Abstract
The thermal runaway model used is a semi-empirical model based on a kinetic equation, parametrised by three parameters (m,n,p). It is believed that this kinetic equation can describe any reaction. The choice of parameters is often made without justifications. We assumed it necessary to develop a method to select the parameters. The method proposed is based on data coming from an accelerating rate calorimeter (ARC) test. The method has been applied on data obtained for cells aged on different conditions. Thanks to a post-mortem analysis and simulations carried out using the parameters obtained, we have shown that the ageing mechanisms have a major impact on the parameters.
Highlights
Lithium ion battery technology is more and more widespread due to its high energy density and good cyclability
The state of health (SOH) was followed via an electrical performance measurement realised at 25 ◦C every 28 days for cells aged by cycling and every 6 weeks for calendar ageing on a battery cycler
All the parameters described were calculated on aged cells in order to appreciate the impact of the ageing on the kinetics model
Summary
Lithium ion battery technology is more and more widespread due to its high energy density and good cyclability This technology can suffer from safety issues. Thermal runaway of the battery results from a chain of reactions, some of which are exothermic. Cells are cycled and tested in order to exhibit different ageing mechanisms that impact the safety. Friesen et al [2] studied the impact of low-temperature cycling on safety, and Borner et al [3] or Larson et al [4] showed the correlation between ageing and thermal stability of batteries. Thermal runaway models are based on the kinetic equation parametrised by the temperature (T) and α (0 ≤ α ≤ 1), the fractional conversion degree of the reactants. The data-crossing proves that ageing mechanisms have a major impact on the parameters that is confirmed by the post-mortem analysis
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