The combination of a fuel cell and batteries has promising potential for powering autonomous vehicles. The MUN Explorer Autonomous Underwater Vehicle (AUV) is built to do mapping-type missions of seabeds as well as survey missions. These missions require a great deal of power to reach underwater depths (i.e., 3000 meters). The MUN Explorer uses 11 rechargeable Lithium-ion (Li-ion) batteries as the main power source with a total capacity of 14.6 kWh to 17.952 kWh, and the vehicle can run for 10 hours. The drawbacks of operating the existing power system of the MUN Explorer, which was done by the researcher at the Holyrood management facility, include mobilization costs, logistics and transport, and facility access, all of which should be taken into consideration. Recharging the batteries for at least 8 hours is also very challenging and time consuming. To overcome these challenges and run the MUN Explorer for a long time, it is essential to integrate a fuel cell into an existing power system (i.e., battery bank). The integration of the fuel cell not only will increase the system power, but will also reduce the number of batteries needed as suggested by HOMER software. In this paper, an integrated fuel cell is designed to be added into the MUN Explorer AUV along with a battery bank system to increase its power system. The system sizing is performed using HOMER software. The results from HOMER software show that a 1-kW fuel cell and 8 Li-ion batteries can increase the power system capacity to 68 kWh. The dynamic model is then built in MATLAB/Simulink environment to provide a better understanding of the system behavior. The 1-kW fuel cell is connected to a DC/DC Boost Converter to increase the output voltage from 24 V to 48 V as required by the battery and DC motor. A hydrogen gas tank is also included in the model. The advantage of installing the hydrogen and oxygen tanks beside the batteries is that it helps the buoyancy force in underwater depths. The design of this system is based on MUN Explorer data sheets and system dynamic simulation results.