Publikační činnost Katedry elektroniky / Publications of Department of Electronics (430)

Permanent URI for this collectionhttp://hdl.handle.net/10084/83530

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Katedry elektroniky (430) v časopisech registrovaných ve Web of Science od roku 2003 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

Bibliografické záznamy byly původně vytvořeny v kolekci Publikační činnost akademických pracovníků VŠB-TUO, která sleduje publikování akademických pracovníků od roku 1990.

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Now showing 1 - 20 out of 82 results

Biodiesel production from marine macroalgae Ulva lactuca lipids using novel Cu-BTC@AC catalyst: Parametric analysis and optimization
(Elsevier, 2024) Yameen, Muhammad Zubair; Juchelková, Dagmar; Naqvi, Salman Raza; Noor, Tayyaba; Ali, Arshid Mahmood; Shahzad, Khurram; Rashid, Muhammad Imtiaz; Mahpudz, Aishah Binti
The pursuit of renewable fuels for the transportation sector, particularly for combustion engines like diesel, is crucial in reducing greenhouse gas emissions. This study introduces an innovative strategy for biodiesel production utilizing marine macroalgae Ulva lactuca as the primary feedstock, emphasizing sustainability and resource efficiency. Lipids were extracted from the macroalgae via a Soxhlet process and characterized using GC-MS and FTIR to ascertain fatty acid composition and functional groups. The Cu-BTC@AC catalyst, synthesized from the lipid-extracted algae residue via pyrolysis and hydrothermal treatment, underwent characterization using SEM-EDS, XRD, and FTIR techniques. Subsequently, the Cu-BTC@AC catalyst was employed in the transesterification process to efficiently convert the extracted algal lipids into biodiesel, achieving a high yield of 92.56 % under RSM-optimized conditions: 65 degrees C temperature, 3.96 wt% catalyst amount, 15:1 methanol-to-lipid ratio, and 140 min reaction time. Kinetic and thermodynamic parameters for biodiesel production were calculated as follows: E a = 33.20 kJ mol -1 , Delta H # = 30.39 kJ mol -1 , Delta S # = - 165.86 J mol -1 K -1 , and Delta G # = 86.48 kJ mol -1 . GC-MS analysis identified a significant FAME content in the biodiesel, comprising 98.12 % of its composition. Notably, the Cu-BTC@AC catalyst exhibited excellent reusability, maintaining 80.21 % biodiesel yield after the third cycle. Moreover, physicochemical analysis of the biodiesel confirmed its compliance with ASTM D6751 specifications, underscoring its potential as a viable alternative fuel for the transportation sector.
Fault-tolerant control based on current space vectors against total sensor failures
(MDPI, 2024) Tran, Cuong Dinh; Kuchař, Martin; Šotola, Vojtěch; Nguyen, Phuong Duy
This paper proposes a fault-tolerant control (FTC) strategy using the current space vectors to diagnose sensor failures and enhance the sustained operation of a field-oriented (FO) controlled induction motor drive (IMD). Three space vectors are established for the sensor fault diagnosis technique, including one converted from the measured currents and the other two calculated from the current estimation technique, respectively, measured and with reference speeds. A mixed mathematical model using three space vectors and their components is proposed to accurately determine the fault condition of each sensor in the motor drive. After determining the operating status of each sensor, if the sensor signal is in good condition, the feedback signal to the controller will be the measured signal; otherwise, the estimated signal will be used instead of the failed signal. Failure states of the various sensors were simulated to check the effectiveness of the proposed technique in the Matlab/Simulink environment. The simulation results are positive: the IMD system applying the proposed FTC technique accurately detected the failed sensor and maintained stability during the operation.
