## 1 Introduction  
The significance of modelling battery behaviour is present in different stages of development. Besides being a supporting tool for cell design, models can be used during operation to determine critical battery parameters, such as state of charge (SoC) and state of health (SoH), or even for power output predictions [1, 2]. Different approaches, distinguished by their complexity, have already been used to predict electrochemical cell behaviour. A commonly used approach is the \"Thevenin circuit model\", a combination of series-connected resistor-capacitor circuits (RC elements) which reproduce the output voltage of the cell during load and relaxation at reduced computational and implementation expense. However, cell parameters must be carefully designed to ensure a precise modelling output. A different and more accurate method is provided by electrochemical modelling approaches using non-linear differential equations to describe the ongoing chemical reactions. The advantage of these methods over the Thevenin circuit model is the level of detail. Besides the output voltage of the cell, internal cell processes can also be simulated. A third approach is \"Black box modelling\" using machine learning (ML) and artificial intelligence (AI). Here, a wide dataset must be generated and the ML andAI models need to be trained with data. More details and an extensive discussion on the mentioned modelling approaches are given by [PERSON] et al. (2018), [PERSON] et al. (2018) and [PERSON] et al. (2018). In particular, for application-related modelling and the development of cells in battery structures such as modules or battery systems, less complex modelling with RC elements is preferred. However, a trade-off between a low computational effort and the detail of prediction needs to be found. In this work, electrochemical and thermal models of sodium-nickel-chloride/iron-chloride (_Na-MCl\({}_{2}\)_) battery cells is presented. Sodium-nickel-chloride/iron-chloride battery cells are a promising alternative to lithium-ion cells, in particular for large-scale stationary applications ([PERSON] et al., 2017; [PERSON] et al., 2018; [PERSON] et al., 2018). Figure 1 shows a scheme of the cell design. The anode, consisting of liquid sodium, is separated from the porous cathode by a solid electrolyte (_Na-\(\beta^{*}\)_ alumina). The cell operates between 250 \({}^{\circ}\)C and 350 \({}^{\circ}\)C to establish ion transportation through _Na-\(\beta^{*}\)_ alumina. A secondary molten salt electrolyte (tetrachlorouluminate, _NaAlCl\({}_{4}\)_) ensures the ionic conductivity in the porous cathode space. The solid part of the cathode consists of iron chloride and nickel chloride (_FeCl\({}_{2}\)_ and _NiCl\({}_{2}\)_), which serve as active materials, as well as solid _NaCl_, as a product of the discharging reaction. Additionally, an excess of iron and nickel metals ensures electron transport towards the current collector. The current collector, as well as the entire casing, is made of nickel. For each active material (_NiCl\({}_{2}\)_ and _FeCl\({}_{2}\)_) there is a corresponding reaction. As indicated in Equations (1) and (2), these two reactions exhibit different equilibrium voltage levels (_E\({}_{OCV,M}\)_ with _M = Ni or Fe_), enabling the battery cell to cope with higher current peaks ([PERSON] et al., 2018; [PERSON] et al., 2018). \[NiCl_{2}+2 Na \leftrightarrow Ni+2 NaCl \tag{1}\] \[E_{OCV,Ni} = 2.58\ V\] \[FeCl_{2}+2 Na \leftrightarrow Fe+2 NaCl\] (2) \[E_{OCV,Fe} = 2.35\ V\]  
The cell type of _Na-MCl\({}_{2}\)_ batteries stands out, as it contains readily available and eco-friendly substances, especially compared to lithium-ion batteries. The active materials are neither flammable nor explosive. Importantly, there is no occurrence of safety-critical cell states during operation or in case of cell failure.