Owing to the variation between lithium-ion battery (LIB) cells, early discharge termination and overdischarge can occur when cells are coupled in series or parallel, thereby triggering a decrease in LIB module performance and safety. This study provides a modeling approach that considers the effect of cell variation on the performance of LIB modules in energy storage applications for improving the reliability of the power quality of energy storage devices and efficiency of the energy system. Ohm’s law and the law of conservation of charge were employed as the governing equations to estimate the discharge behavior of a single strand composing of two LIB cells connected in parallel based on the polarization properties of the electrode. Using the modeling parameters of a single strand, the particle swarm optimization algorithm was adopted to predict the discharge capacity and internal resistance distribution of 14 strands connected in series. Based on the model of the LIB strand to predic... [more]

Energy and power demands for military operations continue to rise as autonomous air, land, and sea platforms are developed and deployed with increasingly energetic weapon systems. The primary limiting capability hindering full integration of such systems is the need to effectively and efficiently manage, generate, and transmit energy across the battlefield. Energy efficiency is primarily dictated by the number of dissimilar energy conversion processes in the system. After combustion, a Compression Ignition (CI) engine must periodically continue to inject fuel to produce mechanical energy, simultaneously generating thermal, acoustic, and fluid energy (in the form of unburnt hydrocarbons, engine coolant, and engine oil). In this paper, we present multiple sets of Shallow Artificial Neural Networks (SANNs), Convolutional Neural Network (CNNs), and K-th Nearest Neighbor (KNN) classifiers, capable of approximating the in-cylinder conditions and informing future optimization and control effo... [more]

Magnetic properties of hard magnets are currently attracting a great deal of attention. In the paper, the modified Harrison model was used to describe the saturating hysteresis loops of three praseodymium−dysprosium ribbons that differed in their chemical composition and processing conditions. Microstructural studies (TEM and diffraction patterns) were performed for the ribbons under consideration. The Harrison model incorporates a number of physically tangible concepts such as the anhysteretic curve, bifurcations, and bi-stability. The modification of the original approach consisted of adding an additional degree of freedom in the modeling by freeing the restraints present in the original version, in which both coercivity and remanence are functions of temperature only.

This paper proposes a novel T-type 7-level single-phase DC-AC inverter having a single input power source, self-balancing, and voltage gain of 3 along with low total harmonic distortion (THD). Since the structure of the proposed 7-level DC-AC inverter is symmetrical, the interchangeability of mass production can be easily achieved. In addition, because only one switch works for all time, the switch has quite low switching loss and voltage stress as well as the control being very easy. Furthermore, not only the proposed 7-level DC-AC inverter is analyzed in detail by the operating principle, but also the mathematical model for the adopted level-shift sinusoidal pulse width modulation (LS-SPWM) for this multilevel DC-AC inverter is successfully developed by using the well-known state averaging technique widely employed in the DC-DC converter. As a result, the required proportional-integral (PI) controller, used in the closed loop, can be designed systematically and easily. Eventually, th... [more]

This publication explores how the existing synergies between conventional liquefied natural gas regasification and hydrogen hydrogenation and dehydrogenation processes can be exploited. Liquid Organic Hydrogen Carrier methodology has been analyzed for hydrogen processes from a thermodynamic point of view to propose an energy integration system to improve energy efficiency during hybridization periods. The proposed neural network can acceptably predict power demand using daily average temperature as a single predictor, with a mean relative error of 0.25%, while simulation results based on the estimated natural gas peak demand show that high-pressure compression is the most energy-demanding process in conventional liquefied natural gas regasification processes (with more than 98% of the total energy consumption). In such a scenario, exceeding energy from liquid organic hydrogen carrier processes have been used as a Rankine’s cycle input to produce both power for the high-pressure compres... [more]

Photovoltaic-thermal (PVT) technologies have demonstrated several attractive features, such as higher power and comparative efficiencies. Improving the thermal recovery from the PVT system would further improve the power output and the efficiency of the PVT system. This paper identifies the best operating factors of nanofluid-based PV thermal/nano-enhanced phase change material using artificial intelligence. The target is the maximization of thermal energy and exergy outputs. The suggested approach combines ANFIS modelling and particle swarm optimization (PSO). Four operating factors are taken into consideration: PCM (phase change material) layer thickness, HTF (heat transfer fluid) mass flow rate, MFNPCM (“mass fraction of nanoparticles in PCM”) and MFNfluid (“mass fraction of nanoparticles in nanofluid”). Using a dataset, an “adaptive neuro-fuzzy inference system” (ANFIS) model has been established for simulating the thermal energy and exergy outputs in terms of the mentioned operati... [more]