Plastic particles in urban compost and their grain size distribution
(Elsevier, 2024) Brťková, Hana; Růžičková, Jana; Slamová, Karolina; Raclavská, Helena; Kucbel, Marek; Šafář, Michal; Gikas, Petros; Juchelková, Dagmar; Švédová, Barbora; Flodrová, Šárka
Gathering information on plastic particles in composts and the processes they undergo is important in terms of potentially limiting their further entry into the environment, for example, in improving the fertilising properties of soils. Microplastics (MPs) were determined in composts produced from urban greenery. They are present in decreasing order: polyethylene terephthalate, polystyrene, polyethylene, and polypropylene. The determination of polymers and additives used to improve their properties was performed by pyrolysis and gas chromatography with mass spectrometric detection (Py-GC/MS). Additives and microplastics are most concentrated in composts in the 0.315-0.63 and 0.63-1.25 mm grain size class, together with the carbon contained in the compost dry matter. Additives form 0.11-0.13% of MPs in dry matter of compost. The average concentration of microplastics in the particle size class from 0.63 to 1.25 mm is 2434 +/- 224 mg/kg; in the total sample of composts, it is 1368 +/- 286 mg/kg of P-MPs. For composts with particle size <2.5 mm, a relationship between the C/N ratio and the plastic particle concentration was statistically significant. It documents a similar behaviour of lignocellulose and plastic particles during the degradation processes. A relationship between the concentration of polymer markers and additives in the compost dry matter and their concentrations in the leachate has been demonstrated. The leachability from compost is higher for additives than for chemical compounds originating from the decomposition of the main components of MPs. The suitability of the use of the compost for agricultural purposes was monitored by the germination index (GI) for watercress. The lowest value of the GI was determined in the particle size class from 0.63 to 1.25 mm. The leachability of polymer markers and additives alone cannot explain the low GI value in this grain size class. The GI value is also influenced by the leachability of chemical compounds characterised by the value of dissolved organic carbon (DOC) and water-leachable nitrogen (N-w). A statistically significant dependence between DOC/N-w and the germination index value was found.
Towards greener approach: Techno-economic insights into formaldehyde bio production from a hybrid pine and mustard biomass combination
(Elsevier, 2024) Kazmi, Bilal; Shareef, Rameez; Noman, Sarmad; Saeed, Sibra; Zehra, Tabbassum; Masood, Zehra; Albasher, Gadah; Juchelková, Dagmar
In an era marked by environmental crises and dwindling fossil resources, the need to revolutionize industrial processes for sustainability is paramount. Formaldehyde synthesis, a pivotal precursor in industries spanning polymers, resins, and textiles, stands at a critical juncture where innovation and necessity intersect. Conventional methods of formaldehyde production, despite their efficiency, remain tethered to non-renewable feedstocks and energy-intensive techniques, perpetuating ecological harm and resource constraints. This study explores ecofriendly pathways for formaldehyde production. Recent strides in bio-based chemistry enable the creation of formaldehyde from renewable biomass, reducing energy use and carbon emissions. Decentralized production with locally sourced biomass boosts supply chain resilience and community-centered sustainability. The research employs Aspen Plus (R) software to model a two-step process: gasification of a hybrid pine and mustard biomass blend to produce bio-methanol, followed by its oxidation into formaldehyde. Sensitivity analyses demonstrate temperature's impact on syngas composition, with higher temperatures favoring hydrogen production. The airto-biomass ratio affects carbon dioxide content and energy content, crucial for efficient energy production. In formaldehyde synthesis, the air-to-methanol ratio significantly influences yield. Economically, formaldehyde bio- production shows promise, with an 8.50% return on investment and a 22.16-year payback period. An annual net profit of $2.41 million is projected, with a break-even point at $53.47 million in total sales revenue. This research underscores the convergence of sustainability, innovation, and economic viability in formaldehyde bioproduction, offering valuable insights for environmentally friendly chemical manufacturing and the broader transition to ecological progress.
State-of-the-art review of biomass gasification: Raw to energy generation
(Wiley, 2024) Taqvi, Syed Ali Ammar; Kazmi, Bilal; Naqvi, Salman Raza; Juchelková, Dagmar; Bokhari, Awais
Despite the increasing global need for sustainable energy, biomass gasification is becoming a highly promising method for transforming raw biomass into usable energy. The present review article analyzes the essential aspects of biomass-based energy production, starting with an assessment of existing energy needs and the crucial contribution that biomass can make in fulfilling these demands. The research investigates recent advancements in several biomass gasification methods, explaining their mechanics and discussing the related difficulties. The research conducts a thorough evaluation of the efficiency, yield, and environmental consequences of biomass gasification, aiming to determine the feasibility of the technique. In addition, the study rigorously assesses the techno-economic factors of energy generation from biomass, providing valuable information on the economic viability and scalability of various biomass gasification techniques. The present study is focused on providing a comprehensive understanding of biomass gasification by analyzing current improvements and conducting a techno-economic comparison to make well-informed decisions for a sustainable energy future.
