A data-driven digital-twin prognostics method for proton exchange membrane fuel cell remaining useful life prediction

Prognostics and health management of proton exchange membrane fuel cell (PEMFC) systems have driven increasing research attention in recent years as the durability of PEMFC stack remains as a technical barrier for its large-scale commercialization. To monitor the health state during PEMFC operation, digital twin (DT), as a smart manufacturing technique, is applied in this paper to establish an ensemble remaining useful life prediction system. A data-driven DT is constructed to integrate the physical knowledge of the system and a deep transfer learning model based on stacked denoising autoencoder is used to update the DT with online measurement. A case study with experimental PEMFC degradation data is presented where the proposed data-driven DT prognostics method has applied and reached a high prediction accuracy. Furthermore, the predicted results are proved to be less affected even with limited measurement data.     

Influence of anode current density on carbon parasitic reactions during electrolysis

In the electro-deoxidation process, carbon parasitic reaction (CO₃^2- + 4e^-=C + 3O^2-) usually occurs when using carbon materials as the anode, which leads to increase of the carbon content in the final metal and decrease of the current efficiency of the process. The aim of this work is to reduce the negative effect of carbon parasitic reaction on the electrolysis process by adjusting anode current density. The results indicate that lower graphite anode area can achieve higher current density, which is helpful to increase the nucleation site of CO₂ bubbles. Most of CO₂ would be released from the anode instead of dissolution in the molten CaCl₂ and reacting with O^2- to form CO₃^2-, thus decreasing the carbon parasitic reaction of the process. Furthermore, the results of the compared experiments show that when the anode area decreases from 172.78 to 4.99 cm², CO₂ concentration in the released gases increases significantly, the carbon mass content in the final metal product decreased from 1.09% to 0.13%, and the current efficiency increased from 6.65% to 36.50%. This study determined a suitable anode current density range for reducing carbon parasitic reaction and provides a valuable reference for the selection of the anode in the electrolysis process.     

Preparation and desalination performance of porous planar cordierite membranes using industrial solid waste as main silica source

Silica is a main component of cordierite ceramic, in the present work, industrial solid waste was used as main silica source to prepare porous planar cordierite membranes by a solid-phase sintering process with starch as pore-forming agent. It is shown that the concentration of starch plays a critical role in the pore structure and mechanical property and the cordierite membranes with a starch concentration of 40?wt% (M-40) have a desirable pore structure and flexural strength after sintering at 1300?°C for 5?h. After grafted with 1H,1H,2H,2H-perfluorooctyltriethoxysilane (FAS, C₈), the ceramic membranes were used for desalination by vacuum membrane distillation (VMD). The results show that the membranes(M-40) possess an average flux of 11.43?kg/m² h, a high salt rejection of 99.9% under the following operation conditions: a NaCl concentration of 3.5?wt%, a feed rate of 300?ml/min and a temperature of 80?°C. After desalination for 120?h, the water contact angle decreases to 130°. The cordierite membranes exhibit poor resistance to thermal acid/alkali solution(boiling, pH?=?1 and 14, respectively, soaked for 8?h) but excellent resistance to ambient temperature acid/alkali solution (25?°C, pH?=?1 and 14, respectively, soaked for 120?h).     

Use of heat-moisture treated maize starch to modify the properties of wheat flour and the quality of noodles

Waxy, normal and high-amylose maize starches were subjected to heat-moisture treatment (HMT) and then added to wheat flour (WF) in different ratios (1%, 5% and 10%). The properties of blends and their cooked noodles were studied to investigate the effects of HMT starches. The incorporation of HMT starch in WF led to an increase in swelling power, peak viscosity and breakdown and to a decrease in setback, thus inhibiting retrogradation, hence enhancing resultant noodle softness. Compared to the same addition ratio of native starch to WF, HMT starch led to higher tensile strength and extensibility in resultant noodles. WF with added HMT starch had higher resistant starch than with native starch. This study showed that addition of HMT maize starch has potential to bring nutritional benefits. However, it is necessary to select the proper blending ratio and amylose content of starch to add, in consideration of its effect on noodle quality.     

Tunable microwave absorption properties of nickel-carbon nanofibers prepared by electrospinning

The nickel-carbon nanofibers (Ni-C NFs) were fabricated by the electrospinning of poly(vinyl alcohol) (PVA) and nickel acetate tetrahydrate (NiAc) solution precursor with succedent PVA pyrolyzation and calcination process. The microwave absorption performance and electromagnetic (EM) parameters of the NFs were researched over the frequency range of 2.0–18.0?GHz. Both the impedance matching and EM wave absorption properties of the Ni-C NFs were improved by changing the carbonization temperature. The effect of graphitization degree on reflection loss (RL) and the possible loss mechanisms were directly displayed in the comparative study of each sample. The optimal RL value of ??44.9?dB and an effective frequency bandwidth of 3.0?GHz under a thickness of 3.0?mm can be reached by a sample calcined at 650?°C. These lightweight Ni-C NFs composites can be promising candidates for EM wave absorbers due to the combination of multiple loss mechanisms, nano-size effect and good impedance matching between Ni nanoparticles and CNFs.     

Techno-economic analysis of hydrogen energy for renewable energy power smoothing

With the increasing proportion of renewable energy (mainly wind power and photovoltaic) connected to the grid, the fluctuation of renewable energy power brings great challenges to the safe and reliable operation of power grid. As a clean, low-carbon secondary energy, hydrogen energy is applied in renewable energy (mainly wind power and photovoltaic) grid-connected power smoothing, which opens up a new way of coupling hydrogen storage energy with renewable energy. This paper focuses on the optimization of capacity of electrolyzers and fuel cells and the analysis of system economy in the process of power output smoothing of wind/photovoltaic coupled hydrogen energy grid-connected system. Based on the complementary characteristics of particle swarm optimization (PSO) and chemical reaction optimization algorithm (CROA), a particle swarm optimization-chemical reaction optimization algorithm (PSO-CROA) are proposed. Aiming at maximizing system profit, the capacity of electrolyzers and fuel cells are constrained by wind power fluctuation, and considering environmental benefits, government subsidies and time value of funds, the objective function and its constraints are established. According to the simulation analysis, by comparing the calculated results with PSO and CROA, it shows that PSO-CROA effectively evaluates the economy of the system, and optimizes the optimal capacity of the electrolyzers and fuel cells. The conclusion of this paper is of great significance for the application of hydrogen energy storage in the evaluation of power smoothness and economy of renewable energy grid connection and the calculation of economic allocation of hydrogen energy storage capacity.