Lithium batteries employed in lightweight fixed-wing UAVs are required to operate with large temperature variations and, especially for the emerging applications in hybrid propulsion systems, with relevant transient loads. The detailed dynamic modelling of battery packs is thus of paramount importance to verify the feasibility of innovative hybrid systems, as well as to support the design of battery management systems for safety/reliability enhancement. This paper deals with the development of a generalised approach for the dynamic modelling of battery packs via Thevenin circuits with modular hysteretic elements (open circuit voltage, internal resistance, RC grids). The model takes into account the parameters’ dependency on the state of charge, temperature, and both the amplitude and sign of the current load. As a relevant case study, the modelling approach is here applied to the Li-Po battery pack (1850 mAh, 6 cells, 22.2 V) employed in the lightweight fixed-wing UAV Rapier X-25 devel... [more]

The global trend is constantly increasing investments in strategic sectors of the economy, for example the electric power industry, which, in many countries, is becoming diversified and dispersed due to the multitude of entities investing in energy production and renewable resources, which leads to an increase in the heterogeneity of investment decisions. There is an urgent need to control the movement of investments, budget funds, as well as their development in the process of implementing investment programs of energy companies. The control of the movement of investments is the most promising direction of studying the subject of finance and audit. The increasing volume of public and private targeted investments in the energy sector and the lack of control over the effectiveness of investment projects (since each program contains several thousand lists of projects) necessitated the introduction of additional regulation of budget spending. The development of a mathematical apparatus fo... [more]

This paper reviews the current techniques used in energy management systems to optimize energy schedules into microgrids, accounting for uncertainties for various time frames (day-ahead and real-time operations). The current uncertainties affecting applications, including residential, commercial, virtual power plants, electric mobility, and multi-carrier microgrids, are the main subjects of this article. We outline the most recent modeling approaches to describe the uncertainties associated with various microgrid applications, such as prediction errors, load consumption, degradation, and state of health. The modeling approaches discussed in this article are probabilistic, possibilistic, information gap theory, and deterministic. Then, the paper presents and compares the current optimization techniques, considering the uncertainties in their problem formulations, such as stochastic, robust, fuzzy optimization, information gap theory, model predictive control, multiparametric programming... [more]

Twenty-two straight run vacuum residues extracted from extra light, light, medium, heavy, and extra heavy crude oils and nine different hydrocracked vacuum residues were characterized for their bulk properties and SARA composition using four and eight fractions (SAR-ADTM) methods. Intercriteria analysis was employed to determine the statistically meaningful relations between the SARA composition data and the bulk properties. The determined strong relations were modeled using the computer algebra system Maple and NLPSolve with the Modified Newton Iterative Method. It was found that the SAR-ADTM saturates, and the sum of the contents of saturates and ARO-1 can be predicted from vacuum residue density, while the SAR-ADTM asphaltene fraction content, and the sum of asphaltenes, and resins contents correlate with the softening point of the straight run vacuum residues. The softening point of hydrocracked vacuum residues was found to strongly negatively correlates with SAR-ADTM Aro-1 fractio... [more]

This review of the state of the art aims to collect the description and main research results in the field of development and validation of control algorithms with the main purpose to solve the problem of cogging torque and main sources of electromagnetic torque ripple. In particular, we focus on electric drives for advanced and modern mechatronic applications such as industrial automation, robotics, and automotive applications, with special emphasis on work that exploits model-based design. A great added value of this paper is to explicitly show the operational steps required for the model-based design design of optimized control algorithms for electric drives where it is necessary to make up for electromagnetic torque oscillations due to the main sources of ripple, particularly cogging torque. The ultimate goal of this paper is to provide researchers approaching this particular problem with a comprehensive collection of the most effective solutions reported in the state of the art an... [more]

Balancing the production and consumption of electricity is an urgent task. Its implementation largely depends on the means and methods of planning electricity production. Forecasting is one of the planning tools since the availability of an accurate forecast is a mechanism for increasing the validity of management decisions. This study provides an overview of the methods used to predict electricity supply requirements to different objects. The methods have been reviewed analytically, taking into account the forecast classification according to the anticipation period. In this way, the methods used in operative, short-term, medium-term, and long-term forecasting have been considered. Both classical and modern forecasting methods have been identified when forecasting electric energy consumption. Classical forecasting methods are based on the theory of regression and statistical analysis (regression, autoregressive models); probabilistic forecasting methods and modern forecasting methods... [more]

This paper concerns technology challenges for the wind and solar sectors and the role of computational science in addressing the above. Wind energy challenges include understanding the atmospheric flow physics, complex wakes and their interaction with wind turbines, aeroelastic effects and the associated impact on materials, and optimisation of wind farms. Concentrated solar power technologies require an optimal configuration of solar dish technology and porous absorber in the volumetric solar receiver for efficiency and durability and to minimise the convective heat losses in the receiver. Computational fluid dynamics and heat transfer have advanced in terms of numerical methods and physics-based models and their implementation in high-performance computing facilities. Despite this progress, computational science requires further advancement to address the technological challenges of designing complex systems accurately and efficiently, as well as forecasting the system’s performance.... [more]

