PEM System Research Articles

Research and Development Practices within PEM Water Electrolyzer Manufacturing to Support a Circular Economy

Nel Hydrogen has in the last decades substantially invested in R&D efforts to consolidate next-generation PEM stacks and systems towards a commercial pathway for these devices at scale. These innovative tasks have allowed the company to reach much lower values for levelized costs of hydrogen (LCOHs) supported by devices that are much more efficient and lower costs; but that still holds robustness and long-life characteristics. However, to truly represent a sustainable pathway, the production lifecycle needs to be considered, especially related to critical materials such as catalysts and polyfluorinated alkyl substances (PFAS) used for instance in the membranes. PFAS are beginning to be regulated globally, with a goal of for responsible manufacturing and hence zero disposal to the environment. Recycling programs for the polymers used in electrolyzers can assist in keeping them exempt from PFAS regulations, due to the minimized environmental impact and lack of related emissions. In addition, PEM electrolyzers use a significant amount of platinum group metals (PGMs), including iridium, one of the scarcest naturally occurring elements. Addressing these issues through recycling and a healthy circular economy of these key components is an important part of large-scale commercialization and deployment.Recent customers have already raised questions about supplier philosophy and documentation of environmental practices. In other words, these large-scale market players are looking for instance to be ISO14001 certified; designed to minimize a company’s negative impact on the environment. While recycling of any chemicals is not specifically required by ISO14001, the standards include lifecycle assessments, integration of environmental aspects into product design, reduction of greenhouse gas emissions, and related topics where recycling would have positive impact on the metrics.At the last 244th ECS meeting in Gothenburg 2023, we have shown how recycling (or PGM thrifting) is ultimately required to meet the IEA projected capacity demands for electrolyzers by 2050, or around 2500 GW globally. Our analysis has demonstrated that above 40% market share can be reached by 2050 for PEM electrolysis, proven that: 1)20% annual Iridium production (ca. 8 tons/year) is allocated for PEM electrolyzer manufacturing; 2) significant PGM thrifting (above 80%) is demonstrated for these devices; 3) life-time and robustness of these new low loading electrodes are maintained; and 4) a circular economy (responsible recycling) is stablished. Repurposing other components such as titanium, stainless steel, and fluoropolymers provides some additional value stream from reclamation as well. For maximum benefit, material collection methods need to be set up within the manufacturing facility, to capture waste materials and scrap, as well as through the field population, so that systems no longer being operated can be reclaimed for materials. This talk will cover some of the business considerations for effective recycling, as well as current practices.

A comparative analysis of the economic feasibility of reversible hydrogen systems based on time-resolved operation optimisation

The expansion of fluctuating renewable energy production, such as wind and PV, increases the mismatch to consumption. Power-to-Hydrogen-to-Power (PtHtP) systems are believed to be a key for balancing under and overproductions. PtHtP systems can provide temporal and spatial flexibilities and among them reversible solid oxide cells (rSOC) are a promising technology. They combine production of hydrogen and power in the same electrochemical stack. This generates a financial and environmental benefit since less resources are necessary for enabling both Power-to-Hydrogen and Hydrogen-to-Power. This work investigates the application of rSOC systems in comparison to reversible PEM systems consisting of electrolysis and fuel cell unit. In the present studies time-resolved optimization is employed for simulation of the optimal operation of the PtHtP technologies in different market price conditions for electricity, hydrogen and natural gas and with coupling to industry and district heat. Both systems have a zone of market prices, that allows for a positive economic performance over lifetime. The electricity‑hydrogen price difference in this zone is in the range from −83 €/MWh to 133 €/MWh depending on the scenario. Furthermore, the electricity price fluctuations are found to have the major impact on the profitability. By studying the influence of gas grid fees, one finds that local compressed hydrogen storages can be used only for very short storage timescales up to a few hours. Finally, the derivation of application conditions, that are suitable for the two different spatial kinds of reversible hydrogen systems – spatially concentrated and delocalized and the two technologies – rSOC and PEM, is made.

