High temperature proton exchange membrane fuel cells (HT-PEMFCs) are one of the promising alternatives of power production in which chemical energy is converted to electrical energy. Various ...analytical, numerical and system-level models have been developed over the past two decades. These models were beneficial in the investigation of various areas such as fundamental analysis of transport phenomena, process and geometrical optimization, system level integration of HT-PEMFCs etc. Thus, the objective of this review is to summarize the present status of the HT-PEMFC modelling efforts which can aid future researchers in this field of research. Furthermore, areas where more research efforts could be channelled towards are also highlighted.
•Over 150 HT-PEMFC models were reviewed and categorised based on a purpose oriented perspective.•Detailed description of existing models and their purposes with respect to the current status of modelling are given.•Potential areas of research are highlighted.
A comprehensive review of the hydrogen storage systems and investigations performed in search for development of fast refueling technology for fuel cell vehicles are presented. Nowadays, hydrogen is ...considered as a good and promising energy carrier and can be stored in gaseous, liquid or solid state. Among the three ways, high pressure (such as 35 MPa or 70 MPa) appears to be the most suitable method for transportation due to its technical simplicity, high reliability, high energy efficiency and affordability. However, the refueling of high pressure hydrogen can cause a rapid increase of inner temperature of the storage cylinder, which may result not only in a decrease of the state of charge (SOC) but also in damages to the tank walls and finally to safety problems. In this paper, the theoretical analysis, experiments and simulations on the factors related to the fast refueling, such as initial pressure, initial temperature, filling rate and ambient temperature, are reviewed and analyzed. Understanding the potential relationships between these parameters and the temperature rise may shed a light in developing novel controlling strategies and innovative routes for hydrogen tank fast filling.
•Three hydrogen storage systems were presented. Effects of thermo-mechanical were reviewed.•The thermodynamic mechanism of temperature rise and theoretical analysis were reviewed.•The experiments and simulations on fast and safe hydrogen refuelling were summarized.•CFD models on the flow field and temperature field were summarized.•Three safe and fast filling strategies were proposed.
Bipolar plate (BP) in proton exchange membrane (PEM) fuel cells provides conducting paths for electrons between cells, distributes and blocks the reactant gases, removes waste heat, and provides ...stack structural integrity. It is a key component to ensure the aforementioned functions while maintaining a low cost of fuel cell stack. This paper presents a comprehensive review about the BP materials (metallic, non-porous graphite and composite materials) and the corresponding fabrication methods, flow field layouts, and PEM fuel cells applications. Among the materials, the metallic BP has attracted high attention in automotive application due to its superior mechanical and physical properties, competitive cost compared with non-porous graphite and composite materials, but the fabrication technology and corrosion resistance are the major concerns for metallic bipolar plates. In recent studies, the protective coatings reported such as the conductive polymer, metal nitride/carbide and noble coatings have become the hot topics. They have been widely applied in different kinds of metallic bipolar plates, and the metal nitride coatings exhibit relatively low corrosion current and moderate interfacial contact resistance in comparison to other coatings. In future, developing excellent corrosion resistance and electrical conductivity coatings or novel metallic materials for bipolar plates will greatly enhance PEM fuel cells application in transportation field.
•Three kinds of bipolar plates materials and the corresponding fabrication methods are reviewed.•Different kinds of protective coatings for metallic bipolar plates are presented.•The recent studies about flow fields design for better water removal are summarized.•The applications of PEM fuel cells with different bipolar plates materials are reviewed.
The evaluation of pilots' fatigue status is of substantial significance in aviation safety, which faces two major issues. They are how to get the fatigue status feature representation and how to ...identify the fatigue behavior status of pilots via electroencephalogram (EEG) signals. To solve the first issue, we propose a novel fatigue evaluation index via different window functions to compute the power spectrum of relative rhythms from EEG signals. Wavelet packet transform is used to decompose EEG signals from pilots to form four major rhythms, i.e., <inline-formula> <tex-math notation="LaTeX">\boldsymbol {\delta } </tex-math></inline-formula> wave, <inline-formula> <tex-math notation="LaTeX">\boldsymbol {\theta } </tex-math></inline-formula> wave, <inline-formula> <tex-math notation="LaTeX">\boldsymbol {\alpha } </tex-math></inline-formula> wave, and <inline-formula> <tex-math notation="LaTeX">\boldsymbol {\beta } </tex-math></inline-formula> wave, and the combined representation of their power spectrum curve area is the features of pilots' mental status. To solve the second issue, we propose a new deep contractive autoencoder (AE) network with a softmax (SM) classifier to detect the multistatuses of mental fatigue workload. The recognition results of our model are also compared with that of other models such as the deep AE network with a SM classifier model. The experimental results show that our deep learning model has superior classification performance, and the recognition accuracy of fatigue mental status is up to 91.67%, which shows that the proposed method performs excellently compared with the state-of-the-art methods.
•Real and effective test data are adopted.•Combined with dimensionality reduction clustering algorithm, the error caused by inconsistent vehicle operating conditions is eliminated to a certain ...extent.•It more accurately shows the deterioration of fuel cell performance.
