Modelling of lithium-ion batteries calendar ageing is often based on a semi-empirical approach by using, for example the Arrhenius acceleration model. Our approach is based on Eyring acceleration model, which is not widely used for electrochemical energy storage components. Parameter identification is typically performed without taking into account the state-of-charge (SoC) drifting. However, even in rest condition, battery cells' SoC drifts because of capacity losses (self-discharge and capacity fade). In this work we have taken into account the SoC drift during calendar ageing tests. For this, we considered available capacity (Ah) instead of SoC (%) as ageing factor. Then, the analytical solution of the problem leads to the use of the Lambert W function in the model formulation. Simulation results show that Lambert-Eyring model is more accurate and allows a reduction in the number of parameters to be identified.