The article analyzes the dynamics of the development of the electromobility sector in Poland in the context of the European Union and due to the economic situation and development of the electromobility sector in the contexts of Switzerland and Norway. On the basis of obtained data, a forecast was made which foresees the most likely outlook of the electric car market in the coming years. The forecast was made using the creeping trend method, and extended up to 2030. As part of the analysis of the effect of the impact of electromobility, an original method was proposed for calculating the primary energy factor (PEF) primary energy ratio in the European Union and in its individual countries, which illustrates the conversion efficiency of primary energy into electricity and the overall efficiency of the power system. The original method was also verified, referring to the methods proposed by the Fraunhofer-Institut. On the basis of all previous actions and analyses, an assessment was made of the impact of the development of the electromobility sector on air quality in the countries studied. Carbon dioxide tank-to-wheels emission reductions which result from the conversion of the car fleet from conventional vehicles to electric motors were then calculated. In addition to reducing carbon dioxide emissions, other pollutant emissions were also calculated, such as carbon monoxide (CO), nitrogen oxides (NO_x) and particulate matter (PM). The increase in the demand for electricity resulting from the needs of electric vehicles was also estimated. On this basis, and also on the basis of previously calculated primary energy coefficients, the emission reduction values have been adjusted for additional emissions resulting from the generation of electricity in power plants.

The power sector is currently experiencing a dynamic transformation, resulting not only from EU directives, but also from current problems, mainly related to ensuring energy security for customers. For this reason, in Poland, it was decided that the model of electricity market operation needed to be changed. A dual market has been created, and a separated segment is the capacity market. This solution operates, in addition to other power mechanisms, in many European Union countries, e.g., in France, Great Britain, and Italy. The experience of these countries indicates the positive impact of the power market on various aspects of the power sector, such as legal, economic, technical and technological, social, and infrastructural aspects, mainly due to technological neutrality and open competition between power suppliers. The creation of the structure of an energy market drastically changes the rules of energy management, which requires investigations concerning the impact of those factors on the energy sector in Poland. The aim of this work is to examine the impact of the power market on the Polish power sector, and to determine the impact of individual consequences on several predefined areas. For this purpose, a questionnaire survey was used. The purpose of a detailed analysis is to develop probable scenarios for the sustainable development of the Polish energy sector.

The article discusses the possibility of object detector usage in field of automated visual inspection for objects with specific parameters, specifically various types of defects occurring on the surface of a car tire. Due to the insufficient amount of input data, as well as the need to speed up the development process, the Transfer Learning principle was applied in a designed system. In this approach, the already pre-trained convolutional neural network AlexNet was used, subsequently modified in its last three layers, and again trained on a smaller sample of our own data. The detector used in the designed camera inspection system with the above architecture allowed us to achieve the accuracy and versatility needed to detect elements (defects) whose shape, dimensions and location change with each occurrence. The design of a test facility with the application of a 12-megapixel monochrome camera over the rotational table is briefly described, whose task is to ensure optimal conditions during the scanning process. The evaluation of the proposed control system with the quantification of the recognition capabilities in the individual defects is described at the end of the study. The implementation and verification of such an approach together with the proposed methodology of the visual inspection process of car tires to obtain better classification results for six different defect classes can be considered as the main novel feature of the presented research. Subsequent testing of the designed system on a selected batch of sample images (containing all six types of possible defect) proved the functionality of the entire system while the highest values of successful defect detection certainty were achieved from 85.15% to 99.34%.

The creep trend method is used for the analysis of the development of electric car production in three regions: The United States, the European Union and Japan. Based on vehicle registration and population growth data for each year the creep trend method using historical data for the years 2007–2017 is applied for forecasting development up to 2030. Moreover, the original method for calculating the primary energy factor (PEF) was applied to the analysis of power engineering systems in the regions investigated. The assessment of the effects of electromobility development on air quality has been performed, reduction values for pollutant and greenhouse gas emissions have been determined, which was the main objective of this manuscript. Mitigation of air pollutant emissions, i.e., carbon dioxide (CO₂), carbon monoxide (CO) and nitrogen oxides (NO_x) was estimated and compared to the eventual expected increase of emissions from power plants due to an increase of the demand for electricity. It can be concluded that electricity powered cars along with appropriate choices of energetic resources as well as electricity distribution management will play the important role to achieve the sustainable energy economy. Based on the emission reduction projections resulting from the projected increase in the number of electric cars, (corrected) emissions will be avoided in 2030 in the amount of over 14,908,000 thousand tonnes CO₂ in European Union, 3,786,000 thousand tonnes CO₂ in United States and 111,683 thousand tonnes CO₂ in Japan.

This article deals with solving the urgent scientific problem of the diagnostics of drives of technological robotized workplaces with support of sensors. The dependence of diagnostic parameters on the technical state of drives of automated technological systems, which is of great economic importance for industrial enterprises, is being investigated. Diagnostic models have been developed based on sensory systems to diagnose drive models of technological robotized workplaces. The use of these models may also include monitoring systems in which it is possible to build a system for identifying detected changes. These systems identify many contradictory changes and thereby reduce the false alarm frequency of monitoring sensory systems. Numerous methods for solving technical diagnostics problems are often based on methods based on mathematical models describing work processes, as well as on spectral analysis of measured parameters, such as vibrations, noise, and electric current. A fuzzy inference system for assessing the technical condition, a system for estimating the residual resource of drives, and asystem for calculating diagnostic intervals based on fuzzy knowledge have been developed. Based on the historical trend of the diagnostic parameters, the intelligent diagnostic system determines the current technical condition of the actuator and predicts future technical condition changes, determines the remaining service life and the time intervals for diagnostics. The analysis of the time spent on planned preventive maintenance of technological equipment makes it possible to conclude that, after the modernization of equipment in 2018, the repair time was reduced from 350 h to 260 h per year (26%). Since 2019, there is a tendency to increase repair time by 30 h each year.

Nowadays more and more emphasis is placed on the protection of the natural environment. Scientists notice that global warming is associated with an increase of carbon dioxide emissions, which results inter alia from the combustion of gasoline, oil, and coal. To reduce the problem of pollution from transport, the EU is introducing increasingly stringent emission standards which should correspond to sustainable conditions of the environment during the operation of motor vehicles. The emissivity value of substances, such as nitrogen oxides (NO_x), hydrocarbons (HC), carbon monoxide (CO), as well as solid particles, was determined. The aim of this paper was to examine, by means of simulation in the Scilab program, the exhaust emissions generated by the 1.3 MultiJet Fiat Panda diesel engine, and in particular, carbon monoxide and nitrogen oxides (verified on the basis of laboratory tests). The Fiat Panda passenger car was selected for the test. The fuels supplied to the tested engine were diesel and FAME (fatty acid methyl esters). The Scilab program, which simulated the diesel engine operation, was the tool for analyzing the exhaust toxicity test. The combustion of biodiesel does not necessarily mean a smaller amount of exhaust emissions, as could be concluded on the basis of information contained in the subject literature. The obtained results were compared with the currently valid EURO-6 standard, for which the limit value for CO is 0.5 g/km, and for NO_x − 0.08 g/km, and it can be seen that the emission of carbon monoxide did not exceed the standards in any case examined. Unfortunately, when analyzing the total emissions of nitrogen oxides, the situation was completely the opposite and the emissions were exceeded by 20–30%.