In this work, an internal combustion (IC) engine air‐fuel ratio (AFR) control system is presented and evaluated by simulation. The control scheme aims to regulate the overall air‐fuel ratio (AFRoverall) in an IC engine fueled with a hydrogen‐enriched ethanol‐gasoline blend (E10) as fast as possible. The control scheme designed and developed in this work considers two control laws, a feedback control law to regulate the hydrogen and adaptive nonlinear control law for controlling the E10 mass flow injection. The main contribution of this work is the reduction of the number of controllers used for controlling the overall air‐fuel ratio since other control strategies use two controllers for controlling the E10 mass flow injection. Simulation results have shown the effectiveness of the new control scheme.

This work shows the results of evaluating the corrosion type and rate (CR) in the 6061-T6 aluminum alloy exposed to ethanol-gasoline blends (E0, E10, E20, E30, E40, E60, E80, and E100) by analyzing electrochemical noise (EN) signals using the Shannon energy (SSE) and the synchrosqueezing transform (SST). The obtained results are compared against the obtained with the statistical method (Location Index, LI). The results obtained with the SSE method showed that the corrosion type in the 6061-T6 aluminum alloy is classified better than using the statistical method. Moreover, the SST results showed that the corrosion rate increased with the increment of the ethanol content in the ethanol-gasoline blends from values in the order of to mm/year.

In this work, an experimental evaluation was performed using four analytical methods applied to electrochemical noise (EN) signals to estimate the corrosion rate ($C_r$) of reinforced concrete structures. A dataset comprising 10,166 synchronized EN files acquired over approximately 220 days was analyzed. The EN signals were obtained from various natural aqueous media, including seawater and river water, as well as from two laboratory reference media (3.5% NaCl solution and reverse-osmosis water). The Statistical Method (SM), the Fast Fourier Transform (FFT), the Maximum Entropy Method (MEM), and the Stockwell Transform (ST) were used to calculate $C_r$. The resulting corrosion rates were evaluated using a two-way analysis of variance (ANOVA) with full interaction, followed by Tukey HSD post hoc comparisons. Significant effects were found for both the analytical methods and the exposure media ($p<0.001$). Among the methods evaluated, MEM showed the greatest statistical stability and robustness, while ST showed the greatest tolerance to noise and the non-stationary characteristics of the EN signals. Estimated corrosion rates ranged from $0.0366 \mathrm{mm}/\mathrm{year}$ in reverse-osmosis water (MEM) to $0.2022 \mathrm{mm}/\mathrm{year}$ in 3.5% NaCl (MEM). For ST, the corresponding values ranged from $0.0652 \mathrm{mm}/\mathrm{year}$ to $0.3504 \mathrm{mm}/\mathrm{year}$ in the same media. These results demonstrate that both the analytical method and the corrosive medium significantly influence EN-based corrosion rate estimates and highlight the potential of MEM and ST for long-term corrosion monitoring of reinforced concrete.