Hydrogen Consumption Rate Research Articles

In-situ biological biogas upgrading using upflow anaerobic polyfoam bioreactor: Operational and biological aspects.

A high rate upflow anaerobic polyfoam-based bioreactor (UAPB) was developed for lab-scale in-situ biogas upgrading by H2 injection. The reactor, with a volume of 440 mL, was fed with synthetic wastewater at an organic loading rate (OLR) of 3.5 g COD/L·day and a hydraulic retention time (HRT) of 7.33 h. The use of a porous diffuser, alongside high gas recirculation, led to a higher H2 liquid mass transfer, and subsequently to a better uptake for high CH4 content of 56% (starting from 26%). Our attempts to optimize both operational parameters (H2 flow rate and gas recirculation ratio, which is the total flow rate of recirculated gas over the total outlet of gas flow rate) were not initially successful, however, at a very high recirculation ratio (32) and flow rate (54 mL/h), a significant improvement of the hydrogen consumption was achieved. These operational conditions have in turn driven the methanogenic community towardthe dominance of Methanosaetaceae, which out-competed Methanosarcinaceae. Nevertheless, highly stable methane production rates of 1.4-1.9 L CH4/Lreactor.day were observed despite the methanogenic turnover. During the different applied operational conditions, the bacterial community was especially impacted, resulting in substantial shifts of taxonomic groups. Notably, Aeromonadaceae was the only bacterial group positively correlated with increasing hydrogen consumption rates. The capacity of Aeromonadaceae to extracellularly donate electrons suggests that direct interspecies electron transfer (DIET) enhanced biogas upgrading. Overall, the proposed innovative biological in-situ biogas upgrading technology using the UAPB configuration shows promising results for stable, simple, and effective biological biogas upgrading.

Deep reinforcement learning with deep-Q-network based energy management for fuel cell hybrid electric truck

To better utilize hydrogen energy from fuel cell electric vehicles (FCEVs), an investigation is conducted into how a proton exchange membrane fuel cell (PEMFC) hybrid vehicle's 100-km hydrogen consumption rate is affected by a dynamic programming-based energy management method. The Dueling Deep Q-Network (Dueling DQN) algorithm's energy management approach is proposed. The DQN algorithm is optimized to increase the method's stability and quicken its pace of convergence. The simulation results show that the fuel economy of DQN and Dueling DQN algorithm are 94.28 % and 95.7 % respectively, both of which are improved, while the Dueling DQN algorithm converges at 480 steps higher than the DQN algorithm converges at 800 steps, and the algorithm comparison verifies the two algorithms' The validity of both algorithms was verified by algorithm comparison. In China Truck Driving Conditions (CHTC-LT), the hardware-in-the-loop simulation of CAN communication protocol using NI-PXI hardware-in-the-loop test system achieves the target vehicle speed following and verifies the real-time performance of the strategy.

Assessing the Impact of Organic Loading Rate on Hydrogen Consumption Rates during In Situ Biomethanation

Biogas upgrading via biomethanation has been extensively studied recently, but the influence of organic loading rate on process performance remains to be fully understood. This is particularly significant because both organic loading rate and hydrogen injection can lead to volatile fatty acid accumulation during anaerobic digestion. This study investigated the impact of a wide range of organic loading rates (from 1.25 to 3.25 g VS/L/d) on hydrogen consumption rates, organic acid accumulation, and microbial communities during in situ biomethanation. It also provided kinetics data and metabolite production data for different control reactors, including anaerobic digestion, ex situ biomethanation, and endogenous control reactors. Hydrogen was injected into parallel batch reactors using digestate from a semi-continuous lab-scale reactor subjected to increasing organic loading rates (1.25–3.25 g VS/L/d) as an inoculum. The inoculum was well adapted to each tested organic loading rate. The batch experiments were replicated following a 12 h hydrogen starvation period to assess the stability of hydrogen consumption rates. High organic loading rate values resulted in increased hydrogen consumption rates, peaking at 68 mg COD/L/h at an organic loading rate of 3.25 g VS/L/d (maximum value tested), with no significant organic acid accumulation despite the high hydrogen partial pressures. The hydrogen consumption rates were maintained after the starvation period. Furthermore, the addition of an organic substrate did not impact the hydrogen consumption rate (i.e., the in situ and ex situ rates were similar). A higher organic loading rate resulted in higher relative abundances of hydrogenotrophic methanogens (i.e., Methanospirillum sp.). This study highlights that increasing the organic loading rate can accelerate the rate of hydrogen consumption during in situ biomethanation, consequently reducing both capital and operational costs.