Processing and surface modification of titanium open cell porous structures for PEM fuel cell bipolar plates

Bipolar plate (BP) and porous transport layer (PTL) materials and designs are critical for the performance of a proton exchange membrane fuel cell (PEMFC) and electrolyser (PEMEC) due to their role as fluid distributor and electron transporter between cells. Designs based on open cell porous structures require a good control on the porosity features. The aim of this work is to use powder metallurgy to manufacture titanium porous structures and the use of suitable surface modification techniques that can improve the performance of the PEM systems, focusing on fuel cells. Using the space holder method, porous structures of up to 63% porosity and controlled pore size can be processed to tailor the characteristics for an optimal design and, through a simple gas nitriding treatment, the performance of the material in terms of interfacial contact resistance (below 10 mΩcm2 after corrosion) and corrosion resistance (below 1 μAcm−2) are improved for both dense and porous structures.

Benchmarking of Heuristic Algorithms for Energy Router-Based Packetized Energy Management in Smart Homes

This article presents an ER-based PEM strategy for PV integrated smart homes to jointly optimize their load scheduling delays, energy transactions cost, and battery degradation cost. The proposed approach incorporates a MA case, where, the ER acts as a main selecting agent realized by all other system elements. This leads to a combinatorial optimization problem, which can be effectively solved by heuristic optimization methods (HOMs), namely, genetic algorithm (GA), binary particle swarm optimization (BPSO), differential evolution (DE) algorithm, and harmony search algorithm (HSA). Specifically, we investigate the impact of the hyperparameters of the HOMs on the designed ER-based PEM system. Simulations are carried out for multiple smart homes under varying weather conditions to evaluate the effectiveness of HOMs in terms of selected performance metrics. Results show that the ER-based PEM reduces the average aggregated system cost, ensures economic benefits by selling surplus energy, while meeting customers energy packet demand, satisfying their quality-of-service, and operational constraints.

Benchmarking Molybdenum-Based Materials as Cathode Electrocatalysts for Proton Exchange Membrane Water Electrolysis: Can These Compete with Pt?

Proton exchange membrane water electrolysis (PEMWE) is a promising technology to produce high-purity renewable hydrogen gas. However, its operation efficiency is highly dependent on the usage of expensive noble metals as electrocatalysts. Replacing, decreasing, or simply extending the operational lifetime of these precious metals have a positive impact on the hydrogen economy. Mo-based electrocatalysts are often praised as potential materials to replace the Pt used at the cathode to catalyse the hydrogen evolution reaction (HER). Most electrocatalytic studies are performed in traditional three-electrode cells with different operational conditions than those seen in PEM systems, making it difficult to predict the expected material’s performance under industrially relevant conditions. Therefore, we investigated the viability of using three selected Mo-based nanomaterials (1T′-MoS2, Co-MoS2, and β-Mo2C) as HER electrocatalysts in PEMWE systems. We investigated the effects of replacing Pt on the catalyst loading, charge transfer resistance, kinetics, operational stability, and hydrogen production efficiency during the PEMWE operation. In addition, we developed a methodology to identify the individual contribution of the anode and cathode kinetics in a PEMWE system, allowing to detect the cause behind the performance drop when using Mo-based electrocatalysts. Our results indicate that the electrochemical performance in three-electrode cells might not strictly predict the performance that could be achieved in PEMWE cells due to differences in interfaces and porosity of the macroscopic catalyst layers. Among the catalysts studied, 1T′-MoS2 is truly an excellent candidate to replace Pt as an HER electrocatalyst due to its low overpotential, low charge transfer resistance, and excellent durability, reaching a high efficiency of ∼75% at 1 A cm–2 and 1.94 V. Our study highlights the importance of a continuous development of efficient noble-metal free HER electrocatalysts suitable for PEMWE systems.

Comparative optimization study of three novel integrated hydrogen production systems with SOEC, PEM, and alkaline electrolyzer

The present research conducts a comparative analysis and techno-economic optimization of three novel integrated energy systems for producing hydrogen, power, and desalinated water. These systems consist of heliostat field collectors, photovoltaic panels, a Rankine cycle, an organic Rankine cycle (ORC), and multi-effects water desalination systems. The main difference between the three proposed systems is the electrolyzer type. Three electrolyzer types are utilized: solid oxide electrolyzer cell (SOEC), polymer electrolyte membrane electrolyzer (PEM), and alkaline electrolyzer. This research aims to compare these three types of electrolyzers in an integrated system to analyze their performance from both exergy and economic viewpoint at their optimum conditions. Parametric studies on system exergy efficiency and hydrogen production rate were also conducted. The results demonstrate that in the exergy-economic optimum conditions, the exergy efficiency of the combined solid oxide system, polymer exchange membrane system, and Alkaline system are 13.15%, 13.04%, and 12.41%, respectively. As SOEC works at high temperatures, both thermal and electrical energy cooperate to produce hydrogen. Therefore, the maximum hydrogen production rate and system exergy efficiency happen in the integrated SOEC system. Although the SOEC system has the most significant cost rate of 0.9372 $/s, the most expensive hydrogen cost belongs to the PEM system with a charge of 3.54 $/kg, and the cheapest one is produced in the alkaline system at 2.94 $/kg.

