The electro-hydraulic brake (EHB) system of a vehicle should operate normally under all circumstances to ensure automotive safety. This redundant system guarantees the minimum required performance in the event of a critical failure of the brake system. In this study, we propose a redundant motor control strategy for the EHB to fully realize a functional safety design. The EHB system is composed of two identical electronic control units (ECUs), a dual three-phase dual-winding permanent magnet synchronous motor (DW-PMSM), and hydraulic components to generate brake pressure through the movement of an actuator. First, we propose a method to acquire the necessary motor current for generating brake pressure. Second, we present an initial driving method for the DW-PMSM for achieving stability before generating the braking pressure that involves setting the actuator’s origin position without a position sensor. Lastly, we describe a redundant motor control strategy for continuous brake operatio... [more]

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV... [more]

Photovoltaic plants are helping to reduce CO2 emissions, but the energy performance of photovoltaic systems must remain high throughout their operational life. Supervision and monitoring are mandatory for large photovoltaic plants because failures can cause high power losses due to the large number of photovoltaic modules. Infrared analysis is effective and reliable in detecting anomalies or failures in photovoltaic modules, but it is time-consuming and expensive when the infrared inspection of large photovoltaic plants is manual. Nowadays, the diffusion of unmanned aerial vehicles equipped with infrared cameras can support the fast supervision of photovoltaic plants. Nevertheless, the use of drones is regulated by international and national rules; consequently, it is not always possible to use a drone, or its utilization is limited based on geographic areas and/or authorizations. Moreover, infrared analysis requires additional requirements when done by drone, because the mutual positi... [more]

Rotor dynamic balancing is a classical problem. Traditional balancing methods such as the influence coefficient method and the modal balancing method, have low balancing efficiency because they need to run many times to add trial weights. Although the model-based balancing method improves the balancing efficiency, it cannot accurately identify the position, amplitude and phase of each unbalance fault for rotors with multi-disc structures, so it is difficult to apply it to actual balancing. To solve the above problems, based on the traditional modal balancing theory, this paper deduces that the continuous and isolated unbalance in the rotor-bearing system can be represented by isolated unbalance on several balancing planes approximately. The model-based method is used to identify the above-mentioned equivalent isolated unbalances, and then the corrected mass is added to the balancing planes so as to complete the balance of multiple flexible rotor without trial weights. Considering the p... [more]

In recent years, the number of articles reporting the addition of nanomaterials to enhance the process of anaerobic digestion has exponentially increased. The benefits of this addition can be observed from different aspects: an increase in biogas production, enrichment of methane in biogas, elimination of foaming problems, a more stable and robust operation, absence of inhibition problems, etc. In the literature, one of the current focuses of research on this topic is the mechanism responsible for this enhancement. In this sense, several hypotheses have been formulated, with the effect on the redox potential caused by nanoparticles probably being the most accepted, although supplementation with trace materials coming from nanomaterials and the changes in microbial populations have been also highlighted. The types of nanomaterials tested for the improvement of anaerobic digestion is today very diverse, although metallic and, especially, iron-based nanoparticles, are the most frequently... [more]

The article presents a cluster analysis of the EU-27 countries. The clusters were built to identify groups of countries similar to each other in relation to the set of Eurostat indicators from the Climate Change Drivers and Environment and Energy sections. During the research, tools of spatial information systems were used, such as cluster analysis, diagram maps, rasterization and the TSA method. ARIMA prediction models were also used. The research aims to verify our hypotheses. Particular attention was paid to Poland; therefore, it was verified whether the composition of the country’s energy mix translated into excessive emissions of pollutants in relation to other EU countries. Furthermore, the level of integration of energy markets in the European Union and its changes over time were examined. The authors also proposed a methodology to create detailed energy and climate strategies for designated clusters. The results of the presented research are particularly important in light of r... [more]

Optimizing the heating, ventilation, and air conditioning (HVAC) system to minimize district heating usage in large groups of managed buildings is of the utmost important, and it requires a machine learning (ML) model to predict the energy consumption. An industrial use case to reach large building groups is restricted to using normal operational data in the modeling, and this is one reason for the low utilization of ML in HVAC optimization. We present a methodology to select the best-fitting ML model on the basis of both Bayesian optimization of black-box models for defining hyperparameters and a fivefold cross-validation for the assessment of each model’s predictive performance. The methodology was tested in one case study using normal operational data, and the model was applied to analyze the energy savings in two different practical scenarios. The software for the modeling is published on GitHub. The results were promising in terms of predicting the energy consumption, and one of t... [more]

