An exact prediction of temperature inside cylindrical lithium ion (Li-ion) batteries is important for their safe operation, extended life expectancy and development of next generation battery management systems. Research attempts have been made to place temperature sensors inside cylindrical Li-ion batteries [1, 2], but such arrangements are not yet commercially available. Alternatively, a computational fluid dynamics (CFD) approach can be used to accurately predict internal temperature profiles. This computational technique couples the multiphysics phenomena occurring inside cylindrical Li-ion batteries [3, 4].

In this work we present a coupled one dimensional electrochemical and three dimensional thermal CFD model, to predict internal and surface temperature profiles of a commercially available 21700 cylindrical Li-ion battery. Since the operating temperature has an important effect on Li-ion battery ageing, the CFD model is coupled with the solid electrolyte interphase (SEI) formation on the negative electrode. The SEI formation and growth is one of the main reasons that shortens the life expectancy of Li-ion batteries with liquid electrolytes and needs to be addressed in computational models [5]. The developed CFD model will be used to predict temperature profiles and SEI growth response to charge, discharge and rest duty-cycle periods of the 21700 cylindrical Li-ion battery. Surface temperature and voltage profiles acquired from the CFD model will be compared against experimental results to confirm the validity of the computational model. Such an extended model will represent a computational framework to potentially decrease the cost and number of 21700 cylindrical Li-ion battery experiments with different duty-cycle scenarios. It will also support the design of more advanced battery management systems and optimise the cooling and heating system of battery modules and packs.

References:

[1] Horizon 2020 Projects: Portal – Issue 13, Smarter battery management, 93, 2017.

[2] G. Zhang, L. Cao, S. Ge, C.-Y. Wang, C. E. Shaffer, C. D. Rahn, Reaction temperature sensing (RTS)-based control for Li-ion battery safety. Scientific Reports, 5, 18237, 1-6, 2015.

[3] D. H. Jeon, Numerical modeling of lithium ion battery for predicting thermal behavior in a cylindrical cell. Current Applied Physics, 14 (2), 196-205, 2014.

[4] L. H. Saw, Y. Ye, A. A. O. Tay, Electrochemical-thermal analysis of 18650 lithium iron phosphate cell. Energy Conversion and Management, 75, 162-174, 2013.

[5] M. B. Pinson, M. Z. Bazant, Theory of SEI formation in rechargeable batteries: capacity fade, accelerated aging and lifetime prediction. Journal of The Electrochemical Society, 160 (2), A243-A250, 2013.