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The electro-hydraulic servo pump control system (EHSPCS) is a volume control system that uses a permanent magnet synchronous motor (PMSM) with a fixed displacement pump to directly drive and control the hydraulic cylinder. The energy transmission law of the system is very complicated due to the transformation of electrical, mechanical and hydraulic energy as well as other energy fields, and qualitative analysis of the energy transfer efficiency is difficult. Energy transfer analysis of the EHSPCS under different working conditions and loads is proposed in this paper. First, the energy flow transfer mechanism was analyzed, and the mathematical and energy transfer models of the key components of the system were established to explore the energy characteristic state transition rule. Second, a power bond diagram model was built, its state equation and state matrix were deduced, and a system simulation model was built. Finally, combined with the EHSPCS experimental platform, simulation experiments were carried out on the dynamic position following and steady-state position holding conditions of the system, and the variation rules of the power of each energy characteristic state and the system energy transfer efficiency under different loads were obtained. The research results provide a foundation for the study of power matching and energy-saving mechanism of the EHSPCS.

The characteristics of excess aerobic granular sludge, related to its structure and chemical composition, limit the efficiency of anaerobic digestion. For this reason, pre-treatment methods and compositions with other organic substrates are used. In earlier work, no attempt was made to intensify the methane fermentation of the excess aerobic granular sludge by adding fatty waste materials. The aim of the research was to determine the effects of co-digestion of pre-hydrodynamically cavitated aerobic granular sludge with waste fats on the efficiency of methane fermentation under mesophilic and thermophilic conditions. The addition of waste fats improved the C/N ratio and increased its value to 19. Under mesophilic conditions, the highest effects were observed when the proportion of volatile solids from waste fats was 25%. The amount of biogas produced increased by 17.85% and CH4 by 19.85% compared to the control. The greatest effects were observed in thermophilic anaerobic digestion at 55 °C, where a 15% waste fat content in volatile solids was ensured. This resulted in the production of 1278.2 ± 40.2 mL/gVS biogas and 889.4 ± 29.7 mL/gVS CH4. The CH4 content of the biogas was 69.6 ± 1.3%. The increase in biogas and CH4 yield compared to pure aerobic granular sludge anaerobic digestion was 34.4% and 40.1%, respectively. An increase in the proportion of waste fats in the substrate had no significant effect on the efficiency of methane fermentation. Strong positive correlations (R2 > 0.9) were observed between biogas and CH4 production and the C/N ratio and VS concentration.

With the continuous development of intelligent transportation technologies, new ways of energy usage in transportation continue to emerge, which puts forward new requirements for the planning and design of energy systems. However, comprehensive analyses on the characteristics of transportation energy systems and the development trend of energy usage patterns brought by intelligent technologies have rarely been carried out so far. This paper explores this subject by reviewing the recent development and utilization of intelligent technologies in the transportation system and its impacts on energy usage. This review is carried out from three aspects, covering the representative intelligent transportation and energy technologies on vehicles, infrastructures and systems. The scope is limited within road, railway and water transport domains, with a focus on the recent developments in China as a representative. In terms of vehicles, the development trend of the power systems for new energy vehicles, the characteristics of energy usages in electric vehicles and the effects on energy saving and emission reduction are summarized. In terms of infrastructures, new technologies on smart road, smart port, intelligent railway energy system and the usage of clear energy on electric grid for transportation are reviewed, with the consideration of their potential influences on energy usages and the energy consumption characteristics of typical facilities also being analyzed. As for the transportation system, this review has focused on intelligent and connected transportation systems, train control and autonomous systems, and intelligent shipping system, with the emphasis on the energy saving and emission reduction effects of applying these intelligent technologies. The overall development trend of the transportation energy system is then analyzed based on the above materials, in particular, the future energy usage patterns in transportation system are given and the major challenges and obstacles approaching the future scenarios are also identified.

Car-sharing services are developing at an ever-increasing pace. Taking into account the reduction of carbon dioxide emissions and pursuit of the sustainable development of transport, implementing electric cars in car-sharing fleets is being proposed. On the one hand, these types of vehicles are referred to as emission-free, but on the other hand, their environmental friendliness is questionable due to the emission of carbon dioxide during the production of energy to power them. Although many scientific papers are devoted to the issue of reducing emissions through car sharing, there is a research gap concerning the real production of carbon dioxide by car-sharing vehicles during car-sharing trips. To fill this research gap, the objective of the article was to analyze the actual level of carbon dioxide emissions from combustion and electric vehicles from car-sharing systems produced when renting rides. The test results showed that the electric car turned out to be significantly less emitting. The use of electric vehicles in car-sharing fleets can reduce carbon dioxide emissions from 14% to 65% compared to using cars with internal combustion engines. However, the key role during car-sharing trips is played by the driving style of the drivers, which has been omitted from the literature to date. This should be properly regulated by service providers and focus on the proper use of energy from electric vehicle batteries, especially at low temperatures. The article provides support for operators planning to modernize their fleet of vehicles and fills the research gap concerning car-sharing emissions.