Archaeal community composition as key driver of H2 consumption rates at the start-up of the biomethanation process

The performance of hydrogen consumption by various inocula derived from mesophilic anaerobic digestion plants was evaluated under ex situ biomethanation. A panel of 11 mesophilic inocula was operated at a concentration of 15 gVS.L−1 at a temperature of 35 °C in batch system with two successive injections of H2:CO2 (4:1 mol:mol). Hydrogen consumption and methane production rates were monitored from 44 h to 72 h. Hydrogen consumption kinetics varies significantly based on the inoculum origin, with no accumulation of volatile fatty acids. Microbial community analyses revealed that microbial indicators such as the increase in Methanosarcina sp. abundance and the increase of the Archaea/Bacteria ratio were associated to high initial hydrogen consumption rates. The improvement in the hydrogen consumption rate between the two injections was correlated with the enrichment in hydrogenotrophic methanogens. This work provides new insights into the early response of microbial communities to hydrogen injection and on the microbial structures that may favor their adaptation to the biomethanation process.

Modeling and optimization of a residential PEMFC-based CHP system under different operating modes

Proton exchange membrane fuel cell (PEMFC)-based combined heat and power (CHP) system can improve the system overall efficiency. In this study, with the electrical and thermal demand curves from a survey of 500 households as the input, a residential PEMFC-based CHP system is numerically studied to explore the system operating characteristics under different operating modes, including constant-power output, electrical-led output, and stepped electrical-led output. Effects of structural and operating parameters, such as tank volume, tank temperature, PEMFC temperature, and environmental temperature, are studied. The system performance is evaluated based on CHP efficiency, matching degree, and hydrogen consumption. The results show that while the optimal CHP efficiency is higher under the constant-power output mode, the corresponding matching degree is lower and the hydrogen consumption rate is higher. A new hybrid mode is proposed to combine the advantages of different modes, achieving both higher efficiency and matching degree. Additionally, the CHP system is compared with a conventional energy supply system in terms of carbon emission and operating costs. The critical hydrogen price for a more cost-effective CHP system than the conventional system is calculated. Furthermore, a dataset is utilized to establish the relationship between CHP efficiency and key input parameters, and an artificial neural network (ANN) model is developed to predict CHP efficiency. The ANN model demonstrates a high accuracy of 98.5% and is coupled with the genetic algorithm to optimize the system, leading to the final CHP efficiency of 95.62%.

Numerical evaluation of passive autocatalytic recombiner performance under post-accident conditions

In the accident conditions, the operational behavior of passive autocatalytic recombiners (PARs) has garnered significant attention, particularly with regards to the complicated atmosphere in the containment. This paper aims to systematically study and analyze the PAR performance under post-accident conditions. CFD simulation resolving individual catalytic channels of PARs provide valuable insights into hydrogen consumption performance and temperature distribution. A simplified model of PARs, consisting of a gas channel and two catalyst plates, was developed using the CFD software STAR-CCM+. One-step reaction mechanism was used in this model to define the hydrogen consumption rate on the catalytic surface. To study the variation in gas concentration and temperature distribution, physical values of interest were extracted from designated locations. An analysis of catalyst section was conducted to provide a comprehensive understanding of the reaction process occurring within PARs. Subsequent tests were conducted using the developed simplified model to examine the effect of inlet gas components variation and operating conditions on PAR performance under post-accident conditions. Our findings show that the variation of steam concentration primarily alters the heat absorption capacity of the gas mixture, rather than the catalytic reaction rate. Furthermore, inlet velocity and operating pressure play a role in controlling the inlet mass flow rate, thereby influencing the reaction process of the gas channel by introducing varying amounts of hydrogen.