(Invited) Low Temperature PEM Cells Leveraging Hydrogen and Oxygen Evolution Electrodes

Proton exchange membrane-based electrochemical devices have been growing in commercial relevance, from fuel cells for automotive and other vehicle applications to hydrogen production and energy storage applications. These membranes are highly versatile, able to operate with both vapor and liquid feed systems, different cation conductors, and with different redox chemistries such as for flow batteries. This talk will focus on electrolyzer advancements in PEM systems and related synergies with flow batteries and CO2 electrolysis, which each share an electrode with water electrolyzers.Renewable hydrogen generation is a key enabler for decarbonization. The need for a sustainable source of hydrogen has been widely recognized: carbon dioxide re-utilization requires hydrogen to make useful chemicals, and ammonia production is one of the largest industrial demands for hydrogen. Over 95% of hydrogen is currently made from fossil fuels, generating CO2 as a byproduct; this reality needs to change in order to reach sustainability. Currently, the only commercial options for hydrogen production from water are alkaline electrolysis and PEM electrolysis, which will need to be leveraged to make impact in the near term before less mature technologies like solid oxide electrolysis become viable at scale. PEM technology has considerable opportunity for cost reduction and performance improvement, based on many years of research and development in the related PEM fuel cells.To accelerate this progress in a still emerging market, enlarging the field by working in similar technology areas is helpful. Flow battery research based on hydrogen cells, such as hydrogen halide and hydrogen iron batteries, can validate low catalyst loadings for the hydrogen evolution electrode, and advance coatings for hydrogen embrittlement resistance. Similarly, carbon dioxide electrolysis involves reduction of carbon dioxide on one electrode, but splitting water to evolve oxygen at the other. As another area of research gaining significant interest, CO2 electrolysis can help enable advanced porous transport layer development and oxygen evolution catalyst advancements, and eventually help drive component volumes. In this talk, opportunities and progress benefitting these technologies will be discussed.

Multi-Dimensional Attention Based Spatial-Temporal Networks for Traffic Forecasting

Traffic flow prediction is the key problem of intelligent transportation system. Accurate prediction results are indispensable for traffic management and road planning. However, due to the complex spatial-temporal correlation of traffic flow data, including the spatial correlation and temporal correlation of adjacency, periodicity, and trend that exist between different roads. The existing forecasting methods consider the spatial-temporal correlation but lack the dynamic modeling of spatial-temporal correlation. To deal with this dynamic feature, this paper proposes a multi-dimensional attention-based spatial-temporal network (MA-STN). It mainly contains three parts, the spatial-temporal attention unit, the spatial-temporal feature extraction unit based on Graph Convolutional Network (GCN) and the fusion prediction unit, and the residual connection is also added to the model to avoid the gradient disappearance problem. Meanwhile, this paper divides the dataset into three subsets to deal with the three features in the temporal dimension separately. To verify the effectiveness of the proposed model, two real-world road traffic flow data collected by PeMS system are used for validation. By comparing six different models, the proposed network in this paper has a 7% accuracy improvement compared to the baseline model. To verify the effectiveness of the attention mechanism, ablation experiments are used in this paper for validation, and the results show that the attention mechanism can achieve a 5% accuracy improvement.

