Electric vehicles (EV) and stationary energy storage are the major applications for a battery. We propose zinc-air flow battery (ZAFB) for EV and zinc polyiodide redox flow battery (ZRFB) for stationary energy storage application considering the zinc abundance in India. A mechanically rechargeable zinc-air flow battery reduces the charging time and its high specific energy reduces range anxiety. Similarly, zinc polyiodide redox flow battery (RFB) with its high energy density among the RFB’s and its ability to independently control the power delivery by resizing and energy reserve by varying the electrolyte volume can be a perfect match for grid storage application. Our objective here is to design and develop an efficient ZAFB and ZRFB from scratch by parametric optimisation using statistical and data-driven modeling approaches. We first worked on the cell architecture for both batteries by choosing an appropriate design and suitable battery materials. We then developed working prototypes of ZAFB and ZRFB. After ensuring the successful running of the prototypes we identified all the possible physical and chemical parameters that can potentially influence the battery performance. To understand the influence of the chosen parameters we decided to build a data-driven model using our experimental data and literature data for both ZAFB and ZRFB since building a physics-based model for emerging batteries is challenging. With the use of data-driven models, we will optimise the parameters to ensure efficient running of the ZAFB and ZRFB at different load conditions.