Investigation of drive cycle simulation performance for electric, hybrid, and fuel cell powertrains of a small-sized vehicle

The powertrain simulations of electric, hybrid, and fuel cell hybrid vehicles for the determination of vehicle performance and powertrain efficiency have been studied in the last few decades. Related investigations on fuel cell hybrid vehicles mainly focus on the improvement of a specific powertrain component or vehicle performance for a specific hybrid type. Therefore, this study aims to investigate the effects of not only a specific hybrid configuration but also various electric and fuel cell hybrid powertrain alternatives comparatively including fuel cell, battery, and supercapacitor as energy sources on component efficiency via drive cycle simulations depending on the same vehicle parameters and capacity of the components. Four powertrain cases that differ from each other in terms of the electric power sources (battery, supercapacitor, and fuel cell) were modeled and simulated according to the ECE-15, JPN 10–15, and WLTP drive cycle using MATLAB® - Simulink® environment. The simulations gave the power outputs of powertrain components and component efficiencies, state of charge of the battery, hydrogen consumption, and airflow rate of the fuel cell during the drive cycle. The results showed that better battery efficiency is obtained in Case-1; better vehicle range and lower battery power output than Case-1 can be achieved in Case-2; better fuel cell efficiency is obtained in Case-3; and the lowest H2 consumption is obtained in Case-4. Thus, desired powertrain performance and powertrain efficiency can be achieved by choosing the proper powertrain component in hybrid vehicles.

Experiment and simulation of hydrogen oxidation in a high-pressure turbulent flow reactor

Hydrogen oxidation has a complex dependence on pressure. Despite the well-known, reverse S-shape explosion limits, variation of hydrogen oxidation reactivity with pressure has rarely been investigated in a quantitative manner, particularly in the peninsula between the second and third ignition branches when the overall reactivity is low. This work investigates hydrogen oxidation in a turbulent flow reactor at 10 to 48 bar with an inlet temperature of 950 K and an equivalence ratio of 0.03–0.05, which complements our recent study at 1–8 bar in the same reactor (Lu et al. Proc. Combust. Inst. 2021, 243–250). The elevated pressures show a weak promoting effect, in contrast to the strong inhibiting effect at lower pressures in crossing the second ignition branch. Analyzing the hydrogen consumption rates across the pressure range revealed that the reactivity remains at a low level and is barely affected by pressure between 2 and 20 bar, suggesting the existence of a broad low-reactivity valley on the temperature–pressure plane which could be potentially important for practical applications.The measured species-time concentrations, combined with ignition delays selected from the literature, are used to develop a new hydrogen oxidation model focusing on hydrogen autoignition behavior. A comprehensive review of elementary reactions incorporating the latest updates for the rate coefficients is conducted to determine the prior uncertainties. A global optimization method incorporating random sampling and high-dimensional model representation is used to identify the most sensitive reactions and to constrain their uncertainty with the selected experimental targets. An optimized model is then obtained which shows excellent agreement with hydrogen autoignition experiments.

Energy management strategy for fuel cell vehicles via soft actor-critic-based deep reinforcement learning considering powertrain thermal and durability characteristics