The operational characteristics during transients are significantly influenced by magnetic saturation in electrical equipment. For the computation of steady-state rated operation in multiphase induction machines, the assumption of linear magnetic behavior of the iron core in classical machine models may be sufficient. The mathematical models of the considered models differ in terms of the existence or absence of dynamic cross-saturation effects. The approach that is most frequently used to examine the impact of magnetic saturation is based on the state-space variable representation of the mathematical model in dynamic axes (d−q). The purpose of this research is to investigate the effects of magnetic saturation on six-phase induction machines. In this study, a d−q transformation-based model of a six-phase induction machine (SPIM), including the magnetic saturation effect, is developed. The cross-saturation and the common mutual leakage inductance between the two sets of stators’ winding... [more]

The use of simulation and modelling has been proposed for determining the excitations to be applied in the procedures of laboratory testing of a car’s structural components, without the need to test the complete vehicle. The paper presents the general concept as well as an example of the procedure. It covers determining the spectrum and time-domain realization of a load on a selected node of the vehicle structure under durability tests. The author used both the mathematical and physical model of the tractor-semitrailer unit, where the input was considered as a random process resulting from the road profile. He calculated the transmittance modules and the power spectral densities of the vertical force on the joint between the tractor’s fifth wheel and the kingpin of the semitrailer and the extreme values of the dynamic components of this force. The inverse discrete Fourier transform makes it possible to generate the realization of the said force. It can be used in durability studies. Th... [more]

The direct reduction process has been developed and investigated in recent years due to less pollution than other methods. In this work, the first direct reduction iron oxide (DRI) modeling has been developed using artificial neural networks (ANN) algorithms such as the multilayer perceptron (MLP) and radial basis function (RBF) models. A DRI operation takes place inside the shaft furnace. A shaft furnace reactor is a gas-solid reactor that transforms iron oxide particles into sponge iron. Because of its low environmental pollution, the MIDREX process, one of the DRI procedures, has received much attention in recent years. The main purpose of the shaft furnace is to achieve the desired percentage of solid conversion output from the furnace. The network parameters were optimized, and an algorithm was developed to achieve an optimum NN model. The results showed that the MLP network has a minimum squared error (MSE) of 8.95 × 10−6, which is the lowest error compared to the RBF network mod... [more]

This research presents a comprehensive analysis of electric vehicle (EV) proliferation factors and various monetary and non-monetary value streams emerging in the EV domain. A comprehensive mathematical model is implemented to study EV proliferation and the resulting market share applicable to any geography and jurisdictional regime. Further, a novel framework is presented to analyze the interdependency between EV proliferation factors and value streams. The proposed model and framework can be leveraged to quantifiably evaluate the timeline available for grid operators to accommodate EV growth while utilizing those as Distributed Energy Resources (DERs) to improve grid reliability, commercial value, and environmental benefits. Compared to the previous studies, the analysis indicated that if all the factors which impact EV proliferation are addressed simultaneously, EV market share can surpass the internal combustion engine vehicle (ICV) in as quickly as 15−20 years. The study also high... [more]

This paper presents a novel design approach of a Petri-net-based cyber-physical system (CPS). The idea is oriented toward implementation in a field-programmable gate array (FPGA). The proposed technique permits error detection in the system at the early specification stage in order to reduce the time and prototyping cost of the CPS. Due to the state explosion problem, the traditional verification methods have exponential computational complexity. In contrast, we show that under certain assumptions, the proposed algorithm is able to detect possible errors in the system even in cubic O(|T|2|P|) time. Furthermore, all the required steps of the proposed design method are presented and discussed. The idea is illustrated by a real-life case study example of a traffic light crossroad. The system was modelled, analysed, implemented, and finally validated within the FPGA device (Virtex-5 family).

The worldwide population growth and the technological advancements reported in the past few years have led to an increase in the production and consumption of energy. This has increased greenhouse gas (GHG) emissions, the primary driver of climate change. As a result, great attention has been paid to sustainable and green energy sources that can replace or reduce reliance on non-sustainable energy sources. Among the different types of renewable energy sources currently available, bioenergy has been reported as an attractive resource mainly due to its low cost and great availability. Bioenergy can be produced from different biomass sources and converted into biofuels or value-added products through thermochemical, biochemical, and chemical processes. Gasification is a thermochemical process commonly used for bioenergy production, and it is particularly attractive mainly due to its high efficiency. However, its performance is influenced by parameters such as type of feedstock, size of bi... [more]

