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Fuel cell vehicles have always garnered a lot of attention in terms of energy utilization and environmental protection. In the analysis of fuel cell performance, there are usually some outliers present in the raw experimental data that can significantly affect the data analysis results. Therefore, data cleaning work is necessary to remove these outliers. The polarization curve is a crucial tool for describing the basic characteristics of fuel cells, typically described by semi-empirical formulas. The parameters in these semi-empirical formulas are fitted using the raw experimental data, so how to quickly and effectively automatically identify and remove data outliers is a crucial step in the process of fitting polarization curve parameters. This article explores data-cleaning methods based on the Local Outlier Factor (LOF) algorithm and the Isolation Forest algorithm to remove data outliers.

In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement. The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution.

Water content estimation is a key problem for studying the PEM fuel cell. When several hundred fuel cells are connected in serial and their active surface area is enlarged for sufficient power, the difference between cells becomes significant with respect to voltage and water content. The voltage of each cell is measurable by the cell voltage monitor (CVM) while it is difficult to estimate water content of the individual. Resistance of the polymer electrolyte membrane is monotonically related to its water content, so that the new online high frequency resistance (HFR) measurement technique is investigated to identify the uniformity of water content between cells and analyze its sensitivity to operating conditions in this paper. Firstly, the accuracy of the proposed technique is experimentally validated to be comparable to that of a commercialized electrochemical impedance spectroscopy (EIS) measurement equipment.

Exhaust gas recirculation technology is one of the main methods to reduce engine emissions. The pressure of the intake pipe of turbocharged direct-injection diesel engine is high, and it is difficult to realize EGR technology. The application of Venturi tube can easily solve this problem. In this paper, the working principle of guide-injection Venturi tube is introduced, the EGR system and structure of a turbocharged diesel engine using the guide-injection Venturi tube are studied. According to the working principle of EGR system of turbocharged diesel engine, the model of guide-injection Venturi tube is established, the calculation grid is divided, and it is carried out by using Computational Fluid Dynamics method that the three-dimensional numerical simulation of the internal flow of Venturi tube under different EGR rates injection.

Fuel cells’ soft output characteristics and mismatched voltage levels with subordinate electrical devices necessitate the use of DC/DC converters, which are an important part of the power electronic subsystem of the fuel cell system. The staggered parallel Boost topology is commonly employed in fuel cell DC/DC converters. This paper focuses on the control characteristics of the two-phase interleaved parallel Boost topology in the context of a fuel cell system. Specifically, we derive the small-signal model and output-control transfer function of the topology, and design a controller based on frequency characteristic analysis. Our proposed controller uses a cascaded double-ring structure and supports both constant current and constant voltage switching modes. To evaluate the effectiveness of our proposed control strategy, we conduct simulation and prototype testing.

To study the state of health (SOH) of the proton exchange membrane fuel cell (PEMFC), a novel hybrid method combining the advantages of both the model-based and data-driven methods is proposed. Firstly, the model-based method is proposed based on the voltage degradation model to estimate the variation trend, and three parameters reflecting the performance degradation are selected. Secondly, the data-driven (long short-term memory (LSTM)) method is presented to estimate the variation fluctuation. Moreover, the core step of the hybrid method is returning the results of the LSTM method to the power degradation model as the “observation” and modifying related parameters to improve the estimation accuracy. Finally, the sliding window method is applied to solve the problem of the data increase with the increase of the operating time. The results show that the power estimation is better than the current estimation for the SOH estimation.

To improve the prediction accuracy of the remaining useful life (RUL) of the proton exchange membrane fuel cell (PEMFC), an integrated health index (IHI) including electrical and non-electrical parameters of PEMFC is established, and the RUL prediction is conducted based on the above index. Firstly, several operating conditions including the PEMFC degradation information are selected according to the information theory method. Moreover, the IHI is established by the sequential quadratic programming method. Secondly, RUL predictions based on the power and IHI are conducted by the adaptive neuro fuzzy inference system (ANFIS), respectively. Finally, different results comparisons including power and IHI differences, differences between experimental and training/predicting results, amounts of different differences in training and predicting phases, and RUL prediction results are presented in detail.

The acoustic muffler is one of the practical solutions to reduce the noise in ducts. The acoustic and aerodynamic performances are two critical indices of one muffler for the air intake system of a hydrogen fuel cell electric vehicle (FCEV). In this study, the concept of phononic crystal is applied to design the muffler to obtain superior acoustic performance. One duct with periodic and compact resonator-type mufflers is designed for broadband noise attenuation. The two-dimensional (2D) transfer matrix method and bandgap theory are employed to calculate the transmission loss (TL) and acoustic bandgap. It is numerically and theoretically demonstrated that broadband noise attenuation could be acquired from 500Hz to 3500Hz. Afterwards, the three-dimensional (3D) computational fluid dynamics (CFD) approach is applied to predict the pressure distribution. The results indicate that the proposed hybrid muffler and the phononic crystal duct possess low pressure loss values.