Harnessing the power of functionalized biochar: progress, challenges, and future perspectives in energy, water treatment, and environmental sustainability
(Springer Nature, 2024) Yameen, Muhammad Zubair; Naqvi, Salman Raza; Juchelková, Dagmar; Khan, Muhammad Nouman Aslam
The swift advancement of sustainable energy technologies, coupled with the urgent need to address environmental challenges, has generated considerable interest in the multifaceted applications of biochar materials to promote energy, water, and environmental sustainability. This comprehensive review examines recent advancements in the production and applications of functionalized biochar materials, emphasizing their pivotal roles in energy conversion and storage, wastewater treatment, CO2 reduction, soil amelioration, and the promotion of carbon neutrality within a circular economy framework. The functionalization of biochar materials involves surface chemistry and porosity modifications, achieved through techniques like templating, chemical activation, metal impregnation, or heteroatom doping. These modifications substantially enhance the catalytic activity, energy storage capacity, and cycling stability of biochar materials, making them particularly effective in diverse energy applications such as water splitting, fuel cells, and supercapacitors. Additionally, functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment, proficiently removing pollutants like heavy metals, organic contaminants, and nutrients, thereby facilitating resource recovery from wastewater. The review also underscores the potential of functionalized biochar materials in CO2 capture and conversion, exploring innovative strategies to augment their CO2 adsorption capacity and state-of-the-art catalytic processes for transforming captured CO2 into valuable fuels and chemicals. In summary, this review offers valuable insights into the recent advancements in biochar research, underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.
Environmental impact assessment of the coal yard and ambient pollution
(Springer Nature, 2024) Kucbel, Marek; Raclavská, Helena; Slamová, Karolina; Šafář, Michal; Švédová, Barbora; Juchelková, Dagmar; Růžičková, Jana
This study investigates the vertical distribution of pollutants emitted from coal yards using unmanned aerial vehicles (UAVs). Vertical concentration measurements of black carbon (BC) and particulate matter (PM) in a range of 1 m to 100 m above ground level (AGL) in the central coal yard showed clear spatial patterns and gradients of these pollutants. In addition, measurements were taken at specific heights (1 m, 30 m AGL, and 60 m AGL) at seven locations approximately 3 km from the yard. Thirteen measurements were carried out during the non-heating period under similar weather conditions. The measured BC concentrations decreased significantly with increasing altitude, with ground-level concentrations reaching 1.88 +/- 0.61 mu g/m3 and decreasing by over 46% at 80 m AGL. Similarly, PM10 concentrations at 60 m AGL decreased by 21.7%, with values of 25.99 +/- 9.24 mu g/m3 measured near the ground level and 16.52 +/- 8.31 mu g/m3 at 60 m AGL. The maximum coal particle pollution from the coal depot ranges from 500 to 1,000 m. The study showed a significant decrease in BC concentrations with height above the coal yard surface. Concentrations of PM10 and PM10-TSP showed a complex distribution influenced by local emissions and long-range particle transport. Meteorological factors, especially wind speed and direction, significantly influenced the pollutant dispersion. In addition, higher pollutant concentrations were measured during dry periods than after rainfall. The findings of this study contribute to a better understanding of the dispersion patterns and potential impacts of coal dust, enabling the implementation of targeted mitigation strategies and improved pollution control measures.
Modified fuzzy logic PI speed controller with scheduling boundaries of integral time constant for PMSM drive
(Sigma Not, 2023) Vo, Hau Huu; Brandštetter, Pavel
In order to obtain high performance speed response in pulse-width-modulation direct torque controlled drive of permanent magnet synchronous motor, fuzzy logic is utilized to update parameters of proportional-integral speed controller. However, overshoot and undershoot of speed response are still high, especially at times of load torque change. For reduction of the overshoot and undershoot, boundaries of integral time constant in fuzzy logic are tuned according to speed error during overshoot and undershoot. Theoretical assumptions are validated via simulations.
Instrumentation for verification of shunt active power filter algorithms
(MDPI, 2023) Baroš, Jan; Bilík, Petr; Jaroš, René; Danys, Lukáš; Strossa, Jan; Hlavatý, Lukáš; Martinek, Radek
This article presents a comprehensive system for testing and verifying shunt active power filter control methods. The aim of this experimental platform is to provide tools to a user to objectively compare the individual control methods. The functionality of the system was verified on a hardware platform using least mean squares and recursive least squares algorithms. In the experiments, an average relative suppression of the total harmonic distortion of 22% was achieved. This article describes the principle of the shunt active power filter, the used experimental platform of the controlled current injection source, its control system based on virtual instrumentation and control software and ends with experimental verification. The discussion of the paper outlines the extension of the experimental platform with the cRIO RTOS control system to reduce the latency of reference current generation and further planned research including motivation.
