## 3 Results
Similarly, the Fan Variable (Fan V) configuration reduces consumption by 6.3% under the same conditions, while the Compressor Constant (Comp C) configuration offers a smaller improvement of 4.3%. As ambient temperature increases, the efficiency gains of variable-speed configurations diminish slightly. At 0\({}^{\circ}\)C, Comp V and Fan V reduce hydrogen consumption by 5.8% and 3.9%, respectively, relative to Fan C. At moderate temperatures (20\({}^{\circ}\)C), Fan V and Comp V still outperform Fan C, with reductions of 2.5% and 3.6%, respectively. However, at high temperatures (40 \({}^{\circ}\)C), the performance differences narrow further. Fan V achieves only a 1.3% reduction, while Comp V provides a 2.4% reduction compared to Fan C. Interestingly, the Compressor  
Figure 21: Power comparison of fan and compressor architectures with respect to variable current input. Figure 20: Exp. and 1D model correlations of power and voltage values of fan and compressor architectures. Constant configuration shows an increase in hydrogen consumption at 40 \({}^{\circ}\)C, exceeding that of Fan C by 0.8%, highlighting its inefficiency under high-temperature conditions. Overall, the Compressor Variable (Comp V) configuration consistently delivers the best performance across all temperature ranges, especially in colder environments. The Fan Variable (Fan V) configuration provides balanced efficiency improvements across the entire temperature spectrum, albeit with smaller gains. These findings emphasize the importance of adaptive control strategies in optimizing hydrogen consumption for fuel cell systems, with variable-speed configurations offering significant improvements over constant-speed setups, particularly under extreme ambient conditions. The test results presented in Figure 23 compare velocity and power measurements between two architectures. In the velocity graph (left), both architectures maintain similar peak velocities, with values consistently around 8-9 m/s during steady operation. However, deviations in velocity occur during transitional phases (e.g., acceleration and deceleration). The power graph (right) demonstrates a more significant distinction. Both architectures exhibit power fluctuations throughout the test. These deviations indicate slightly faster response times in the compressor arch., but the differences remain minimal, with an average error of less than 3% between the two architectures. Figure 23: Test results: velocity and power measurements from the torque sensor. Figure 22: Simulation results of the hydrogen gas consumption with respect to different ambient temperatures. Figure 24 presents the hydrogen consumption rates for two architectures. The compressor architecture demonstrates improved hydrogen efficiency, reducing average consumption by approximately 8.3% and peak consumption by 7.9% compared to the fan architecture with respect to the experimental results. Additionally, the compressor architecture decreases the average fuel consumption by approximately 10.3%. These results indicate that the compressor architecture is better optimized for fuel utilization, particularly under dynamic operating conditions, which enhances overall system efficiency. The maximum errors between the simulation results and experimental data are 5.78% and 5.36% for the fan and compressor architectures, respectively. These errors stem from various factors, including simplifying assumptions in the 1D model, which does not fully capture the multidimensional effects of airflow distribution and local phenomena. Moreover, additional sources of discrepancy include sensor reading errors, driver-induced variations in vehicle operation, simplifications in the thermal modeling approach, and idealized assumptions in the fan and compressor models. These factors collectively contribute to deviations between simulated and experimental results.