The annual electricity trade scheduling is the basis of long-term power generation scheduling. In recent decades, the ratio of new energy generation in China has increased annually, and the electricity market has operated under the “market electricity” and “planned electricity” double track mode in recent years. However, the existing annual electricity trade scheduling methods are extensive and cannot adapt to the new situation of “market electricity” and large-scale new energy generation. The annual scheduled energy of the power units is set as a decision variable, and a novel annual energy scheduling optimization model based on Gini coefficient of fairness is presented in this paper. In this model, “market electricity” capacity is conversed monthly, considering peaking reserve demand and monthly characteristics of new energy generation. The fairness constraint set based on Gini coefficient is introduced into the optimization model to solve various fairness problems. Simulation result... [more]

The development of any country is closely related to its ability to provide access to electricity for productive labor. Many countries in sub-Saharan Africa have low electrification rates for commercial, industrial and residential consumers. This study focuses on Nigeria, which has one of the largest populations and economies in sub-Saharan Africa. Although Nigeria possesses abundant renewable energy resources that can increase electricity generation, it has suffered a significant setback in electricity generation. However, for Nigeria to become one of the leading industrialized countries by 2030, access to clean, reliable, and sustainable energy sources is vital (Vision 20: 2030). This study assesses the possibility of Nigeria developing and transitioning to the use of various energy sources. Additionally, this study evaluates greenhouse gas (GHG) mitigation plans and future trends in energy sustainability through multi-criteria decision analysis (MCDA), considering the technical, soc... [more]

Proton-exchange membrane fuel cells (PEMFCs) are regarded as promising alternatives to internal combustion engines (ICEs) to reduce pollution. Recent research on PEMFCs focuses on achieving higher power densities, reducing the refueling time, mitigating the final price, and decreasing the degradations, to facilitate the commercialization of hydrogen mobility. The design of bipolar plates and compression kits, in addition to their coating, can effectively improve performance, increase durability, and support water/thermal management. Past reviews usually focused on the specific aspect, which can hardly provide readers with a complete picture of the key challenges facing and advances in the long-term performance of PEMFCs. This paper aims to deliver a comprehensive source to review, from both experimental, analytical and numerical viewpoints, design challenges, degradation modeling, protective coatings for bipolar plates, and key operational challenges facing and solutions to the stack t... [more]

Hegang coalfield is one of the areas with abundant coal resources in Heilongjiang Province. Characteristics of minerals and geochemistry of No. 26 coal (lower Cretaceous coals) from Junde mine, Hegang coalfield, Heilongjiang province, China, were reported. The results showed that No. 26 coal of Junde mine is slightly enriched in Cs, Pb, and Zr compared with world coals. The minerals in No. 26 coal of Junde mine primarily include clay minerals and quartz, followed by calcite, siderite, pyrite, monazite, and zircon. The diagrams of Al2O3−TiO2, Zr/Sc−Th/Sc, Al2O3/TiO2−Sr/Y, and Al2O3/TiO2−La/Yb indicate that the enriched elements in No. 26 coal were mainly sourced from the Late Paleozoic meta-igneous rocks in Jiamusi block. The volcanic ash contribution to No. 26 coal seems very low. Sulfate sulfur indicating oxidation/evaporation gradually decreases during No. 26 coal formation.

In this study, we present a Direct Model Reference Adaptive Control (DMRAC) algorithm in a boost converter used in islanded microgrids (MG) with a solar photovoltaic (PV) system. Islanded types of microgrids have very sensitive voltage and frequency variability; therefore, a robust and adaptive controller is always desired to control such variations within the MG. A DC−DC boost converter with a modified MIT rule controller is proposed in this paper, which stabilizes output voltage variations in islanded MG. Since the boost converter is a non-minimum phase, the controller design that relies only on output voltage feedback becomes challenging. Even though output voltage control can be achieved using inductor current control, such current mode controllers may also require prior knowledge of the load resistance and more states, such as output and inductor currents in feedback. Here, two control loops are used to achieve a stable output voltage; a PID controller can regulate the output volt... [more]

This paper presents the modeling, the design and verification of a three-phase coil structure for high-power Wireless-Power-Transfer (WPT) in automotive applications. The system, a Three-Polar-Pad (TPP), with complex mechanical geometry, is analytically modeled with an equivalent simplified structure. Thanks to this simplification, a numerical design is performed to minimize cross-coupling effects among different phases of the same side (receiver or transmitter) maximizing the linkage flux receiver-to-transmitter and then the power transferred. The analytical model is then verified in a Finite-Element-Analysis (FEA) environment. A final design, comprehensive of the shielding, is proposed matching the preliminary design constraints. Hence, the preliminary model is verified by testing a prototype using a three-phase Silicon Carbide (SiC) inverter at the transmitter side. The capability of the system is demonstrated by transferring 100 kW with more than 94% DC-to-DC efficiency over a 50 m... [more]

A frequency and voltage control strategy based on a decentralized and communication-less approach is proposed in this work and applied to Photovoltaic-Storage-Microturbine islanded Microgrids (MGs). The approach is based on the Model Predictive Control (MPC) technique. Thanks to the use of local measurements, each source can nullify the steady-state voltage and frequency errors by means of a dedicated MPC controller. Consequently, the proposed approach unifies the advantages of classic droop and master/slave controllers due to the absence of communication links among devices and due to the absence of a secondary centralized control loop.

