<p>Sodium-ion batteries are emerging as a next-generation battery technology, owing to their abundant raw material. The physics-based pseudo-2-dimensional model is widely used to understand their electrochemical behaviour; however, this model is computationally intensive. To address this issue, this study presents a reduced-order tanks-in-series model consisting of a system of differential-algebraic equations. This model offers computational efficiency while maintaining prediction accuracy, making it a potential candidate for battery management systems. The model variables are volume-averaged in a given domain and are solved at the interface regions in a cathode-separator-anode representation. The pseudo-2-dimensional model is set as a benchmark to evaluate the cell-level quantities. The battery electrodes in this study undergo phase changes and exhibit concentration-dependent diffusivity, which is modelled using the Galerkin formulation. The electrolyte potential variation is modelled with the incorporation of dilute solution theory. The simulation is conducted for various current densities and the electric vehicle drive cycle to evaluate constant current and dynamic operating conditions. The Root Mean Square Error is 3 mV at 1C and 13 mV at 1.5C discharge rate. The tanks-in-series model demonstrates considerable agreement at lower C-rates, with minor deviations at higher discharge rates, which are attributed to the overpotential and averaged molar flux.</p>