Electric centrifugal air compressor is one of the most important auxiliary components for the fuel cell engine, which has great impacts on the system efficiency, cost and compactness. However, the centrifugal compressor works at an ultra-high speed for a long time, which poses a great challenge to the lives of motor, bearing and seal. Therefore, reducing the rotating speed of the impeller and maintaining high pressure ratio and high efficiency are important issues for aerodynamic design of the compressor. In this paper, a centrifugal compressor rotor for a 100kW fuel cell system is designed. Aiming at reducing the rotating speed, the influences of three key structural parameters including inlet blade angle, outlet blade angle and blade outlet radius on performance are investigated. The aerodynamic performance of the compressor is predicted using the Reynolds-averaged Navier-Stokes (RANS) equations with computational fluid dynamic (CFD) tools.

With the continuous upgrading of emission regulations, NOx emission limit is becoming more and more strict, especially in the cold start phase. Passive NOx absorber (PNA) can adsorb NOx at a relatively low exhaust temperature, electrically heated catalyst (EHC) has great potential to improve exhaust gas temperature and reduce pollutant emissions of diesel engines at cold start conditions, while experimental research on the combined use of these two kinds of catalysts and the coupling mode of the electrically heated catalyst and the aftertreatment system under the cold start condition are lacking. In this paper, under a certain cold start and medium-high temperature phase, the exhaust gas temperature and emission characteristics of PNA, EHC and aftertreatment system under different coupling modes were studied.

The temperature management of the proton exchange membrane fuel cell cooling system is very important to the stability and life of the engine. The size and cycle switching of the cooling system and the rapid temperature rise of the system are inseparable from the thermostat. In this paper, a simulation model of the fuel cell cooling system is built for a 30KW fuel cell system, and its accuracy is verified by experiments. The temperature fluctuation of the system in the confluence mode is mainly studied, and the error is about 0.9 °C. The influence of the converging mode of the thermostat on the temperature of the cooling system is researched through the simulation platform. Based on the simulation model, the influence of thermostats with different external environments and opening degrees on the size cycle switching of cooling system is predicted, which provides optimization and guidance for the system control strategy.

China VI emission standards (Limits and measurement methods for emissions from diesel fueled heavy-duty vehicles, China VI, GB17691-2018) have strict particle number (PN) emission standards and so the coated diesel particulate filter (DPF) technology from the EU and US market has challenge in meeting the regulation. Hence, a coated DPF with higher PN filtration efficiency (FE) is required. Currently, there are two approaches. One is from the DPF substrate standpoint by using small pore size DPF substrate. The other is from the coating side to develop a novel coating technology. Through the second approach, a layer coating process has been developed. The coated DPF has an on-wall catalytic layer from inlet side and an in-wall catalytic coating from outlet side. The DPF has improved PN filtration efficiency and can meet China VI regulation without any pre-treatment. It has lowered soot loading back pressure (SLBP), compared to the DPF with small pore size.

The catalyzed diesel particulate filter with Pt and Pd noble metals as the main loaded active components are widely used in the field of automobile engines, but the high cost makes it face huge challenges. Rare earth element doping can improve the soot oxidation performance of the catalyzed diesel particulate filter and provide a new way to reduce its cost. In this paper, thermogravimetric tests and chemical reaction kinetic calculations were used to explore the effect of Pt-Pd catalysts doped Ce, and La rare earth elements on the oxidation properties of soot. The results shown that, among Pt-Pd-5%Ce, Pt-Pd-5%La, and Pt-Pd-5%Ce-5%La catalysts, Pt-Pd-5%La catalyst has the highest soot conversion, the highest low-temperature oxidation speed, and the activation energy is the smallest. Compared with soot, this catalyst reduced T10 and T20 by 82% and 26%, respectively, meaning the catalytic activity of Pt-Pd-5%La catalyst was the best.

Proton exchange membrane fuel cells (PEMFC) are considered an environment-friendly alternative vehicle power in the future owing to their high power density and zero-carbon emission. To research the performance of the air supplied by the PEMFC air system, the PEMFC air system bench composed of an air compressor, cooler, emulated stack, back-pressure valve, and sensors was built. Then, a PEMFC system test bench composed of a hydrogen supply subsystem, stack, air supply subsystem, electronic control subsystem, and cooling subsystem was established. The fuel cell system control parameters and control method are complex due to the coupling and nonlinearity of the air supply system. The strategy composed of a feedforward table and piecewise proportional integral (PI) feedback control strategy was employed to regulate the pressure and flow rate of the air supply system.