One of the important goals of the EU is to ensure a secure, sustainable, and competitive energy system that is less dependent on external energy supply. Greater independence is planned to be achieved by diversifying energy sources, as well as investing in renewables and energy efficiency. One of the mechanisms is the demand response (DR) that provides a high level of energy independence for the consumer. In this paper, we explore perspectives of the development of DR with a mediating effect of the independent aggregators from an EU member state standpoint. We use a hybrid research methodology that combines instruments of strategic analysis, i.e., PESTLE framework and SWOT analysis, along with the integrated risk management framework in order to identify, evaluate and rank prominent risks to which this initiative is exposed. Interdependencies between the identified risk factors are also included and efficient mitigation measures are proposed. The findings of this exploratory research ar... [more]

Promising massive emissions reduction and energy savings, the utilization of autonomous unmanned aerial vehicles (UAVs) in last-mile parcel delivery is continuously expanding. However, the limited UAV range deters their widescale adoption to replace ground modes of transportation. Moreover, real-world data on the impact of different parameters on the operation, emissions, and energy consumption is scarce. This study aims to assess the impact of airspace planning and discretization on the energy consumption of autonomous UAVs. We utilize a novel open-source comprehensive UAV autonomous programming framework and a digital-twin model to simulate real-world three-dimensional operation. The framework integrates airspace policies, UAV kinematics, and autonomy to accurately estimate the operational energy consumption via an experimentally verified energy model. In the simulated case study, airspace is discretized by both a traditional Cartesian method and a novel dynamic 4D discretization (Sk... [more]

This article proposes a framework that uses analytical assessment of reliability to guide the expansion planning of power distribution systems (PDS) considering reliability criteria. The framework allows the estimation of reliability indices with and without the execution of expansion projects, thus supporting the decision-making process on investments in expansion projects. In the analytical assessment of reliability, failure rates of zones and restoration times are calculated from past data of interruptions in the primary distribution network. In addition, the estimated reliability indices are adjusted to historical values through failure rates proportionate to the length of each zone. To test and validate the proposed framework, it was applied to the distribution network at bus 5 of the Roy Billinton Test System (RBTS) and also to a real distribution feeder located in Brazil. The results indicated that the proposed framework can help define the most attractive investments leading to... [more]

Hydropower plants often work in off-design conditions to regulate the power grid frequency. Frequent transient operation of hydraulic turbines leads to premature failure, fatigue and damage to the turbine components. The speed-no-load (SNL) operating condition is the last part of the start-up cycle and one of the most damaging operation conditions of hydraulic turbines. Hydraulic instabilities and high-stress pressure fluctuations occur due to the low flow rate and unsteady load on the runner blades. Numerical simulations can provide useful insight concerning the complex flow structures that develop inside hydraulic turbines during SNL operation. Together with experimental investigations, the numerical simulations can help diagnose failures and optimize the exploitation of hydraulic turbines. This paper introduces the numerical model of a full-scale 10 MW Kaplan turbine prototype operated at SNL. The geometry was obtained by scaling the geometry of the corresponding model turbine as th... [more]

Chromated copper arsenate-treated (cca) wood disposal faces environmental restrictions due to its toxicity, heavy metal leaching in storage sites, and greenhouse gas emissions during incineration. Thus, finding new management methods for this contaminated wood at the end of life is crucial. This study evaluated the effect of pyrolysis temperature (300, 400, and 500 °C), particle size, biochar yield, and the behavior of arsenic (As), chromium (Cr), and copper (Cu) during treated-wood pyrolysis. The highest biochar yield was obtained at 300 °C for fine particles. The biochar retention of heavy metals decreased with increasing pyrolysis temperature. At 300 °C, the highest biochar As, Cr, and Cu retentions were 76, 91, and 83%. At 500 °C, biochar only retained 43% of the As. Additionally, heavy metal leaching from the biochar exceeded the Environmental Protection Agency’s (EPA) maximum concentration limit of 5 mg/L. High-density polyethylene encapsulation of contaminated biochar reduced th... [more]