Optimum parameters extraction of proton exchange membrane fuel cells using Fractional‐Order Whale Optimization Algorithm

AbstractThis study proposes a novel metaheuristic‐based technique for optimum parameters' estimation of the proton exchange membrane fuel cells (PEMFCs). To provide better results with more reliability and accuracy, a Fractional Order‐based design of the Whale Optimizer Algorithm (FO‐WOA) is designed. A validation test showed that the proposed method provides a good trade‐off between accuracy and convergence speed. Performing the algorithm for multiple independent runs also shows that the proposed method delivers reliable results toward some other comparative metaheuristic algorithms. This algorithm is then used for the minimization of the sum of square deviation between the experimental voltage‐current polarization and the optimal achieved results by the model based on FO‐WOA. The method is validated by considering two practical case studies, which are the Nexa PEMFC and 250 W PEM system, and its achievements are put in comparison with some approaches to indicate the higher effectiveness of the proposed method toward the others. The experimental results on the Nexa PEMFC indicate that the proposed FO‐WOA‐based method with 12 sum square errors (SSE) provided the minimum error toward the other. Also, the experiments on the 250 W PEM Stack indicated that for 250 W PEM Stack with 3/5 bar and 80°C, the proposed method with 0.01 SSE provides the fittest profile with the experimental data, and finally, the experiments on the same stack with 3/5 bar and 80°C showed the higher accuracy of the proposed method with the least SSE value (0.16) toward the others.

A Feasibility Study of Photovoltaic-Electrolysis-PEM Hybrid System Integrated Into the Electric Grid System Over the Korean Peninsula.

A photovoltaic–electrolysis–PEM hybrid model was developed for a feasibility study, and simulations of several scenarios in Korea were performed. The solar irradiance was derived from the University of Arizona solar irradiance based on satellite–Korea Institute of Energy Research model which provides the satellite imagery over the Korean peninsula every 15 min. In Korea, the annual average solar irradiance is 1,310 kWh m−2 with a maximum of 1,440 kWh m−2 in 2017. Electricity load and solar irradiance information were used to test the performance model of the photovoltaic–electrolysis–PEM hybrid system for baseload and several peak load shave runs. When the baseload was set at 4200 MW, the total capacity of the Photovoltaic plants was 58.5 GWp. In contrast, the hybrid system reduced the peak load more efficiently during daytime. In particular, the capacity factor of the Proton Exchange Membrane system increased in winter because the solar irradiance is relatively weak in that season. These results provide useful insights for the development of control logic models for the PV–electrolysis–PEM system in micro-grid setups.

Scalable low-rank tensor learning for spatiotemporal traffic data imputation

Missing value problem in spatiotemporal traffic data has long been a challenging topic, in particular for large-scale and high-dimensional data with complex missing mechanisms and diverse degrees of missingness. Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data. However, despite the promising results, these approaches do not scale well to large data tensors. In this paper, we focus on addressing the missing data imputation problem for large-scale spatiotemporal traffic data. To achieve both high accuracy and efficiency, we develop a scalable tensor learning model—Low-Tubal-Rank Smoothing Tensor Completion (LSTC-Tubal)—based on the existing framework of Low-Rank Tensor Completion, which is well-suited for spatiotemporal traffic data that is characterized by multidimensional structure of location × time of day × day. In particular, the proposed LSTC-Tubal model involves a scalable tensor nuclear norm minimization scheme by integrating linear unitary transformation. Therefore, tensor nuclear norm minimization can be solved by singular value thresholding on the transformed matrix of each day while the day-to-day correlation can be effectively preserved by the unitary transform matrix. Before setting up the experiment, we consider some real-world data sets, including two large-scale 5-min traffic speed data sets collected by the California PeMS system with 11160 sensors: 1) PeMS-4W covers the data over 4 weeks (i.e., 288×28 time points), and 2) PeMS-8W covers the data over 8 weeks (i.e., 288×56 time points). We compare LSTC-Tubal with some state-of-the-art baseline models, and find that LSTC-Tubal can achieve competitively accuracy with a significantly lower computational cost. In addition, the LSTC-Tubal will also benefit other tasks in modeling large-scale spatiotemporal traffic data, such as network-level traffic forecasting.