Gas diffusion layer (GDL), as a critical constituent of the proton exchange membrane fuel cell (PEMFC), plays a key role in mass, heat, electron, and species transport. GDL generally has two distinct layers: a macro-porous substrate (MPS) and a micro-porous layer (MPL). The fibers in MPS and the cracks formed during the deposition process on the surface of MPL change the overall transport capacity and effect the output performance of PEMFC. In this paper, methods of identifying the structural features of fibers and cracks in GDL images based on artificial intelligence are proposed. The block probabilistic Hough transform and the quadric voting based on the weighted K-means algorithm are programmed to realize the fiber feature extraction, and the crack feature extraction is realized by the regional connectivity algorithm and the geometric feature calculation based on the circumscribed graph of the crack region.

The hydrogen supply integrated subsystem is an important part of the proton exchange membrane fuel cell system. In the multi-stack fuel cell system, the optimal design and integration of the hydrogen supply subsystem have great influence on the whole system structure. In this paper, a fuel cell hydrogen integration subsystem with two hydrogen cycle structures is established based on an optimized split-stack approach. Firstly, the matching of hydrogen subsystem is carried out on the basis of multi-stack fuel cell optimization. Then, the structure of the gas buffering and distribution device and the gas circulation device is optimized considering the gas circulation and the diversity of the equipment, and two solutions are proposed: the separate circulation structure (Structure I) and the common circulation structure (Structure II). Finally, the multi-stack fuel cell system is built by MATLAB/Simulink software and simulated under the condition of step and C-WTVC.

Fuel cell electric vehicles (FCEVs) require multiple components to operate properly, and the fuel cell stack—the source of power—is one of the most important components. While the number of enterprises manufacturing and selling fuel cell stacks is increasing globaly year after year, the residual challenges of core components and technologies still need to be resolved in order to keep pace with the development of lithium-ion batteries (i.e., its primary competitor). Additionally, many production and distribution standards are seen as unsettled. These barriers make large-scale commercialization an issue. Use of Proton-exchange Membrane Fuel Cells in Ground Vehicles explores the opportunities and challenges within the PEMFC industry. With the help of expert contributors, a critical overview of fuel cells and the FCEV industry is presented, and core technology, applications, costs, and trends are analyzed.

Durability performance prediction is a critical issue in fuel cell research. During the demonstration operation of fuel cell commercial vehicles in China, this issue has attracted more attention. In this article, the long short-term memory neural network (LSTMNN), which is an improved recurrent neural network (RNN), and the demonstration operation data are used to establish the prediction model to predict the durability performance of the fuel cell stack. Then, a model based on a back-propagation neural network (BPNN) is established to be a control group. The demonstration operation data is divided into training group and validation group. The former is used to train the prediction model, and the latter is used to verify the validity and accuracy of the prediction model. The outputs of the prediction model, as the durability performance evaluation indexes of the fuel cell, are the polarization curve (current-voltage curve) and the voltage decay curve (time-voltage curve).

The temperature of proton exchange membrane fuel cell (PEMFC) is the key factor restricting fuel cell’s performance. A deep understanding of temperature on stack voltage consistency and transient characteristics is necessary for improving the output performance of fuel cell. In this paper, the variation trend of consistency and transient characteristics of 20kW PEMFC stack at different temperatures is studied by experiment. In consistency, the amplitude of voltage changes and voltage difference (voltage coefficient variation σV) under different thermal loading conditions is examined. In transient characteristics, discussing the trends of transient voltage at different thermal loading. As the result, once the stack temperature increases from 65 °C to 70 °C, the stack performance and dynamic response are significantly improved, which may be caused by the rise in temperature promoting the establishment of the internal quality transmission channel.

Ethanol reforming gas combined with EGR technology can not only improve thermal efficiency, but also reduce pollutant emission under lean combustion condition. In this investigation, GT-Power is used to carry out one-dimensional simulation model calculation and analysis to explore the combustion characteristics, economy performance of a direct injection gasoline engine when the excess air coefficient (λ) increases from 1 to 1.3 and the ethanol reforming gas mixing ratio increases from 0% to 30% at the working condition of 2000 r/min and 10 bar. Then the EGR system is introduced to deeply discuss the working characteristics of the direct injection gasoline engine when the EGR rate increases from 0% to 20%. The results show that the increase of λ leads to the decrease of in-cylinder pressure and the delay of the peak of cylinder pressure.