Temperature can significantly affect the water equilibrium, electrochemical kinetics and mass transmission in a proton exchange membrane fuel cell (PEMFC) stack, meanwhile it also impacts the lifespan and safety of a lithium-ion battery (LIB). Yet, energy management strategy (EMS) is rarely to synchronously study the durability performances of the LIB and PEMFC stack with their thermal effects in fuel cell vehicles (FCVs) under real-world driving scenarios. Thus, this study proposes a deep reinforcement learning (DRL)-based EMS to minimize transient costs of the LIB and PEMFC stack, which include their state-of-health (SOH) descents and overtemperature penalties. Meanwhile, the transient costs are incorporated into the overall cost, which comprises the hydrogen consumption rate of the PEMFC stack, and penalty of maintaining the LIB state-of-charge (SOC). Moreover, the soft actor-critic (SAC) is applied to the DRL-based EMS due to its advantage of stability across different random environments and no meticulous hyperparameter calibration. Specifically, the proposed EMS intelligently allocates the direct current (DC) bus power of FCVs in real time to maximize a multi-objective reward in accordance with FCV states, in which the reward is the negative overall cost. Then, long-term real-world driving scenarios in Chongqing city, China, are used for off-line training and real-time control to advance the adaptability of the proposed EMS. The results show that in comparison with the deep Q-network (DQN)-based EMS considering the powertrain temperature and durability, and the SAC-based EMS neglecting the powertrain temperature and durability, the proposed strategy can actualize overall SOH increments of the powertrain up to 14.01 % and 3.45 %, respectively, and restrict the maximum temperatures of the PEMFC stack and LIB. In addition, the generalization of the proposed EMS is verified, in which the trained model of the proposed EMS is tested in other FCV and driving cycles, and it can acquire similar effectiveness. Thus, the proposed strategy can enforce the lifespan durability and thermal stability of the powertrain system.

An oil-soluble precursor with strong feedstock adaptability and excellent product selectivity for heavy oil hydrocracking

The feedstock adaptability and product selectivity of catalyst are very important for heavy oil hydrocracking. Considering that the components of heavy oil are mainly composed of aromatic compounds and alkyl compounds, Mo aryl-alkyl-dithiophosphate (Mo-Ar/R) with both benzyl and n-butyl was efficiently prepared based on the preparation method of Mo dialkyl-dithiophosphate (Mo-R) with only n-butyl whose high hydrogenation activity has been proved to improve the structural similarity to feedstock. Fourier transform infrared (FTIR) analysis, elemental analysis and oil solubility study were carried out on Mo-Ar/R and Mo-R. X-Ray diffraction (XRD), transmission electron microscope (TEM), scanning electron microscopy (SEM) and polarized microscope were used to obtain the structural and morphological information of MoS2 catalysts. Mo-Ar/R and Mo-R were evaluated in the hydrocracking of atmospheric residue ultra heavy oil (feedstock A), high sulfur vacuum residue (feedstock B) and coal tar oil (feedstock C) at 430 ℃ with an initial hydrogen pressure of 7 MPa for various reaction times, respectively. The results showed that the coexistence of benzyl and n-butyl led to better oil solubility of Mo-Ar/R, smaller size, lower stacking number and shorter slab length of the resulting MoS2 catalysts. Compared with Mo-R, Mo-Ar/R increased the valuable product yields during hydrocracking of feedstock A, feedstock C and feedstock B by 1.33 wt%, 3.53 wt% and 3.97 wt%, decreased the coke yields by 0.21 wt%, 0.40 wt% and 0.51 wt% and decreased the gas yields by 0.65 wt%, 0.97 wt% and 1.19 wt%, respectively. The initial hydrogen consumption rates and TOFs obtained in the presence of Mo-A/R are higher than that obtained in the presence of Mo-R. The performance difference between Mo-Ar/R and Mo-R seemed to be related to the contents of saturates of the different feedstocks. The coexistence of benzyl and n-butyl was proved to lead to the better feedstock adaptability and product selectivity of Mo-Ar/R compared with Mo-R due to the better structural similarity.

Optimization of Energy Saving and Fuel-Cell Durability for Range-Extended Electric Vehicle

For a fuel cell range-extended electric vehicle (FC-REEV), the fuel cell system can work at a fixed output power point, and it has high durability. However, the differences in output power and start–stop threshold can lead to a significant difference in energy loss and degradation of power sources. Based on the thermostat control strategy (TCS), the state of charge (SOC) of the battery is stabilized within a reasonable range. To obtain the lowest hydrogen consumption rate, the vehicle’s fuel economy is considered in the evaluation function. The artificial bee colony (ABC) optimization algorithm is then used to increase the driving range, and the conventional ABC-TCS (CABC-TCS) is proposed. However, the CABC-TCS leads to many start–stop times for fuel cells. To enhance the durability of the fuel cells, a penalty factor was added to the evaluation function, and a novel optimized ABC-TCS (OABC-TCS) is proposed. Different strategies were tested under federal test procedure (FTP)-72 and worldwide light-duty test procedure (WLTC) driving cycles. The results show that, compared with TCS, the optimized driving range of OABC-TCS in FTP-72 and WLTC conditions increased almost 10.59% and 10.3%. Compared with CABC-TCS, the start–stop times of OABC-TCS in FTP-72 and WLTC conditions decreased by 27.55 and 46.47 times/h, respectively.

