On the basis of road tests, the authors assessed the feasibility of the vehicle body acceleration values for the purposes of assessing road surface characteristics in terms of its roughness. Short-term Fourier Transform (STFT) was used for the analysis of the recorded signal. The spectra obtained in successive frequency bands demonstrate the amplitudes originating from the natural vibrations of the rolling wheel and forces resulting from the interaction with the road roughness. The article focuses on the relationships between the road roughness and the ratios of individual amplitudes in a specific frequency band of the vehicle body acceleration values. Amplitude values derived on the basis of successive windows were averaged for analogous, arbitrarily assumed local frequency bands. The value characterizing the road surface condition provided the information regarding the mean amplitude value in specific frequency ranges depending on the instantaneous velocity of the car body and the condition of the road surface on which it was moving. In cases where the road was free of any visible roughness, the obtained mean amplitude value in the analyzed spectrum window, for the adopted vehicle velocity range from 50 km h to 100 km/h, did not exceed 0.02 m/s². It was also demonstrated that the road surface roughness leads to an increase in the mean amplitude value from 0.07 m/s² to 0.16 m/s².

The market demand for vehicles with reduced energy consumption, as well as increasingly stringent standards limiting CO₂ emissions, are the focus of a large number of research works undertaken in the analysis of the energy consumption of cars in real operating conditions. Taking into account the growing share of hybrid drive units on the automotive market, the aim of the article is to analyse the total unit energy consumption of a car operating in real road conditions, equipped with an advanced hybrid drive system of the PHEV (plug-in hybrid electric vehicles) type. In this paper, special attention has been paid to the total unit energy consumption of a car resulting from the cooperation of the two independent power units, internal combustion and electric. The results obtained for the individual drive units were presented in the form of a new unit index of the car, which allows us to compare the consumption of energy obtained from fuel with the use of electricity supported from the car’s batteries, during journeys in real road conditions. The presented research results indicate a several-fold increase in the total unit energy consumption of a car powered by an internal combustion engine compared to an electric car. The values of the total unit energy consumption of the car in real road conditions for the internal combustion drive are within the range 1.25–2.95 (J/(kg·m)) in relation to the electric drive 0.27–1.1 (J/(kg·m)) in terms of instantaneous values. In terms of average values, the appropriate values for only the combustion engine are 1.54 (J/(kg·m)) and for the electric drive only are 0.45 (J/(kg·m)) which results in the internal combustion engine values being 3.4 times higher than the electric values. It is the combustion of fuel that causes the greatest increase in energy supplied from the drive unit to the car’s propulsion system in the TTW (tank to wheels) system. At the same time this component is responsible for energy losses and CO₂ emissions to the environment. The results were analysed to identify the differences between the actual life cycle energy consumption of the hybrid powertrain and the WLTP (Worldwide Harmonized Light-Duty Test Procedure) homologation cycle.

One of the most important features of the proper operation of technical objects is monitoring the vibrations of their mechanical components. The currently significant proportion of the research methods in this regard includes a group of research methods based on the conversion of vibrations using sensors providing data from individual locations. In parallel with the continuous improvement of these tools, new methods for acquiring information on the condition of the object have emerged due to the rapid development of visual systems. Their actual effectiveness determined the switch from research laboratories to actual industrial installations. In many cases, the application of the visualization methods can supplement the conventional methods applied and, under particular conditions, can effectively replace them. The decisive factor is their non-contact nature and the possibility for simultaneous observation of multiple points of the selected area. Visual motion magnification (MM) is an image processing method that involves the conscious and deliberate deformation of input images to the form that enables the visual observation of vibration processes which are not visible in their natural form. The first part of the article refers to the basic terms in the field of expressing motion in an image (based on the Lagrangian and Eulerian approaches), the formulation of the term of optical flow (OF), and the interpretation of an image in time and space. The following part of the article reviews the main processing algorithms in the aspect of computational complexity and visual quality and their modification for applications under specific conditions. The comparison of the MM methods presented in the paper and recommendations for their applications across a wide variety of fields were supported with examples originating from recent publications. The effectiveness of visual methods based on motion magnification in machine diagnosis and the identification of malfunctions are illustrated with selected examples of the implementation derived from authors’ workshop practice under industrial conditions.

In order to identify the state of the wheel balance in a passenger car on the basis of vibrations of the car body under actual conditions of its operation, it is necessary to determine the impact of random interferences resulting from a changing environment. For this purpose, the criterion for the evaluation of the road surface condition was developed on the basis of longitudinal vibrations of the car body of the tested car in the speed range from 50 km/h to 110 km/h. Selected functions such as: probability distribution and methods in the frequency domain: short-time Fourier transform (STFT) and power spectral density (PSD) were used to analyse recorded signals.

Internal combustion engines are among the most commonly used propulsion units for drive systems in various industries such as land transportation, maritime transportation, and power generation. Their operation involves a continuous change of technical condition as a result of not only the combustion process but also their operation under conditions of variable load or ambient impact. It is therefore important to monitor the technical condition of internal combustion engines to ensure high performance and reliability over their lifetime. The article presents the test results obtained from incorrect operation of an internal combustion engine as a result of forced failures of the ignition and injection system. On this basis, a multicriteria comparison of the signal analysis of engine block vibrations was made, after the transformation of the signal from the time domain to the frequency domain, by using the induction technique obtained from the operation of decision tree algorithms. For this purpose, the amplitude spectrum in the frequency domain, scaled to absolute values of discretization for which teaching and testing data tables were created for successive harmonics, was determined for the engine block vibration signal being tested. On the basis of the developed algorithm using decision trees, a multicriteria data table was analyzed for which a compatibility path for the analyzed engine block vibration signal is created. In this way, it is confirmed with a specified degree of effectiveness, depending on the point of operation of the engine resulting from its crankshaft speed, that there is a possibility of detecting a preset ignition or injection system malfunction in the technical condition of the internal combustion engine with a probability up to about 72%.