Reasonable and effective control of a cathode air supply system is conducive to improving the dynamic response, operating efficiency, and reliability of fuel cell systems. This paper proposes a novel data-driven adaptive oxygen excess ratio (OER) control strategy based on online parameter identification for fuel cell systems. The proposed control scheme employs a second-order active disturbance rejection controller (ADRC) derived from the proportional-integral-derivative tuning rule to effectively deal with model uncertainties and external disturbances. Online parameter identification continuously translates the cathode air supply system into the second-order model, enabling the real-time adaptation of controller parameters to varying operating conditions. Simulation results demonstrate that the OER control strategy proposed significantly improves voltage stability and system efficiency under dynamic conditions compared to traditional methods. The innovation of this paper is that, based on consideration of the nonlinear slow time-varying characteristics of a PEMFC and the frequent disturbance of load current, adaptive control under system dynamic conditions can be considered. Combining the parameter identification scheme, an adaptive online self-tuning scheme is designed for the identified system model, which avoids the tediousness of a complex modeling process and has promotion value in practical applications.

Marine wave energy exhibits significant potential as a renewable resource due to its substantial energy storage capacity and high energy density. However, conventional wave power generation technologies often suffer from drawbacks such as high maintenance costs, cumbersome structures, and suboptimal conversion efficiencies, thereby limiting their potential. The wave power generation technologies based on micro-energy technology have emerged as promising new approaches in recent years, owing to their inherent advantages of cost-effectiveness, simplistic structure, and ease of manufacturing. This paper provides a comprehensive overview of the current research status in wave energy harvesting through micro-energy technologies, including detailed descriptions of piezoelectric nanogenerators, electromagnetic generators, triboelectric nanogenerators, dielectric elastomer generators, hydrovoltaic generators, and hybrid nanogenerators. Finally, we provide a comprehensive overview of the prevailing issues and challenges associated with these technologies, while also offering insights into the future development trajectory of wave energy harvesting technology.

High-Cu-content (Cu-content > 1.3 at.%) nanocrystalline alloys exhibit wide heat-treatment windows and favorable soft magnetic properties due to the presence of pre-existing α-Fe nanocrystals. By fabricating ribbons with varying thicknesses to tailor cooling rates, distinct structural characteristics were achieved in Fe₈₂B_16.5Cu_1.5 alloy ribbons. Notably, the face-centered cubic (fcc) γ-Fe phase was identified in Fe-based nanocrystalline alloys. The precipitation of the fcc γ-Fe phase originates from a phase-selection mechanism under specific cooling conditions, while its retention in the as-quenched ribbon with a thickness of 27 μm is attributed to kinetic suppression during rapid cooling and the nanoscale stabilization effect. The formation of the fcc γ-Fe phase significantly reduced the saturation flux density (B_s) and increased coercivity (H_c), concurrently destabilizing the residual amorphous matrix. By suppressing the precipitation of the γ-Fe and Fe₃B phases through precise control of ribbon thickness and annealing parameters, the alloy ribbon with a thickness of 16 μm achieved an optimal combination of B_s (1.82 T) and H_c (8.3 A/m). These findings on anomalous fcc γ-Fe phase precipitation provide novel insights into metastable phase engineering and offer structural design guidelines for alloys containing pre-existing α-Fe nanocrystals.