Two-dimensional numerical pore-scale investigation of oxygen evolution in proton exchange membrane electrolysis cells

Oxygen blocking the porous transport layer (PTL) increases the mass transport loss, and then limits the high current density condition of proton exchange membrane electrolysis cells (PEMEC). In this paper, a two-dimensional transient mathematical model of anode two-phase flow in PEMEC is established by the fluid volume method (VOF) method. The transport mechanism of oxygen in porous layer is analyzed in details. The effects of liquid water flow velocity, porosity, fiber diameter and contact angle on oxygen pressure and saturation are studied. The results show that the oxygen bubble transport in the porous layer is mainly affected by capillary pressure and follows the transport mechanism of ‘pressurization breakthrough depressurization’. The oxygen bubble goes through three stages of growth, migration and separation in the channel, and then be carried out of the electrolysis cell by liquid water. When oxygen breaks through the porous layer and enters the flow channel, there is a phenomenon that the branch flow is merged into the main stream, and the last limiting throat affects the maximum pressure and oxygen saturation during stable condition. In addition, increasing the liquid water velocity is helpful to bubble separation; changing the porosity and fiber diameter directly affects the width of pore throat and the correlative capillary pressure; increasing porosity, reducing fiber diameter and contact angle can promote oxygen breakthrough and reduce the stable saturation of oxygen.     

Experimental investigation on the heat and water transfer enhancement in a membrane-based air-to-air humidifier at insulation condition

In the present study, a membrane-based air-to-air planar humidifier (MAPH) with baffle-blocked flow channels and a common MAPH are fabricated, tested and compared. These MAPHs are well thermal insulated from their surroundings. Polyoxymethylene (POM) plates with some unique properties such as large tensile and flexural strength, high chemical resistance and high stiffness are used to create channels at dry and humid sides of MAPHs. The obtained findings revealed that the higher heat and water transfer rates and smaller dew point approach temperature (DPAT) in entire tested flow rates occurs in baffle-blocked MAPH. To evaluate the MAPH performance with considering the pressure drop, a dimensionless parameter, performance evaluation criteria (PEC), is introduced. At flow rates less than 1 m³/h, PEC is less than 1, indicating a decline in MAPH performance with considering the pressure drop. In baffle-blocked MAPH using water trap in the inlet of dry side leads to the performance deterioration. Additionally, the increased relative humidity (RH) of humid side inlet causes an increase in DPAT, consequently, the performance deterioration.     

Development of titanium bipolar plates fabricated by additive manufacturing for PEM fuel cells in electric vehicles

Bipolar plates (BPs) are one of the main parts of proton exchange membrane (PEM) fuel cell stacks, which constitute a significant percentage of a PEM fuel cell system in terms of cost, weight, and structural strength. Although frequently used graphite BPs have low density, high conductivity, and high corrosion resistance, machining the desired flow channels on these plates is challenging. On the other hand, BPs made of various materials rather than graphite can be also fabricated by additive manufacturing methods. These methods can be considered as a reasonable alternative to conventional machining for the fabrication of graphite BPs in PEM fuel cells regarding material cost, fabrication of flow channels, and some post-processes in which the large-scale manufacturing of graphite BPs is more complex. This study offers a comparison of formed stainless-steel, additive manufactured titanium and machined composite graphite plates having the same flow-field geometry as a bipolar plate. In addition, titanium BPs are coated with gold and their performances are compared. Among the cells tested, the highest peak power of 639 mWcm^?2 is measured from the cell with 450 nm gold coated titanium BP, whereas those of the cell with conventional graphite and stainless-steel BP are only around 322 mWcm^?2 and 173 mWcm^?2, respectively. Moreover, a new titanium bipolar plate design providing high specific power density is also presented.     

Parameter characterization of HTPEMFC using numerical simulation and genetic algorithms

This paper develops a novel approach to the parameterisation of high temperature exchange membrane fuel cells (HTPEMFC) with limited and non-invasive measurements. The proposed method allows an effective identification of electrochemical parameters for three-dimensional fuel cell models by combining computational simulation tools and genetic algorithms. To avoid each evaluation undertaken by the optimisation method involving a complete computational simulation of the 3D model, a strategy has been designed that, thanks to an iterative process, makes it possible to decouple the fluid dynamic resolution from the electrochemistry one.Two electrochemical models have been incorporated into these tools to describe the behaviour of the catalyst layer, Butler-Volmer and spherical aggregate. For each one, a case study has been carried out to validate the results by comparing them with empirical data in the first model and with data generated by numerical simulation in the second. Results show that, from a set of measured operating conditions, it is possible to identify a unique set of electrochemical parameters that fits the 3D model to the target polarisation curve. The extension of this framework can be used to systematically estimate any model parameter in order to reduce the uncertainty in 3D simulation predictions.     

Process knowledge-based random forest regression for model predictive control on a nonlinear production process with multiple working conditions

In process industry, predictive control approaches have been widely used for nonlinear production processes. Practically, the predictor in a predictive controller is extremely important since it provides future states for the optimization problem of controllers. The conventional predictive controller with precise mathematical predictors approximating the state space of physical systems is difficult and time-consuming for nonlinear production processes, and it performs poorly over a wide range of working conditions and with significant disturbances. To address the challenges, the trend of applying artificial intelligence emerges. However, the industrial process-specific knowledge is ignored in most cases. In this study, a predictive controller with a control process knowledge-based random forest (RF) model is proposed. Specifically, working data are clustered at first to handle diverse working conditions. Then, a process knowledge-based forest predictor, namely MIW-RF model with a redesigned cascading RF structure, is proposed to incorporate control process knowledge into modeling. Thus, future states of controlled variables could be more accurately acquired for the optimizer. A simplified version of the predictive model is also developed with quick model training and updating. The proposed predictive methods are finally introduced into the controller design. According to the empirical results, the proposed methods deliver a better control performance against benchmarks, including more accurate anticipated controlled-variable responses, better set-point tracking and disturbance rejection capability.     

基于多通道的ICU脑血管疾病死亡风险预测模型

死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患，通过死亡风险预测可以有针对性地对病人做出临床诊断，以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表，针对ICU病人临床监测的17项生理参数，提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型，用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库，从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究，除了六组超参数实验之外，将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归（logistic regression）和支持向量机（support vector machine, SVM）四种模型进行了对比分析，准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标，实验结果表明，所提模型性能优于其他模型，AUC值达到94.3%。     

Three-dimensional and anisotropic numerical analysis of a PEM fuel cell

In this study, the effects of cell temperature and relative humidity on charge transport parameters are numerically analyzed. In order to perform this analysis, three-dimensional and anisotropic numerical models are developed. The numerical models are integrated into the experimental values for anisotropic electrical conductivities, as depending on cell temperature and relative humidity, that were obtained from our previous study. The achieved results indicate that the values of current densities in the in-plane direction increase with increasing cell temperature and relative humidity, while the current densities reach a maximum in the rib regions for both the numerical model at the through-plane direction. The behaviors of electrolyte potentials are similar with changes in the cell temperature and relative humidity. In addition, the cathode electrical potentials in both the in-plane direction and through-plane direction do not change to a considerable amount with increasing cell temperature and relative humidity.