Fuel cell powered industrial electric trucks are widely used in industry where more than 4000 systems are currently installed, achieving more than 20 million operating hours. The electric trucks are equipped with fuel cell power systems instead of an array of lead-acid batteries, which incorporate a permanently mounted pressure vessel containing compressed hydrogen gas and enabling onboard fueling. Fueling can be performed several times a day subjecting the pressure vessel to a large number of pressure cycles. It is critical to design the pressure vessel to withstand the required number of cycles which is in the thousands, over the life of the fuel cell power system estimated at 20000 hours. Steel pressure vessels which are subjected to hydrogen embrittlement are widely used in this application. In order to ensure the safety of the design, a linear elastic fracture mechanics model was developed in order to predict the life of the steel pressure vessel. The developed model was based on the ASME pressure vessel code section KD-10, which uses fatigue crack growth laws based on the relationship between the fatigue crack growth rate (da/dN) and the cyclic intensity factor (ΔK). Two samples were tested under hydrogen cyclic pressure loading. The experimental data was used to obtain estimates for the crack initiation phase. Statistical data was obtained from several hundred systems of the installed base, in order to determine the distributions of the maximum and minimum pressures the vessel is typically subjected to. The probabilistic LEFM model was used in a Monte Carlo simulation where the maximum and minimum pressure assumed a random value based on the equivalent random generator of their associated statistical distribution that is an extreme distribution and a Johnson SB distribution, respectively. The results indicated an increase by a factor of two, in the number of cycles when compared to the cycle prediction based on a constant R-ratio (maximum/minimum fill pressure). The analysis was repeated with normal distribution random generators which resulted in similar results. The results from this analysis ensure the safety of the steel pressure vessel design.

This content is only available via PDF.
You do not currently have access to this content.