Heat pipe systems have attracted increasing attention recently for application in various heat transfer-involving systems and processes. One of the obstacles in implementing heat pipes in many applications is their difficult-to-model operation due to the many parameters that affect their performance. A promising alternative to classical modeling that emerges to perform accurate modeling of heat pipe systems is artificial intelligence (AI)-based modeling. This research reviews the applications of AI techniques for the modeling and control of heat pipe systems. This work discusses the AI-based modeling of heat pipes focusing on the influence of chosen input parameters and the utilized prediction models in heat pipe applications. The article also highlights various important aspects related to the application of AI models for modeling heat pipe systems, such as the optimal AI model structure, the models overfitting under small datasets conditions, and the use of dimensionless numbers as i... [more]

Thermochemical energy storage materials and reactors have been reviewed for a range of temperature applications. For low-temperature applications, magnesium chloride is found to be a suitable candidate at temperatures up to 100 °C, whereas calcium hydroxide is identified to be appropriate for medium-temperature storage applications, ranging from 400 °C up to 650 °C. For the high-temperature range (750−1050 °C), oxides of cobalt, manganese, and copper are found to have the redox behaviour required for thermochemical heat storage. However, some of these materials suffer from low thermal conductivities, agglomeration, and low cyclability and, therefore, require further improvements. The concept of enhancing thermal conductivities through additives such as nanomaterials has been encouraging. From an operational point of view, fluidized-bed reactors perform better than fixed- and moving-bed reactors due to better particle interactions. There is, however, a need for the reaction bed to be fu... [more]

Ultracapacitors are energy storage devices that have shown outstanding capability in a vast spectrum of applications, mainly in energy storage systems required to deliver short bursts of electrical energy. Ultracapacitors possess high power density while batteries possess high energy density. In this paper, a hybrid energy storage device comprising a lithium-ion ultracapacitor module and a lead acid battery was modeled, built, and tested for vehicular start−stop application, which requires a much larger number of engine cranking events than conventional vehicles. The combination of a lead acid battery with Li-ion ultracapacitors was chosen due to the fact that the vast majority of vehicles utilize lead acid batteries to crank the internal combustion engine. This allows retrofitting this hybrid setup in conventional vehicles along with the start−stop feature without inflicting damage to the already installed lead acid battery. The start−stop feature puts high stress on the lead acid bat... [more]

In situ Bio-Methanation (BM) is a recently developed biogas upgrading technique which finds application also in the Power to Gas (P2G) field. In this study a novel configuration of BM digester, the randomly packed Gas Stirred Tank Reactor (GSTR), was modelled. A 49 L reactor, in thermophilic conditions (55 °C) and at atmospheric pressure, was filled up with random packing on which the microbial populations could adhere. The feedstock used was Second Cheese Whey (SCW), liquid waste of cheese factories, rich in lactose (38 g/L), and its flowrate was chosen to obtain a Hydraulic Retention Time (HRT) of 30 days. The process was analyzed for different hydrogen inlet flowrates of 10 mL/min and 50 mL/min. The produced biogas was also recirculated in the reactor in order to transfer, into the liquid phase, as much hydrogen as possible. The model parameters were estimated by means of stationary state information of the reactor working without hydrogen injection, while a dynamical fitting was ne... [more]

Chromium is an element that possess several oxidation states and can easily pass from one to another, so its behavior in soils is very complex. For this reason, determining its fate in the environment can be difficult. In this research work we tried to determine which factors affect the chromium fractionation in natural soils, conditioning chromium mobility. We paid special attention to the parent material. For this purpose, extraction experiments were carried out on spiked soils incubated for 50−60 days, using H2O, CaCl2 and diethylenetriaminepentaacetic acid (DTPA). The most efficient extraction rate in all soils was achieved using water, followed by CaCl2 and DTPA. We obtained models with an adjusted R2 of 0.8097, 0.8471 and 0.7509 for the H2O Cr, CaCl2 Cr and DTPA Cr respectively. All models were influenced by the amount of chromium added and the parent material: amphibolite and granite influenced the amount of H2O Cr extracted, and schist affected the other two fractions (CaCl2 an... [more]

Due to the numerous side effects of synthetic pesticides, including environmental pollution, threats to human health, harmful effects on non-target organisms and pest resistance, the use of alternative healthy, available and efficient agents in pest management strategies is necessary. In this paper, the susceptibility of the cosmopolitan, polyphagous, stored-product pest Tribolium castaneum (red flour beetle) to the fumigation of the essential oils of two important medicinal and food additive plants, Satureja hortensis and S. intermedia, was investigated. The insecticidal properties of the essential oils were modeled and optimized using response surface methodology. It was found that a maximum significant mortality of 94.72% and 92.97% could be achieved within 72 h with the applications of 55.15 µL/L of S. hortensis (with the linear model) and 58.82 µL/L of S. intermedia (with the quadratic model), respectively. There were insecticidal terpenes and phenylpropanoids in both essential oi... [more]