Accurate perception of the performance degradation of fuel cell is very important to detect its health state. However, inconsistent operating conditions of fuel cell vehicles in the test result in errors in the data. In order to obtain a more credible degradation rate, this study proposes a novel method to classify the experimental data collected under different working conditions into similar operating conditions by using dimensionality reduction and clustering algorithms. Firstly, the experimental data collected from fuel cell vehicles belong to high-dimensional data. Then projecting high-dimensional data into three-dimensional feature vector space via principal component analysis (PCA). The dimension-reduced three-dimensional feature vectors are input into the clustering algorithm, such as K-means and density-based noise application spatial clustering(DBSCAN). According to the clustering results, the fuel cell voltage data with similar operating conditions can be classified. Finally, the selected voltage data can be used to precisely represent the true performance degradation of an on-board fuel cell stack. The results show that the voltage using the K-means algorithm declines the fastest, followed by the DBSCAN algorithm, finally the original data, which indicates that the performance of the fuel cell actually declines faste. Early intervention can prolong its life to the greatest extent.
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Battery management systems (BMSs) play a critical role in electric vehicles (EVs), relying heavily on two essential factors: the state of charge (SOC) and state of health (SOH). However, accurately ...estimating the SOC and SOH in lithium-ion (Li-ion) batteries remains a challenge. To address this, many researchers have turned to machine learning (ML) techniques. This study provides a comprehensive overview of both BMSs and ML, reviewing the latest research on popular ML methods for estimating the SOC and SOH. Additionally, it highlights the challenges involved. Beyond traditional models like equivalent circuit models (ECMs) and electrochemical battery models, this review emphasizes the prevalence of a support vector machine (SVM), fuzzy logic (FL), k-nearest neighbors (KNN) algorithm, genetic algorithm (GA), and transfer learning in SOC and SOH estimation.
•A review of design and optimization of fuel cell power systems and hybrid power system for extending UAVs endurance.•The data-driven models with artificial intelligence (AI) are promising in ...intelligent energy management.•The selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV.
The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight; hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell, battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.
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The water issue of high-temperature proton exchange membrane fuel cell (HT-PEMFC) is rarely studied in the previous work. However, the different water vapor behaviors might greatly influence both ...cell performance and stability. In order to gain a fundamental understanding of the vapor behaviors in HT-PEMFC, a 3D computational fluid dynamics model and a 2D transient model were developed to investigate the effects of materials properties and operating parameters on the vapor behavior. Temperature, membrane materials, and phosphoric acid doping degrees are examined. The results show that higher temperature and phosphoric acid doping degrees with PBI membrane would lead to a significant increase of water vapor generation at cathode. For the transient model, the dynamics of vapor accumulation were observed with the dead-end anode. It is revealed that vapor transport and distribution get adapted to a dynamic equilibrium after 18 sec. According to these results, a periodic purging at anode with optimized purging time is still needed to remove the accumulated water vapor. The findings of this paper can be further applied in the design of fuel cell controller.
Ambient temperature affects the performance of a battery power system and its accuracy in state-of-charge (SOC) estimation for electric vehicles and smart grid systems. This paper proposes a battery ...model that considered ambient temperature, cell temperature, hysteresis voltage and thermal aging on capacity due to multiple charging and discharging. The SOC is then estimated using an extended Kalman filter. Several forms of validation were tested on an actual cell battery under specific ambient temperatures to verify the battery cell model, terminal voltage and SOC estimation performance. The SOC estimation results show an improvement in root-mean-squared error as compared to Extended Kalman Filter (EKF) without considering the temperature dependency. The proposed battery temperature-dependent model gave a smaller root-mean square error in SOC and terminal voltage at 5 °C, 15 °C and 45 °C.
This paper investigates the start-up or warm-up process of a high-temperature proton exchange membrane fuel cell (HT-PEMFC) from room temperature to a desired temperature of ∼180 °C. The heating ...strategy considered in this study involves an initial heating of the HT-PEMFC by a process referred to as inlet gas heating to a temperature above 100 °C. After the fuel cell reaches above 100 °C, a voltage is applied, where electrochemical reaction heating is expected to contribute to the heating process. Thus, a numerical transient non-isothermal three-dimensional model is derived to mimic the start-up process. Operational parameters such as anode inlet temperature, cathode inlet temperature, applied voltage and voltage application temperature are varied and their effects on the maximum temperature in the membrane electrode assembly (MEA) and temperature difference in the MEA are studied. Firstly, the distribution of temperature along the channel length indicates an increase of temperature during gas heating and as the voltage is applied at the voltage application temperature, the temperature increases at the centre of the MEA due to exothermic reactions. The two-dimensional temperature distribution indicates a temperature difference between the centre of the MEA and the regions below the bipolar plate where the temperature is relatively lower. Considering the whole start-up process with respect to time, the temperature difference exists throughout the process. This will be the key focus in the parametric study. The parametric study indicates that the inlet gas temperatures, applied voltage and the voltage application temperature affect the maximum temperature in the MEA and most importantly, the temperature difference in the MEA. This can cause thermal stresses to build-up if the increase rate of temperature difference is excessive. Setting the applied voltage high (thus, lower current density) is necessary to reduce the increase rate of temperature difference.
•Temperature difference at short time period during applied voltage is observed.•Lower applied voltage increases the rate of temperature difference w.r.to time.•Temperature difference is not affected by gas and voltage application temperatures.
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