Incidence and spread of additives from co-combustion of plastic waste in domestic boilers in indoor and outdoor environments around the family house
(Elsevier, 2023) Růžičková, Jana; Raclavská, Helena; Kucbel, Marek; Pfeifer, Christoph; Juchelková, Dagmar; Hrbek, Jitka; Šafář, Michal; Slamová, Karolina; Švédová, Barbora; Kantor, Pavel
The additives released from plastic waste during co-combustion significantly influence indoor air quality. It was found that the unauthorised burning of plastics in households increased the additive concentrations in the indoor air of living spaces by an average of 5 μg/m3. This effect was observed from the difference between background concentrations (indoor quality during combustion of wood) and concentrations during the co-combustion of plastics. The one-way ANOVA analysis shows that indoor air quality is affected not only by the migration of pollutants from the boiler room within the indoor environment (infiltration) but also by air exchange with emissions and outdoor air. The highest concentrations of released additives in the boiler room were found for polystyrene > polypropylene > polyethylene terephthalate > polyethylene (low-density polyethylene and high-density polyethylene). Phthalates from polystyrene (21.16 ± 3.15 μg/m3) were released at the highest concentration, while phthalates from other plastics reached approximately half of this value. During the combustion of high-density polyethylene with softwood, chemical compounds from the residuals of content in plastic packaging were identified in the air (6.26 ± 0.31 μg/m3). Almost all these compounds show significant adverse health effects (irritation of the skin and the respiratory system), and some are carcinogenic.
Municipal sludges as sources of energy or nutrients – What is the best?
(Elsevier, 2023) Raclavská, Helena; Růžičková, Jana; Šafář, Michal; Kucbel, Marek; Slamová, Karolina; Švédová, Barbora; Juchelková, Dagmar; Kantor, Pavel
The decision on the optimal use of sludges from wastewater treatment plants is still very complex, even when applying the principles of sustainability and circular economy. Interest in the energy use of sludges is conditioned not only by their inclusion among biowaste but also by the availability of technologies that meet emission limits and newly by the possibility of extending anaerobic digestion processes to hydrogen production. The use of sludges in agriculture as a source of carbon and nutrients is limited by concerns about the occurrence of anthropogenic organic compounds and especially micropollutants that can migrate in individual environmental compartments. Based on information from the Globally Harmonised System of Classification and Labelling of Chemicals, 287 compounds of anthropogenic origin in sludge were divided into five groups: compounds causing environmental risk, health risk, acute toxicity, irritant, and no impact. The group of compounds causing environmental risk (highly toxic for the aquatic environment) includes 42 compounds. Phytotoxicity tests (Lepidium sativum) in relation to other parameters characterising sludge stability have shown that the key parameter for achieving a germination index >85% is the amount of organic matter expressed as chemical oxygen demand (COD) and conductivity.
Prediction and performance optimisation of a DI CI engine fuelled diesel–Bael biodiesel blends with DMC additive using RSM and ANN: Energy and exergy analysis
(Elsevier, 2023) Pitchaiah, S.; Juchelková, Dagmar; Sathyamurthy, Ravishankar; Atabani, A. E.