Performance comparison of a dedicated total breast PET system with a clinical whole-body PET system: a simulation study

This paper presents a novel PET geometry for breast cancer imaging. The scanner consists of a ‘stadium’ (a rectangle with two semi-circles on opposite sides) shaped ring, along with anterior and posterior panels to provide high sensitivity and high spatial resolution for an imaging field-of-view (FOV) that include both breasts, mediastinum and axilla. We simulated this total-breast PET system using GATE and reconstructed the coincidence events using a GPU-based list-mode image reconstruction implementing maximum likelihood expectation-maximization (ML-EM) algorithm. The rear-panel is made up of a single layer of LSO crystals (3.2 × 3.2 × 20 mm3 each), while the ‘stadium’-shaped elongated ring and the anterior panel are made with dual-layered LSO crystals (1.6 × 1.6 × 6 mm3 each). The energy resolution and coincidence resolving time of all detectors are assumed to be 12% and 250 ps full-width-at-half-maximum, respectively. Various sized simulated lesions (4, 5, 6 mm) having 4:1, 5:1, and 6:1 lesion-to-background radioactivity concentration ratios, mimicking different biological uptakes, were strategically located throughout a volumetric torso phantom. We compared system sensitivity and lesion detectability of the dedicated total-breast PET system to a state-of-the-art clinical whole-body PET scanner. The mean sensitivity of the total-breast PET system is 3.21 times greater than that of a whole-body PET scanner in the breast regions. The total-breast PET system also provides better contrast-recovery coefficients for lesions of all sizes and lesion-to-background ratios in the breast when compared to a reference clinical whole-body PET scanner. Receiver operating characteristics (ROC) study shows the area under the ROC curve is 0.948 and 0.924 for the total-breast system and the whole-body PET scanner, respectively, in the detection of 4 mm diameter lesions with 4:1 lesion-to-background ratio. This study demonstrates our novel geometry can provide an imaging FOV larger than conventional PEM systems to simultaneously image both breasts, chest wall and axillae with significantly improved lesion detectability in the breasts when compared to a whole-body PET scanner.

Techno-economic assessment of a synthetic fuel production facility by hydrogenation of CO2 captured from biogas

In this study, a thermodynamic and economic analysis of a synthetic fuel production facility by utilizing the hydrogenation of CO2 captured from biogas is carried out. It is aimed to produce methanol, a synthetic fuel by hydrogenation of carbon dioxide. A PEM electrolyzer driven by grid-tie solar PV modules is used to supply the hydrogen need of methanol. The CO2 is captured from biogas produced in an actual wastewater treatment plant by a water washing unit which is a method of biogas purification. The required power which is generated by PV panels, in order to produce methanol, is found to be 2923 kW. Herein, the electricity consumption of 2875 kW, which is the main part of the total electricity generation, belongs to the PEM system. As a result of the study, the daily methanol production is found to be as 1674 kg. The electricity, hydrogen and methanol production costs are found to be $ 0.043 kWh−1, $ 3.156 kg−1, and $ 0.693 kg−1, respectively. Solar availability, methanol yield from the reactor, and PEM overpotentials are significant factors effecting the product cost. The results of the study presents feasible methanol production costs with reasonable investment requirements. Moreover, the efficiency of the cogeneration plant could be increased via enriching the biogas while emissions are reduced.

Composite polyelectrolyte multilayers for biofunctionalization of medical devices

Abstract Polyelectrolyte multilayer coatings (PEM) are prepared by alternative layer-by-layer deposition of cationic and anionic polyelectrolyte monolayers on charged surfaces. The thickness of the coatings ranges from nm to few μm. Their properties such as roughness, stiffness, surface charge and surface energy can be precisely tuned to fulfill different technical or biological requirements. The coating process is based on self-assembly of polyelectrolytes. Advantages of these coatings are their easy handling, no harsh chemistry and the possibility for coatings on complex geometries. The PEM coatings can be prepared from a variety of suitable polyelectrolytes. Their stability varies from very durable PEM coatings that are only soluble in strong solvents to quickly degradable, which may be applied as drug release system. One example of such a degradable PEM system is the one based on the polyelectrolyte pair Hyaluronan (HA) and Chitosan (CHI). These biopolymers originate from natural sources and show low toxicity towards human cells. However, HA/CHI multilayers shows only weak adhesiveness for human umbilical vein endothelial cells (HUVEC). In this article, we summarize our approaches to enhance the HA/CHI multilayer by incorporation of a non-polymer substance -graphene oxide- to improve the cell adhesion and keep such properties as low cytotoxicity and biodegradability. Different approaches for incorporation of graphene oxide were performed and the cellular adhesion was tested by metabolic assay.