Particulate mass concentration is a crucial parameter for characterising air quality. The diesel particulate filter (DPF) is the primary technology used to limit vehicle particle emissions, but it needs periodic cleaning, a process called regeneration. This study aims to assess the impact of active DPF regeneration on the performance and emissions of Euro 5 and 6 vehicles. The study examined both carbon dioxide (CO2) and pollutant (nitrogen oxides (NOx) and particle number (PN)) emissions for eight vehicles tested in the laboratory and on the road. Apart from the DPF, a wide range of emission control systems was covered in this experimental campaign, including exhaust gas recirculation (EGR), diesel oxidation catalyst (DOC), lean NOx trap (LNT) and selective catalytic reduction (SCR) catalyst, revealing the different impacts on NOx emissions. The regeneration frequency and duration were also determined and used to calculate the Ki factor, which accounts for the emissions with and witho... [more]

Heat transfer is one of the most fundamental engineering subjects and is found in every moment of life. Heat transfer problems, such as heating and cooling, where the transfer of heat between regions is calculated, are problems that can give exact solutions with parametric equations, many of which were obtained by solving differential equations in the past. Today, the fact that heat transfer problems have a more complex structure has led to the emergence of multivariate models, and problems that are very difficult to solve with differential equations have emerged. Optimization techniques, which are also the subject of computer science, are frequently used to solve complex problems. In this study, laminar thermal boundary layers in flow over a flat plate, a sub-problem of heat transfer, is solved with recent metaheuristic algorithms. Teaching learning-based optimization (TLBO), sine cosine optimization (SCO), gray wolf optimization (GWO), whale optimization (WO), salp swarm optimization... [more]

In Poland, there is a high ratio of private transport and unfavorable patterns of daily commuting. These patterns can be changed by introducing comfortable and eco-friendly vehicles, such as e-scooters and e-bikes. At the same time, the development of the e-micromobility-based vehicle sharing services market is developing. The aim of the article is to analyze selected e-scooters available on the Polish market and to identify the most useful vehicles from two opposing perspectives, i.e., the potential customer and owner of the vehicle sharing system. The PROSA GDSS (PROMETHEE for Sustainability Assessment—Group Decision Support System) method and the graphical representation of GAIA (Geometrical Analysis for Interactive Assistance) were used to search for a compromise and balance between the needs of the indicated stakeholders. The results of the methods used were compared with the results of the PROMETHEE GDSS method, which does not take into account the balance between the stakeholder... [more]

Green energy is a crucial component in addressing expanding energy demands and combating climate change, but the possible negative repercussions of these technologies are frequently disregarded. Green energy’s deployment is tied to environmentally sustainable development goals (SDGs). It can only be achieved by scaling up the finance of investment that provides environmental benefits through new financial instruments and new policies, such as green banks, green bonds, community-based green funds, green central banking, etc. In an effort to address the issues with IPAT and ImPACT, this study employed the STIRPAT model approach, which is a proven framework for energy economics analysis. The author gathers yearly data spanning 2002−2018 for six ASEAN member countries with the aim of investigating the relationship between CO2 emissions, green finance, energy efficiency, and the green energy index (GEX). After preliminary tests, the study employed the Westerlund test and Johansen Fisher tes... [more]

This study investigates a prediction model for the cycle injection quantity in a high-pressure common rail injector under a transient thermal boundary. The results show that the transient temperature increase curve calculated by the mathematical model of the common rail injector under adiabatic flow is significantly different from the experimental data. A non-isothermal model of the injector coupled with heat transfer is established, which considers the actual heat transfer phenomenon. The excellent agreement between the new calculation results and the experimental data confirms that the fuel injection process of a common rail injector comprises the coupled phenomena of fuel heating and heat transfer. Based on the established simulation model, it is found that in the continuous injection process of the injector, owing to the thermal effect of injection, the cycle injection quantity decreases gradually with an increase in the injector working time and then stabilizes. Under the conditio... [more]

To reduce the negative impacts of stall and surge on compressor performance, a novel combined casing treatment (CCT) structure with axial skewed slots and injection groove is proposed in this paper. The aerodynamic performance, as well as the mechanisms of loss generation, of a transonic axial compressor with NASA Rotor 67 are investigated numerically. The simulation results indicate that, compared with individual casing treatment method, the CCT works effectively with regard to operation performance. The stall margin (SM) is increased by 14.7% with 1.12% decrease in the peak efficiency. The interaction of axial skewed slots and injection groove can be explained by the enhancement of exchange flow in slots and axial motion of fluid. As a result, the leakage flow near the blade tip is eliminated and the flow separation is further suppressed. What is more, an analysis of entropy generation is also conducted. The results reveal that the effect of CCT on loss reduction mainly concentrates... [more]