Abstract: Objectives The enhancement of the economic performance is crucial for the widespread adoption of pure electric ships that powered by battery. Increasing battery capacity allows ship to sail faster, which enable it to complete more missions within the same timeframe and increase incomes. However, increasing battery capacity also bring higher costs. Therefore, it is necessary to optimize battery capacity that considers both incomes and costs. Methods Frist, models for the ship’s battery power system and operation are established. Subsequently, with the objective of maximizing post-battery profit which is the difference between incomes and costs, a bilevel optimization problem for battery capacity and economic speed is formulated. Finally, the optimal solution for battery capacity and economic speed are obtained by particle swarm optimization algorithm. Results Taking a battery container ship as a case study, both the post-battery profit and the economic speed increase in a stepwise manner as the number of battery containers grows. Compared with the battery capacity optimization methods targeting minimal cost or are based on a fixed sailing speed, the approach proposed in this paper achieves a 33.43% improvement in post-battery profit. The post-battery profit exhibits adaptability to variations in electricity prices. Conclusions The proposed method can inform the battery capacity planning for battery-powered ships during the design phase.