Performance and cost of fuel cells for off-road heavy-duty vehicles

Replacing hydrocarbon-powered off-road vehicles with hydrogen fuel cell-powered off-road vehicles can reduce carbon dioxide and criteria pollutant emissions in the agriculture, construction, and mining industries. Off-road vehicles perform challenging work in harsh environments that complicate deployment of their fuel cell-powered counterparts. Customers and vehicle manufacturers recognize the health and environmental benefits of emissions reductions but are compelled by the total cost of ownership of their vehicles. This study provides a novel technoeconomic comparison of hydrogen fuel cell + battery hybrid powertrains to traditional diesel powertrains for three hallmark off-road vehicles: tractors, wheel loaders, and excavators. Performance metrics include fuel cell engine power, hydrogen consumption rate, hydrogen storage system volume, energy-regenerative drivetrain efficiency, cost of capital, operating and maintenance cost, fuel cost, and fuel storage cost. Results demonstrate that state-of-the-art fuel cell-powered wheel loaders and excavators are currently cost competitive with diesel platforms by total cost of ownership: compact wheel loaders are 19% less expensive, large wheel loaders are equally expensive, mini/compact excavators are 11% more expensive, and standard/full excavators are 9% less expensive. If targeted improvements to cost, performance, and durability of fuel cell stacks and storage systems are achieved, fuel cell systems would be cost competitive for tractors and significantly lower total cost of ownership options for wheel loaders and excavators. This study also elucidates the relationship between performance, cost, and vehicle duty cycle and provides guidance for optimal deployment of fuel cell off-road vehicles. • Performance and total cost of ownership modeling of fuel cell vehicles. • FC powertrains are currently economically viable for wheel loaders and excavators. • FC powertrains become lower cost than diesel powertrains if ultimate targets are met.

A Real-Time Rule-Based Energy Management Strategy With Multi-Objective Optimization for a Fuel Cell Hybrid Electric Vehicle

Energy management strategy (EMS) has a great impact on securing fuel cell durability, battery charge sustenance, and fuel saving in fuel cell hybrid electric vehicles (FCHEVs). This study aims to develop EMS that can be applied in real-time to satisfy above conditions. Real time power separation was performed using rule-based EMS. A genetic algorithm (GA) was implemented to calculate the optimal battery charge/discharge criterion that simultaneously satisfies the minimum hydrogen consumption rate, battery charge rate preservation, and high fuel cell efficiency. The battery charge/discharge parameter values vary according to driving patterns, and in this paper, typical suburban, urban, and highway driving conditions are considered. For the real-time application of this research method, the effectiveness was demonstrated by applying the driving conditions of unknown patterns. The effect on the initial battery SOC on EMS was analyzed, and in order to verify the superiority of this method, it was compared and analyzed with EMS results using dynamic programming and fuzzy logic under the same driving cycles. The effectiveness of this research method was verified through simulation, and it was confirmed through experiments for real-time application. Since there is a limit to the experiment using an actual fuel cell vehicle, the experiment was performed using a fuel cell and battery. This method can be applied to real fuel cell vehicles in the same way.