Synthesis of biofuel from bioresources represents one of the greatest propitious options for achieving a cleaner production of energy and the global circular bio-economy. The superior cetane rating of biodiesel makes it a fitting fuel for CI diesel engines. The present study aims to valorise Bael seeds for biodiesel production. Bael is a species of tree indigenous to India. The diesel-Bael biodiesel was blended with dimethyl carbonate (DMC) as an ignition enhancer and investigated in a selected diesel engine. This work reports that the Bael biodiesel blend gets a tolerable level of BTE against neat fossil diesel. An utmost BTE of 30.68% was achieved with B15DMC5 which is very close to diesel (31.8%) at peak load. Certainly, BSFC was suppressed and emissions lessened by DMC inclusion. For instance, the CO and HC emissions substantially reduced to a minimum of 0.19% and 179 ppm with the B17.5DMC2.5 blend at peak load. NOx emission is directly proportional to Bael biodiesel concentration, Notably, NOx emission is well controlled at 50% and 75% load even though with the increasing biodiesel concentration in the blend. Though, control of emissions at peak load is still a crucial issue. Nevertheless, the DMC additives controlled the NOx emission at peak load. B15DMC5 blend exhibits progress in combustion through the optimized value of HRR, CGP, and CGT against B20. The presence of NOx and smoke opacity without additives is suppressed up to 7% and 10% with additives. Availability (exergy) and exergy efficiency at different loads of both neat diesel and blended fuels, mainly shaft, cooling water, and exhaust availability were calculated. The results of the study illustrated that the input availability increased at peak loads, as well as gross work output, was maximum at peak load due to higher fuel exergy present in the combustion chamber. A maximum exergy efficiency of 68% was recorded by B15DMC5 at peak load. Finally, the process optimization by RSM has been validated by experimental results and further authenticated with ANN. The results of the RSM model promote it as statistically significant. Generate the regression equation for all output responses. The optimized operating parameters of engine load of 50%, 10% of biodiesel blend, and additive concentration of 3.59% achieved the most optimum output response. The results of the predicted optimized condition of BTE, BSFC, CO, HC, NOx, and Smoke opacity showed 24.051%, 0.441861 kg/kW hr, 0.2028%, 113.607 ppm, 316.099 ppm, and 14.4286% respectively. The R2 values from RSM and ANN DoE models were 0.992834 and 0.99984. This study concludes that a superior precision certainty from both RSM and ANN models is beneficial for engine overall performance estimation. This phenomenon provides a good sign to implement the ANN to forecast engine operational behavior in the future. The novel approach of process optimization by RSM and ANN for Bael biodiesel with DMC blended fuel operate DI CI engine supports the SDGs of the UN such as Good health and Well being (SDG: 3), Affordable and Clean Energy (SDG: 7), Responsible Consumption and Production (SDG: 12), Climate Action (SDG: 13) and Life on Land (15).
Techno-economic assessment of sunflower husk pellets treated with waste glycerol for the Bio-Hydrogen production – A Simulation-based case study
(Elsevier, 2023) Kazmi, Bilal; Taqvi, Syed Ali Ammar; Naqvi, Salman Raza; Mirani, Asif Ali; Shahbaz, Muhammad; Naqvi, Muhammad; Juchelková, Dagmar; Eldesoky, Gaber E.
Biomass gasification is a renewable and sustainable energy source with high product yield and economic viability. This study presents a conceptual model for producing biohydrogen from sunflower husks pellets and waste glycerol using the Aspen Plus® simulation tool. The study analyzes the effects of temperature, steam to biomass rate, and CaO rate on the product gas. The results show that increasing the gasifier temperature from 600 to 750 °C increases H2 volume percentage to 92%. Optimizing steam to biomass rate and CaO to biomass rate also affects the volume % of H2 gas in the product gas. The study concludes that a CaO rate of 1.8:1 and a steam-to-biomass ratio of 1.75:1 produce high H2 content with a high heating value of gas. The total capital cost incurred for the system is $2.93 × 106, with a total operating cost of $14.58 × 106/yr.
State-of-the-art review on the steel decarbonization technologies based on process system engineering perspective
(Elsevier, 2023) Kazmi, Bilal; Taqvi, Syed Ali Ammar; Juchelková, Dagmar
Decarbonization of steel manufacturing requires policies to reduce carbon emissions through technology development, renewable energy use, carbon pricing mechanisms, research and development, circular economy practices, energy management systems, and collaboration between industry, government, and academia. This policy assertion seeks to encourage the development and implementation of technologies that can reduce carbon emissions in steel manufacturing processes, such as hydrogen-based steelmaking, carbon capture and utilization, and energy-efficient processes. Low-carbon technologies, renewable energy, a carbon price, material efficiency, and collaboration are key strategies to reduce carbon emissions in the steel sector. Low-carbon energy sources such as wind and solar can be used to power the steelmaking process, while carbon pricing can reduce industrial emissions. To reduce emissions, stakeholders from all stages of the value chain must collaborate to develop decarbonization strategies, such as funding R&D, exchanging knowledge, and offering carbon-cutting incentives. This review provides a conceptual design approach proposed for the successful analysis of steel decarbonization potential from a process system engineering perspective. Challenges and opportunities are also been highlighted with respect to energy, economics, and environmental aspect. Technologies still require more advancement in terms of operation and energy intensity as technical and economic aspects are found superior to conventional technologies.
