The reliability of internal combustion engines becomes an important aspect when traditional fuels with biofuels. Therefore, the development of prognostic models becomes very important for evaluating and predicting the replacement of traditional fuels with biofuels in internal combustion engines. The models have been made to model AVL 5402 engine emission, vibration, and sound pressure parameters using a three-stage statistical regression models. The fifteen parameters might be accurately predicted by a single statistic presented here. Both fuel type (diesel fuel and HVO) and engine parameters that can be adjusted were considered, since this analysis followed the symmetry of the methods. The data analysis process included three distinct steps and symmetric statistical regression testing was performed. The algorithm examined the effectiveness of various engine settings. Finally, the optimal fixed engine parameter and the optimal statistic were used to construct an ANCOVA model. The ANCOVA model improved the accuracy of prediction for all fifteen missing parameters.

Linear displacement measuring systems, like optical encoders, are widely used in various precise positioning applications to form a full closed-loop control system. Thus, the performance of the machine and the quality of its technological process are highly dependent on the accuracy of the linear encoder used. Thermoelastic deformation caused by a various thermal sources and the changing ambient temperature are important factors that introduce errors in an encoder reading. This work presents an experimental realization of the real-time geometric and thermal error compensation of the optical linear encoder. The implemented compensation model is based on the approximation of the tested encoder error by a simple parametric function and calculation of a linear nature error component according to an ambient temperature variation. The calculation of a two-dimensional compensation function and the real-time correction of the investigated linear encoder position readings are realized by using a field programmable gate array (FPGA) computing platform. The results of the performed experimental research verified that the final positioning error could be reduced up to 98%.

The strength and stiffness of the frame is one of the key indicators of vehicle structures. Insufficient stiffness causes vibration and noise, and is also less comfortable for both the passengers and the driver. Symmetry is required between the strength and comfort of the structural frame, which depends on vibration and noise. This article analyses the frame of the structure of a medium-sized passenger bus and its dynamic properties, when replacing materials of structural elements which do not affect the symmetry of the structure. The conducted theoretical and experimental modal analysis of the bus, allows for evaluating dynamic parameters and validating the theoretical model based on the experimental results. The optimization of the medium-sized passenger bus frame—by replacing the material of the ancillary frame elements with fiberglass—reveals that its dynamic characteristics change by up to 20%, comparing the values of the first three resonant frequencies with those of the steel structure. The obtained results show that replacing the material of ancillary frame elements with fiberglass, while maintaining the symmetrical arrangement of the elements in the structure, does not change the safety characteristics of the structure, reducing the mass of the frame by 11%, and shifting the coordinate of the centre of gravity vertically downwards, which is very important for stability, comfort and fuel consumption.