Research on Economic and Operating Characteristics of Hydrogen Fuel Cell Cars Based on Real Vehicle Tests

With the increase of the requirement for the economy of vehicles and the strengthening of the concept of environmental protection, the development of future vehicles will develop in the direction of high efficiency and cleanliness, and the current power system of vehicles based on traditional fossil fuels will gradually transition to hybrid power. As an essential technological direction for new energy vehicles, the development of fuel cell passenger vehicles is of great significance in reducing transportation carbon emissions, stabilizing energy supply, and maintaining the sustainable development of the automotive industry. To study the fuel economy of a passenger car with the proton exchange membrane fuel cell (PEMFC) during the operating phase, two typical PEMFC passenger cars, test vehicles A and B, were compared and analyzed. The hydrogen consumption and hydrogen emission under two operating conditions, namely the different steady-state power and the Chinese Vehicle Driving Conditions-Passenger Car cycle, were tested. The test results show the actual hydrogen consumption rates of vehicle A and vehicle B are 9.77 g/kM and 8.28 g/kM, respectively. The average hydrogen emission rates for vehicle A and vehicle B are 1.56 g/(kW·h) and 5.40 g/(kW·h), respectively. By comparing the hydrogen purge valve opening time ratio, the differences between test vehicles A and B in control strategy, hydrogen consumption, and emission rate are analyzed. This study will provide reference data for China to study the economics of the operational phase of PEMFC vehicles.

Experimental analysis of an ejector for anode recirculation in a 10 kW polymer electrolyte membrane fuel cell system

For analyzing ejector's performance in the system, an ejector for a 10 kW polymer electrolyte membrane fuel cell (PEMFC) system was first designed, manufactured, and a 10 kW PEMFC system bench was built up. A proportional valve and PI pressure feedback control method were adopted to control the hydrogen supply and anode inlet pressure. During the test, performances between dead-ended anode (DEA) mode and ejector mode were compared. Ejector's performances in the system, i.e., volume flow recirculated ratio, difference pressure, dynamic responses of primary pressure, anode inlet pressure, and recirculated gas flow rate during the purge process and current variation condition, were investigated. The results show that pressure adjustment is accurate, continuous, and fast using the proportional valve and PI pressure feedback control method. The hydrogen consumption rate in the ejector mode can reduce from 5% to 10% compared with the rate in the DEA mode except for the stack current 5 A and 10 A conditions. For better water removal out of the anode channel in ejector mode, the maximum stack power increases from 5.11 kW (DEA mode) to 9.56 kW (ejector mode). Anode pressure surge caused by the purge valve switching enhances the ejector's recirculated performance significantly.

A real-time PMP energy management strategy for fuel cell hybrid buses based on driving segment feature recognition

Establishing a reasonable energy management strategy (EMS) is the key to improve the service durability, power performance and fuel economy of the fuel cell hybrid electric vehicle (FCHEV). This paper obtains energy distribution optimal solution for the fuel cell hybrid bus (FCHB) based on Pontryagin's minimum principle (PMP) algorithm, and the problems of inaccurate estimation of motor power and difficult real-time application are solved. Firstly, the driving feature recognition is completed by collecting the motor output power directly when the FCHB stops at the station. On the basis of it, the sub-optimal co-state value is chosen. Secondly, the sub-optimal co-state is used to complete the real-time application of PMP algorithm in the driving segment. The results are acquired through the simulation and the actual comparison experiment, compared with rule-based simulation and rule-based actual experiment, the hydrogen consumption of the proposed strategy decreases by 20.3% and 28.9% on average. Moreover, the online computation time per step of the proposed strategy is 3.64 ms averagely, less than sampling time interval 1s. It is shown that the proposed method has lower hydrogen consumption rate and excellent real-time performance.

Microbial Communities in Flexible Biomethanation of Hydrogen Are Functionally Resilient Upon Starvation