Aspen plus simulation model of municipal solid waste gasification of metropolitan city for syngas production
(Elsevier, 2023) Mehdi, Muzaffar; Taqvi, Syed Ali Ammar; Shaikh, Asif Ahmed; Khan, Saad; Naqvi, Salman Raza; Shahbaz, Muhammad; Juchelková, Dagmar
It is apparent that the population, in general, is increasing and this rise in population increases both the waste production and energy requirements. The main objective of this study to tackle the increasing demand for energy and recycling waste into energy. We will be using Waste to Energy (WTE) technique to convert MSW into energy such as bio-fuel, Hydrogen-rich gas or Syngas. The model of simulation of steam gasification of MSW used in this study is based on ASPEN PLUS. Temperature, the ratio of steam to MSW, and the ratio of air to MSW have all been adjusted in a wide range. For the production of syngas, the impact of carbon conversion efficiency (CCE) and cold gas efficiency (CGE) has been studied. The results showed that by increasing the temperature from 700 °C to 1300 °C the H2 concentration increased from 37 to 51 mol%, CO concentration increases from 35 to 40 mol% and CO2 concentration decreases from 5 to 0.025 mol%. CGE also decreases from 95 to 82% while CCE increases from 80 to 85%. By increasing the steam to MSW ratio from 0.05 to 0.8 mass fraction the H2 concentration increased from 34 to 44 mol% but is maximum at 0.35 at which it is 53 mol%, CO concentration decreases from 43 to 16 mol% and CO2 concentration increases from 0.025 to 8.5 mol%. CGE and CCE also decreases from 94 to 45% and 90 to 44% respectively.And lastly by increasing the air to MSW ratio from 0.01 to 0.5 mass fraction the H2 concentration decreases from 47 to 39 mol% but peaks at 0.05 at which it is 48 mol%, CO concentration decreases from 41 to 31 mol% and CO2 concentration increases from 0.085 to 3.5 mol%. CGE and CCE also decreases from 92 to 55% and 87 to 70% respectively. To compare our data with the base case we have kept temperature at 900 °C S/MSW ratio at 0.11 and air/MSW ratio at 0.05 and it is concluded that our simulation is inline with the base case as our results are off by just 1–3% in terms of yield.
Anaerobic digestion of dry palms from five cultivars of Algerian date palm (Phoenix dactylifera L.) namely H'mira, Teggaza, Tinacer, Aghamou and Takarbouchet: A new comparative study
(Elsevier, 2023) Djaafri, Mohammed; Drissi, Aicha; Mehdaoui, Sabrina; Kalloum, Slimane; Atelge, M. R.; Khelafi, Mostefa; Kaidi, Kamel; Salem, Fethya; Tahri, Ahmed; Atabani, A. E.; Štěpanec, Libor
The lignocellulosic properties of date palm waste (dry palm) differ significantly from one cultivar to another, which affects the anaerobic digestion (AD) process. This study is believed to be amongst the first to evaluate the influence of date palm cultivars on the biomethane yield in order to offer an annual, continuous and cost-effective biogas production model. In this work, 5 cultivars from date palm waste namely; H'mira (H), Teggaza (Tg), Tinacer (Ti), Aghamou (Ag) and Takarbouchet (Tk) were evaluated for biogas production. All experiments were performed for 45 days with 5 reactors in triplicate under mesophilic conditions (37 °C). The highest methane yield of 231.87 ml of CH4/g of Volatile Solid (VS) was obtained with the Ag cultivars with a difference that varied between 37% and 62% depending on the cultivar type. These results indicate that the date palm cultivars massively influence the biomethane yield, it may give an opportunity for researchers to select the most suitable cultivars for methane production and provide opportunities to valorize other cultivars on other beneficial uses, such as adsorption, thermal insulation, or charcoal production etc.
