The ever-growing number of electric vehicles requires increasing amounts of energy to charge their traction batteries. Electric vehicles are the most ecological when the energy for charging them comes from renewable energy sources. Obtaining electricity from renewable sources such as photovoltaic systems is also a way to reduce the operating costs of an electric vehicle. However, to produce cheap electricity from renewable energy sources, you first need to invest in the construction of a photovoltaic system. The article presents a strategic model for charging a fleet of electric vehicles with energy from photovoltaic systems. The model is useful for sizing a planned photovoltaic system to the energy needs of a vehicle fleet. It uses the Metalog family of probability distributions to determine the probability of producing a given amount of energy needed to power electric vehicle chargers. Using the model, it is possible to determine the percentage of energy from photovoltaic systems in the total energy needed to charge a vehicle fleet. The research was carried out on real data from an operating photovoltaic system with a peak power of 50 kWp. The approach presented in the strategic model takes into account the geographical and climatic context related to the location of the photovoltaic system. The model can be used for various renewable energy sources and different sizes of vehicle fleets with different electricity demands to charge their batteries. The presented model can be used to manage the energy produced both at the design stage of the photovoltaic system and during its operation.

In Poland, the market of electric field tractors is practically non-existent. There are individual models in offers dedicated to the agriculture made by foreign producers. However, these offers are presented mainly at agricultural fairs. The article presents the research on the needs of farms for electric tractors and presents the possibilities of developing electro mobility in this sector of the economy. Questionnaire was presented, data were collected from those working in the agricultural sector. The data will be used to gauge attitudes and opinions towards alternative power systems implemented in agriculture.

The TBN (Total Base Number) parameter is generally recognized by both engine oil processors and engine manufacturers as a key factor of oil quality. This is especially true for lubricating oils used in diesel and gas engines, which are exposed to relatively high temperatures and, therefore, require more effective protection against degradation. The FTIR spectrometry method together with a multivariate statistical software helped to create a model for the determination of TBN of worn motor oil SAE 15W-40 ACEA: E5/E7, API: CI-4. The best results were provided using a model FTIR with Partial Least Squares (PLS) regression in an overall range of 4000–650 cm⁻¹ without the use of mathematical adjustments of the scanned spectra by derivation. Individual spectral information was condensed into nine principal components with linear combinations of the original absorbances at given wavenumbers that are mutually not correlated. A correlation coefficient (R) between values of TBN predicted by the FTIR-PLS model and values determined using a potentiometric titration in line with the ČSN ISO 3771 standard reached a value of 0.93. The Root Mean Square Error of Calibration (RMSEC) was determined to be 0.171 mg KOH.g⁻¹, and the Root Mean Square Error of Prediction (RMSEP) was determined to be 0.140 mg KOH.g⁻¹. The main advantage of the proposed FTIR-PLS model can be seen in a rapid determination and elimination of the necessity to work with dangerous chemicals. FTIR-PLS is used mainly in areas of oil analysis where the speed of analysis is often more important than high accuracy.