Ex situ biomethanation allows the conversion of hydrogen produced from surplus electricity to methane. The flexibility of the process was recently demonstrated, yet it is unknown how intermittent hydrogen feeding impacts the functionality of the microbial communities. We investigated the effect of starvation events on the hydrogen consumption and methane production rates (MPRs) of two different methanogenic communities that were fed with hydrogen and carbon dioxide. Both communities showed functional resilience in terms of hydrogen consumption and MPRs upon starvation periods of up to 14 days. The origin of the inoculum, community structure and dominant methanogens were decisive for high gas conversion rates. Thus, pre-screening a well performing inoculum is essential to ensure the efficiency of biomethanation systems operating under flexible gas feeding regimes. Our results suggest that the type of the predominant hydrogenotrophic methanogen (here: Methanobacterium) is important for an efficient process. We also show that flexible biomethanation of hydrogen and carbon dioxide with complex microbiota is possible while avoiding the accumulation of acetate, which is relevant for practical implementation. In our study, the inoculum from an upflow anaerobic sludge blanket reactor treating wastewater from paper industry performed better compared to the inoculum from a plug flow reactor treating cow manure and corn silage. Therefore, the implementation of the power-to-gas concept in wastewater treatment plants of the paper industry, where biocatalytic biomass is readily available, may be a viable option to reduce the carbon footprint of the paper industry.

Kinetic modeling of deep vacuum residue hydroconversion in a pilot scale continuous slurry reactor with recycle

Slurry phase hydroconversion is a developing technology with the potential to completely upgrade Vacuum Residues (VR). In this work we use data from a continuous pilot plant with recycle to test and extend an existing distributed lumped kinetic model. The new data includes results from 134 steady state experiments with a Heavy Iran VR, including some at very high conversion, and allows sediment production rates to be quantified as well as sulphur removal in the form of H2S. The purpose of the work is to study the impact of the deep conversion reaction conditions and feedstock on the reaction kinetics. The model uses nineteen distributed lumps to represent the heavy hydrocarbons undergoing hydroconversion and hydrodesulphurisation with VR defined as the boiling range > 525°C. Reaction rates are based on molar concentrations. Hydrogen consumption and sediment production are taken into account in the model, as well as vapour liquid mass transfer resistances and vapour-liquid equilibrium. Parameter estimation has been carried out and the model provides a good fit with the experimental data. The modelling exercise found that, at very high conversions, thermal reactions give way to a cascade of catalytic reactions. The model gave a moderate fit for hydrogen consumption rates, which are strongly dependent on feedstock. Accumulation of sediment at high conversions was identified and well represented and the description of hydrodesulfurisation rates as proportional to cracking rates was validated.

Hydrocracking and hydrotreating reaction kinetics of heavy oil in CSTR using a dispersed catalyst

A kinetic model for the slurry-phase hydrocracking of vacuum residue was proposed under conditions of: 410–450 °C, 0.25–1 hr−1, 160 bar, 1500 Nm3/m3 of H2 to oil ratio, and 500 ppm catalyst (Mo-octoate). A five-lump model with ten reaction pathways was adopted to describe the hydrocracking kinetics, while the hydrotreating reactions were modeled by the power-law approach. The kinetic parameters were estimated considering the change in liquid density with reaction time. The kinetic model predicted product yields and concentrations with an average error of less than 10%. As for the hydrocracking reaction, it was demonstrated that the secondary cracking of VGO mainly produced MD at high temperature and the high conversion of RES. As for hydrotreating, it was confirmed that asphaltene conversion proceeded to increase the removal level of other impurities. Finally, a hydrogen consumption rate model was proposed based on HCK and HDT, which provides consistent information for further uses in reactor modeling and process modeling.

An Improved Test Method for Energy Consumption and Range of Fuel Cell Vehicles

At present, there are two main standards, ISO 23828 : 2013 and SAE J 2572–2014, which prescribe the hydrogen consumption test using the pressure method, gravimetric method, and flow method. However, these methods do not meet the test requirements for electric energy consumption and the range of plug-in hybrid fuel cell vehicles (FCVs) which are the main technical considerations in China and Europe. In this paper, a new test method for the hydrogen consumption, electric energy consumption, and range of FCVs is proposed without the use of additional hydrogen supply, measurement instruments, or energy consumption correction, which can improve the operability of the test and avoid the conversion between electric energy and hydrogen. One plug-in hybrid FCV and one nonplug-in hybrid FCV were tested using the proposed method. The results show that the new method meets the requirements of fuel economy test for FCVs with hydrogen consumption rate, electric energy consumption rate, the range for plug-in hybrid FCVs, hydrogen consumption rate, and the range for nonplug-in FCVs.