Novel method for determining internal combustion engine dysfunctions on Platform as a Service
(MDPI, 2023) Harach, Tomáš; Šimoník, Petr; Vrtková, Adéla; Mrověc, Tomáš; Klein, Tomáš; Ligori, Joy Jason; Kořený, Martin
This article deals with a unique, new powertrain diagnostics platform at the level of a large number of EU25 inspection stations. Implemented method uses emission measurement data and additional data from significant sample of vehicles. An original technique using machine learning that uses 9 static testing points (defined by constant engine load and constant engine speed), volume of engine combustion chamber, EURO emission standard category, engine condition state coefficient and actual mileage is applied. An example for dysfunction detection using exhaust emission analyses is described in detail. The test setup is also described, along with the procedure for data collection using a Mindsphere cloud data processing platform. Mindsphere is a core of the new Platform as a Service (Paas) for data processing from multiple testing facilities. An evaluation on a fleet level which used quantile regression method is implemented. In this phase of the research, real data was used, as well as data defined on the basis of knowledge of the manifestation of internal combustion engine defects. As a result of the application of the platform and the evaluation method, it is possible to classify combustion engine dysfunctions. These are defects that cannot be detected by self-diagnostic procedures for cars up to the EURO 6 level.
Applications of machine learning in thermochemical conversion of biomass - A review
(Elsevier, 2023) Khan, Muzammil; Naqvi, Salman Raza; Ullah, Zahid; Taqvi, Syed Ali Ammar; Khan, Muhammad Nouman Aslam; Farooq, Wasif; Mehran, Muhammad Taqi; Juchelková, Dagmar; Štěpanec, Libor
Thermochemical conversion of biomass has been considered a promising technique to produce alternative renewable fuel sources for future energy supply. However, these processes are often complex, labor-intensive, and time-consuming. Significant efforts have been made in developing strategies for modeling thermochem-ical conversion processes to maximize their performance and productivity. Among these strategies, machine learning (ML) has attracted substantial interest in recent years in thermochemical conversion process optimi-zation, yield prediction, real-time monitoring, and process control. This study presents a comprehensive review of the research and development in state-of-the-art ML applications in pyrolysis, torrefaction, hydrothermal treatment, gasification, and combustion. Artificial neural networks have been widely employed due to their ability to learn extremely non-linear input-output correlations. Furthermore, the hybrid ML models out-performed the traditional ML models in modeling and optimization tasks. The comparison between various ML methods for different applications, and insights about where the current research is heading, is highlighted. Finally, based on the critical analysis, existing research knowledge gaps are identified, and future recommen-dations are presented.
Review of fundamental active current extraction techniques for SAPF
(MDPI, 2022) Baroš, Jan; Šotola, Vojtěch; Bilík, Petr; Martinek, Radek; Jaroš, René; Danys, Lukáš; Šimoník, Petr
The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable to minimize losses due to the increase in the number of nonlinear loads (deformed power). Currently, there is rapid development in new adaptive, non-adaptive, and especially hybrid methods of digital signal processing. Nowadays, modern methods of digital signal processing maintain a key role in research and industrial applications. Many of the best practices that have been used to control shunt active power in industrial practice for decades are now being surpassed in favor of new progressive approaches. This systematic research review classifies the importance of using advanced signal processing methods in the field of shunt active power filter control methods and summarizes the extant harmonic extraction methods, from the conventional approach to new progressive methods using genetic algorithms, artificial intelligence, and machine learning. Synchronization techniques are described and compared as well.
Sensor fault diagnosis method based on rotor slip applied to induction motor drive
(MDPI, 2022) Tran, Cuong Dinh; Kuchař, Martin; Sobek, Martin; Šotola, Vojtěch; Dinh, Bach Hoang
A novel diagnosis method based on the rotor slip is proposed in the paper to correctly detect current and speed sensor failures during the induction motor drive (IMD) operation. In order to enhance reliability and avoid confusion in the diagnosis algorithm due to the influence of measured signal quality, each fault type is determined in a priority order defined by the diagnosis method. Based on the features of the IMD applying the field-oriented control (FOC) technique, an innovative model uses the measured currents and reference speed as the input signals to estimate the rotor slip for the current sensor fault detection. After verifying the quality of the feedback of the current signals, a speed sensor fault function is continued, and performs according to relations among the reference speed, estimated speed based on the sliding mode method, and measured rotor speeds. Finally, the estimated quantities are selected to replace the wrong measured current or speed signals. The feasibility of the proposed approach is verified by simulations using Matlab-Simulink software as well as by practical experiments using an IMD prototype with a rated power of 2.2 kW and a DSC-TMS320F28335-based control system. The obtained simulation and experimental results demonstrated the feasibility, effectiveness, and reliability of the proposed diagnosis technique in detecting sensor failures and maintaining the stable operation of the IMD.

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