Nitrogen reduction reaction (NRR) and nitrate reduction reaction (NO3−RR) provide a potential sustainable route by which to produce ammonia, a next-generation energy carrier. Many studies have been conducted over the years, mainly emphasizing material design and strategies to improve catalytic performance. Despite significant achievements in material design and corresponding fundamental knowledge, the produced ammonia is still very limited, which makes it prone to bias. The presence of interferants (e.g., cations and sacrificial reagents), the pH of the solution, and improper analytical procedure can lead to the over or underestimation of ammonia quantification. Therefore, the selection of the appropriate ammonia quantification method, which meets the sample solution condition, along with the proper analytical procedures, is of great importance. In this review, the state-of-the-art ammonia quantification method is summarized, emphasizing the advantages, limitations, and practicality for NRR and NO3−RR studies. Fundamental knowledge of the quantification method is introduced. Perspective on the considerations for selecting the suitable quantification method and for performing the quantification process is also provided. Although non exhaustive, this focused review can be useful as a guide to design the experimental setup and procedure for more reliable ammonia quantification results.

The decarbonisation of heating in the United Kingdom is likely to entail both the mass adoption of heat pumps and widespread development of district heating infrastructure. Estimation of the spatially disaggregated heat demand is needed for both electrical distribution network with electrified heating and for the development of district heating. The temporal variation of heat demand is important when considering the operation of district heating, thermal energy storage and electrical grid storage. The difference between the national and urban heat demands profiles will vary due to the type and occupancy of buildings leading to temporal variations which have not been widely surveyed. This paper develops a high-resolution spatiotemporal heat load model for Great Britain (GB: England, Scotland a Wales) by identifying the appropriate datasets, archetype segmentation and characterisation for the domestic and nondomestic building stock. This is applied to a thermal model and calibrated on the local scale using gas consumption statistics. The annual GB heat demand was in close agreement with other estimates and the peak demand was 219 GWth. The urban heat demand was found to have a lower peak to trough ratio than the average national demand profile. This will have important implications for the uptake of heating technologies and design of district heating.

This paper addresses the energy conservation problem in computing systems. The focus is on energy-efficient routing protocols. We formulated and solved a network-wide optimization problem for calculating energy-aware routing for the recommended network configuration. Considering the complexity of the mathematical models of data center networks and the limitations of calculating routing by solving large-scale optimization problems, and methods described in the literature, we propose an alternative solution. We designed and developed several efficient heuristics for equal-cost multipath (ECMP) and Valiant routing that reduce the energy consumption in the computer network interconnecting computing servers. Implementing these heuristics enables the selection of routing paths and relay nodes based on current and predicted internal network load. The utility and efficiency of our methods were verified by simulation. The test cases were carried out on several synthetic network topologies, giving encouraging results. Similar results of using our efficient heuristic algorithm and solving the optimization task confirmed the usability and effectiveness of our solution. Thus, we produced well-justified recommendations for energy-aware computing system design to conclude the paper.

The paper presents a modified algorithm for determining the accuracy parameter of the system for differential corrections and monitoring (SDCM) navigation solution in air navigation. For this purpose, a solution to determine the resultant accuracy parameter was proposed by using two on-board global navigation satellite system (GNSS) receivers. The mathematical algorithm takes into account the calculation of a single point positioning accuracy for a given GNSS receiver and a weighting factor combining the position error values. The weighting factor was determined as a function of the number of tracked GNSS satellites used in the SDCM single point positioning solution. The resultant accuracy parameter was expressed in ellipsoidal coordinates BLh (B—latitude, L—longitude, h—ellipsoidal height). The study used GNSS kinematic data recorded by two on-board receivers: Trimble Alloy and Septentrio AsterRx2i, located in a Diamond DA 20-C1 aircraft. The test flight was performed near the city of Olsztyn in north-eastern Poland. Calculations and analyses were performed using RTKLIB software and the Scilab environment. On the basis of the performed tests, it was found that the proposed algorithm for SDCM system allows for improvement in the determination of the resultant accuracy value by 56–80% in relation to the results of position errors from a single GNSS receiver. Additionally, the proposed algorithm was tested for the European Geostationary Navigation Overlay Service (EGNOS) system, and in this case, the improvement in the accuracy parameter was even better and was in the range of 69–89%. The resulting SDCM and EGNOS positioning accuracy met the International Civil Aviation Organization (ICAO) certification requirements for SBAS systems in air navigation. The mathematical algorithm developed in this work was tested positively and can be implemented within the SBAS augmentation system in air navigation.