Different fast charging protocols will cause different battery aging rates, which will reduce the accuracy and robustness of the capacity estimation. To improve the robustness and accuracy of battery capacity estimation with different fast charging rates, a random health indicator and deep learning approach based capacity estimation framework is proposed in this paper. First, a robust health indicator is proposed to extract the relationship between battery charging data and aging rate, which is a random charging curve segment consist of voltage, current, and charging capacity. Second, a deep convolutional neural network is proposed to estimate capacity based on the robust health indicator with smaller model size, and the field model can be quickly obtained by the pre-trained model and transfer learning. Finally, the proposed framework is verified by the public datasets and experimental datasets with different fast charging protocols. The results show that even the charging protocols of test data are different from that of training data, the average error of capacity estimation is within 0.35%.
PV integrated with EVs has become a promising way of utilizing PV generation in urban areas towards low carbon future. This paper aims to evaluate the technical and economic potentials of rooftop PV system integrated with EVs in 21 cities in Guangdong Province, China, as well as the energy-economic-environmental effects of the PV+EV system, and shed light on how PV+EV system can be deployed within a region. The results show that PV+EV systems are cost-effective in all cities in the Guangdong Province, EVs can increase the PV utilization in each city, making cities less dependent on external energy sources, reducing costs for the whole society, and providing more CO2 emission reductions for most cities. However, cities vary in performance of PV potential and development capabilities, which should be taken into account in overall regional development plan.
The influence of ions concentration and CNT diameter on the interfacial resistance for CNT membrane is revealed through molecular dynamics approach. We find that the interfacial resistance of CNT membrane is affected by ion concentration and CNT diameter, and the reduction diameter can promote the interfacial resistance with the increase of ion concentration. The presence of ions in the system results in the increase of entrance-exit resistance and flange resistance composing the interfacial resistance.
Fracturing is needed to increase shale gas production due to the low porosity and permeability of shale reservoirs. As the main component of fracturing fluid, water is indispensable in the production and development of shale gas. This paper studies the invasion mechanism of fracturing fluid in shale reservoirs by simulating the competitive adsorption of methane and water. This study obtains the variation law of adsorption capacity, interaction force, and gas-water distribution under different gas-water ratios of different minerals. The electrostatic force in quartz plays a major adsorption role, and the van der Waals force in kaolinite plays a major adsorption role.
Cocoa pod husk (CPH) has become a subject of research interest in Ghana because of its competitive energy density and abundance in rural communities. The composition of producer gas in a downdraft gasifier for CPH gasification is predicted using a thermodynamic equilibrium model presented in this research study. Experimental data from a 5kWe gasifier system burning cocoa pod husk was used to validate the thermodynamic model. Lower heating value (LHV), gas output, gasification efficiency, carbon conversion efficiency, engine conversion efficiency, and total biomass gasifier system efficiency were all measured. The carbon conversion efficiency was 75%, and the gasifier efficiency was 51%. Meanwhile, the gasifier system’s overall efficiency was low. However, it can be increased by eliminating all sources of heat loss.
Ammonia, a carbon-free fuel, can make an important contribution towards the decarbonization of on- and off-road internal combustion (IC) engines. However, the research on the ammonia use in IC engines is still in initial stages. The goal of this study was to investigate the effect of the equivalence ratio on an ammonia-dedicated engine performance. To observe how the equivalence ratio of the air-ammonia mixture affects in-cylinder flame speed and the reaction pathway of pollutant formation (therefore, how it affects engine efficiency and emissions), a multi-dimensional computational fluid dynamics simulation of a single-cylinder diesel engine converted to dedicated ammonia spark ignition operation was built. The numerical results suggested that stoichiometric operation was better than lean operation for this engine. In detail, lean operation reduced the combustion efficiency and increased engine-out NOX and ammonia emissions, therefore potentially discarding the known thermal efficiency benefit of lean operation in IC engines. In addition, a rich equivalence ratio drastically reduced combustion and thermal efficiency, and increased fuel consumption rates and unburned engine-out ammonia emissions. Finally, while stoichiometric operation produced the best overall performance in terms of efficiency and emissions, attention must be paid to N2O and unburned NH3 engine-out emissions.
The large-scale commercial development of natural gas hydrate puts forward requirements for efficient gas storage. Solidified natural gas storage via clathrate hydrates presents an economically sound prospect and promising high energy density. Sodium dodecyl sulfate (SDS) is regarded as one of the most effective kinetic promoters for the rapid and high-efficient conversion of CH4 hydrate. However, the mechanism that SDS influences the formation of clathrate hydrate remains controversial. Considering the differences in hydrate film formation characteristics and single crystal structure may be important reasons for the influence of SDS on hydrate formation and different promotion effects, this study investigated, from mesoscopic to molecular scale, the effects of SDS and subcooling on the evolution of CH4 hydrate film. The experimental results showed that a competitive mechanism between SDS concentration and driving force on the CH4 hydrate formation may exist, which could dominate the growth mode of CH4 hydrate. In case of the influence of subcooling being greater, a complete CH4 hydrate film was formed. Once SDS concentration dominates hydrate growth, a non-aggregated CH4 hydrate film can be formed. The critical concentrations of SDS varied with different subcooling conditions so that only if the SDS concentration exceeded the critical point can the formation of CH4 hydrate be obviously accelerated. The results obtained in this study are of great significance to guide the selection of the optimal SDS concentration for the promotion of CH4 hydrate formation and provide insights for the method modification of SDS or other surfactants accelerating CO2 hydrate formation.
Porous media compressed air energy storage (PM-CAES) is a viable option to compensate expected fluctuations in energy supply in future energy systems with a 100% share of renewables. However, the design and evaluation of operational conditions for a PM-CAES require an efficient coupled power plant â€“ geostorage model. In this study, therefore, a proxy model for the geostorage is developed and evaluated with respect to two scenarios representing realistic energy system load profiles. Results show, that the proxy model represents a consistent approximation, yielding storage pressure, rates and capacity within 98% of the full-scale reservoir model, while reducing runtimes to about 6%.
This paper presents a digital twin for the district heating prosumer laboratory at the Center for Combined Smart Energy Systems (CoSES) consisting of heat generators, thermal storages and heat consumption. It is developed using a newly created, Modelica-based simulation library named CoSES ProHMo. Existing simulation models often fail to accurately represent the behavior of commercial hardware components. Therefore, the digital twin features new, accurate heat generator models and tuned models for thermal storage units and heat consumption. The component models are parametrized using measurements from the CoSES laboratory. It can be exported and used in other programs via the Functional Mock-up Interface (FMI). This allows the digital twin to be used platform-independently to design control strategies for realistic heating systems. If desired, the control strategies can be ported to an embedded controller and further tested in the CoSES laboratory. A case study with multiple heat generators, thermal storages and a heat sink was designed to demonstrate the utility of the library. The analysis of the results shows previously unanticipated interactions between different heat generators and the internal controllers of commercial hardware. Based on these findings, the proposed digital twin library can be used by the research community to create realistic scenarios for testing novel control strategies for heating systems and prosumers in district heating grids.
Compared with fixed jet pumps (FJPs), adjustable jet pumps (FJPs) have a wider application potential in heating and other fields. However, the existing mathematical model of FJPs cannot accurately describe the performance of AJPs. In this paper, on the basis of considering the influence of the position of the needle on the performance of the adjustable jet pump, the existing mathematical model of FJPs is improved and simplified to characterize AJPs. Furthermore, the coefficients in the mathematical model are identified by genetic algorithm. After verification, the average error between the flow rate obtained by the mathematical model and the measured value is within 2%.