parameters and thermal parameters upon prediction of capacity, voltage and temperature. r_p,pos and r_p,neg have remarkable influence upon the capacity. When they increased by 5 times, the capacity dropped by 10% and 25% respectively. Specific heat capacity Cp influences the temperature most. The peak temperature increased 4.8% when Cp reduced 40%. The coupled model was also conducted on a 20 Ah LiFePO₄-Graphite battery. At 4 C discharge, the simulation result of temperature had a maximum relative error of 8.3%, larger than that in case of 10 Ah.

Date of Award	2014
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology