A real-world industry issue inspires this study. The cost of EV batteries is critical for the market growth of electric vehicles in today’s era. The cost-effective manufacturing of battery cells is a popular topic in industry and academics. Manufacturers invest billions of dollars in battery cell factories based on predicted EV growth rates. However, manufacturers require information on total manufacturing costs, plant area, total capital equipment costs, and their cost drivers to achieve the goal of a profitable firm. Driven by these concerns, an EPQ model with a process-based cost modeling technique is developed for the large-scale manufacturing of EV battery cells. The data used in this model is collected from the BatPac model (version 4) developed by Argonne National Laboratory. This study considers two types of battery cells used in electric vehicles, and the firm produces 5% of defective cells. This model provides directions to maximize profit by solving the profit function with genetic algorithm considering the production rate and selling price as decision variables. Moreover, this study shows which process steps and cost aspects significantly impact the total cost. Finally, managerial implications and conclusions are presented that support manufacturers in increasing the firm's profit.