Designing and analysis of the micro-trigeneration systems based on combined proton exchange membrane fuel cell with photovoltaic and photovoltaic/thermal prime movers in portable applications

Developing micro-trigeneration systems is an important step in military applications. Therefore, suggesting new portable trigeneration systems that use several energy sources is necessary. The importance of the issue is enhanced when renewable energy sources are used in suggested systems for places with no accessibility to energy sources. In this paper, different useful micro-personal trigenertion systems are proposed based on photovoltaic/thermal (PVT) and combination of photovoltaic (PV) with proton exchange membrane fuel cell (PEMFC). The proposed systems are designed to provide all or a part of personal demand loads by photovoltaic phenomena. Using different energy sources such as solar and hydrogen electrochemical energies in the proposed systems increases the flexibility and reliability of the system. The trigeneration performance of suggested cycles is simulated in the engineering equation solver software (EES) and the results based on different prime movers are compared with the system based on ultra-micro gas turbine (UMGT), which was studied in the previous work under extremely cold/hot weather. Although utilizing the PV module and PVT collector improves the performance of the system, it increases its weight as well, which is not suitable in portable applications. Therefore, the size of elements must be selected carefully. Results showed that the system based on PVT generated more power in summer so that the maximum of 105 and 17 W electrical power were generated with overall efficiency of 14% and 9% in summer and winter at maximum solar irradiance respectively. In addiotion, the most efficient system was the system based on UMGT in which the maximum overall efficiency was 21% and 28% in summer and winter respectively. The effects of the water mass flow rate of PVT on power and overall efficiency were investigated too. We found that increasing in mass flow rate increases the power and overall efficiency slightly about 16% and 15% in summer and about 33% and 25% in winter respectively. Additionally, results showed that in the combined PV-PEM system, the PV module decreased the aluminum hydride consumption significantly and generated a maximum of 13.5 W electrical power in summer. The weight of the suggested trigeneration systems is different based on different prime movers and varies from 5.66 kg to about 37.5 kg for single PEM and PVT systems respectively.

(Invited) Overcoming Technological and Economic Barriers to Generating Renewable Hydrogen with Polymer Electrolyte Membrane Electrolysis

Water electrolysis, coupled with green energy sources has long held the promise for supplanting steam methane reforming, SMR, for hydrogen generation for ammonia and petroleum refining, together contributing a billion tons of CO2/year. Additionally hydrogen can be used as a store and carrier of energy for mobile and grid applications. Wide adoption has been prevented by unacceptable costs however, both capital and operating, the latter of which is dominated by the cost of the electricity. In those industrial applications where electrolysis has found a niche it has been dominated by liquid alkaline electrolysis, due to its long history of proven durability and low cost materials. Polymer electrolyte membrane electrolysis (PEMEL) has had the potential to operate at slightly higher efficiencies, and much higher current density, while allowing high, and more importantly, differential pressure. PEMEL’s reliance on precious group metal (PGM) catalysts as well as membrane lifetime concerns have generally left them to specialty applications where footprint is a premium, such as sea and space.A number of concurrent advancements are overcoming these barriers. First, and most importantly, the cost of energy has come down faster than anyone would have predicted. This cannot be over-emphasized, as will be shown, lowering the cost of renewables has done more for green hydrogen than anything that can be achieved by electrochemical scientists and engineers, as energy costs have long dominated the cost of green hydrogen. Further lowering costs will in turn change focus to capital costs and technology opportunities. Second, improvements in membrane stability has greatly increased the durability of PEMEL systems. This has improved the lifetime of the systems while also allowing more aggressive operating conditions of higher pressure, temperature and current density. The challenges and limitations of further increasing these parameters, as well as their impact on cost will be addressed. Finally, PGM catalyst loadings continue to decrease. This reduction, as well as the increase in lifetimes allows a far greater amount of hydrogen to be generated per gram of PGM catalyst.The last great barrier for PEMEL to achieve parity with SMR, and enable hydrogen for mobility and large scale energy storage is simply scale. PEMEL, and even alkaline electrolysis are at an infancy in terms of scale. As PEM systems grow from traditional 1-100 kW systems to the 1-100 MW systems necessary for mobility, storage and industrial uses the capital costs will come down tremendously. We will look at how low these costs can go as well as consider the scarcity limitation of PGMs as PEMEL increases capacity from current output of < 100 MW/year to 10-100 GW/year necessary to make real impact in these applications.

Deep-Learning-Based Joint Optimization of Renewable Energy Storage and Routing in Vehicular Energy Network

Recent development in renewable energy-enabled electric vehicles (EVs) has posed challenges to the stability and efficiency of the vehicular energy network (VEN), which is a concrete implementation of Internet of Things (IoT) in energy and vehicular networks. In this article, we study a VEN with time-varying point-to-point traffic flow and adjustable energy storage capacity at stations. The goal is to jointly optimize the routing and dynamic storage allocation of renewable energy so as to maximize the efficiency of plant-to-station energy transferring. We first adopt a time-expanded topology graph to describe the scenario and model it as a maximum flow problem. Next, we incorporate routing in our methodology and derive a joint energy storage capacity and route planning method based on linear programming. Then, the problem is extended to a more general case, where the traffic pattern of the VEN is unknown. We apply the long short-term memory model, a deep learning method, to predict the traffic pattern and utilize the concept of reinforcement learning to iteratively improve the prediction accuracy. To evaluate the performance, we implement our method first on regular buses, then extend to EVs based on the real trace data from the PeMS system in California. The simulation results show that the joint optimization can achieve near-optimal performance and performs well even in case of high rate of missing traffic information, with the help of deep reinforcement learning.

Study on Exhaust Emission Test of Diesel Vehicles Based on PEMS

Abstract In order to study the macro-model of vehicle exhaust emissions in accordance with the national conditions of our country, this paper tests the gas emissions of three different types of diesel touring vehicles by using PEMS system, and analyzes the relationship between their emission characteristics, vehicle speed and acceleration.The results show that the emission factor has a strong positive correlation with vehicle speed and acceleration, so increasing the driving speed and reducing the acceleration frequency can effectively reduce the emission of pollutants. At the same time, the COPERT model is used to predict the emission factors. Compared with the measured values, the COPERT prediction values of each pollutant are on the low side, and the error range is 7% - 65%, which provides a theoretical basis for further exploring the applicability of COPERT model in China.

Evaluating the environmental costs in Poland of city buses meeting the Euro VI norm based on tests in real operating conditions

The article analyzes the environmental costs which consisted of determining the annual cost for gases and particles released into the atmosphere by city buses meeting the Euro VI norm. To this end, exhaust emissions of a city bus equipped with a conventional drive system were performed. The vehicle had a length of 18m and was powered by a CI engine with a swept volume of 10,5 dm3, with a maximum power of 240 kW. In order to measure the ecological indicators, tests were performed in real driving conditions using the PEMS system. The apparatus made it possible to measure the concentration of gaseous compounds and particulate matter in the exhaust, which made it possible to determine the road exhaust emissions of the tested vehicle. The research was carried out on a test route including urban and suburban roads in accordance with legislative guidelines. The measurements showed that the bus met the exhaust emission limits determined on the basis of measuring windows defined in relation to the work generated by the drive system. In addition to information on the emissivity of the vehicle, the annual emissions from city buses meeting the Euro VI standard in Poland were also estimated. The information contained in the central vehicle register for the number of vehicles registered in Poland that meet the latest emission standards has been used for this purpose.

Creating an emission model based on portable emission measurement system for the purpose of a roundabout

Road transport is the main source of pollution to the environment in urban areas; therefore, there is a need to accurately estimate the amount of exhaust gases emitted by motor vehicles. The development of systems for measuring emissions of exhaust gases caused the exit from stationary chassis dynamometers to real road test. This paper presents an analysis of emission data from the PEMS system for real driving cycles of various types of vehicles, complying with EURO2-EURO6 standards, fueled with petrol, LPG, and diesel in urban, rural, and motorway areas as well as detailing roundabouts. The results show that in the range of roundabouts, there is an increased emission of harmful exhaust components, such as CO2, THC, CO, and NOx. Due to the specific traffic conditions that prevail at the roundabout (acceleration, braking, acceleration to a certain speed), the methodology for creating an exhaust emission model for this type of objects has been proposed. Statistical analysis of the received boosted regression tree models based on the coefficient of regression, root mean square error, and mean absolute error and based on the visual assessment of the results show that the obtained models are well represented by real data. The obtained results of emission calculations on roundabouts may be used to identify areas of increased emission of harmful exhaust components, as well as an introduction to prepare new roundabout design guidelines concerning emission data.