Military heavy vehicle drivers experience low-frequency vibrations that are associated with fatigue, drowsiness, and other adverse health effects. The existing research papers focus on performing different types of analysis, but few use advance signal processing tools based on recurrence plot representation; therefore, the main goal of this paper is to assess the whole-body vibration (WBV) and hand-arm vibration (HAV) exposure of a driver, comparing armoured personnel carriers and cargo destined vehicles. For this purpose, the power of a signal distributed over its frequency was analysed using power spectral density (PSD) and diagonal line quantification (DLQ) analysis. According to the results, in the case of the cargo vehicle, the driver experienced vibration dose values of frequency weighted acceleration above the limits during all three experimental tests, with a maximum value of 26.802 m/s², whereas the results in the case of the armoured personnel carrier are below the 5 m/s² limit imposed by the ISO 5349-2 standard. From the developed tests it was observed that, to protect the driver against the fatigue induced by the vibrations of the vehicle body, it is necessary to provide an elastic and also damping linkage between the vehicle and the driver’s seat. This is the only way to ensure the needed protection and it is, by far, the least expensive.

Background: A measurable feature of the efficiency of vehicle use in transportation companies is the revenue from transport orders, which has a significant impact on their profitability. Therefore, it is important to skillfully analyze the parameters related to the operation of vehicles and their impact on the bottom line. Transportation companies, when managing their operations, take steps to reduce operating costs. The above makes a large number of studies available in the literature on the analysis of vehicle damage or wear of system components, as well as ways to predict them. However, there is a lack of studies treating the impact of the parameters of specific orders on economic efficiency, which is a research niche undertaken in the following study. Methods: The purpose of this article was to analyze the economic efficiency of vehicle operation in terms of the financial security of enterprises. The main research problem was formulated in the form of the question of how the various parameters of a transport order affect its profitability. During our study, critical analysis of the literature, mathematical modeling and inference were used. A detailed analysis of transport orders executed by SMEs (small and medium-sized enterprises), which are characterized by a fleet of light commercial vehicles with a capacity of up to 3.5 t, was carried out in the FMCG (Fast-Moving Consumer Good) industry in Poland in 2021–2022. Due to the binary variable form, a logistic regression model was elaborated. The estimated parameters of the model and the calculated odds ratios made it possible to assess the influence of the selected factors on the profitability of orders. Results: Among other things, it was shown that in the case of daily vehicle mileage, the odds quotient indicates that with each additional kilometer driven, the probability of profitability of an order increases by 1%. Taking into account the speed of travel, it is estimated that with an increase in its value by 1 km/h, the probability of profitability of an order decreases by 3%. On the other hand, an increase in cargo weight by 1 kg makes the probability of a profitable order increase by 9%. Conclusion: Through this study, the limited availability of low-cost analytical tools that can be applied during transportation fleet management in SME companies was confirmed, as was the use of simple and non-expansive mathematical models. At the same time, they are not “black boxes” and therefore enable drawing and implementing model conclusions into operations. The results obtained can help shape the overall strategy of companies in the area of vehicle operation and can support the decision-making process related to the management of subsequent orders, indicating those that will bring the highest profit. The above is very important for SME companies, which often operate on the verge of profitability.

This paper is the result of a research program which focused on the statistical dynamics of vehicles. Most of the inputs of man-machine-field system have a random variation, so a systemic and statistical analysis of vehicle dynamics is obvious. In our study, data were obtained by measuring the dynamic parameters of vehicles and engines. Testing program aimed to capture a large range of operating regimes. To analyze the data the authors have used neural networks. There was adopted a NNARX (Neural Network Auto-Regressive with eXogene inputs) model with 4 inputs, 5 hidden units and 1 output. It can be concluded that the development of mathematical modeling using non-linear neural network can ensure the desired accuracy, conveniently is obtained by increasing the number of neurons in the hidden laws.

In many technical disciplines modem data analysis techniques has been successfully applied to understand the complexity of the system. The growing volume of theoretical knowledge about systems dynamic's offered researchers the opportunity to look for non-linear dynamics in data whose evolution linear models are unable to explain in a satisfactory manner. One approach in this respect is Recurrence Analysis - RA which is a graphical method designed to locate hidden recurring patterns, nonstationarity and structural changes. RA approach arose in natural sciences like physics and biology but quickly was adopted in economics and engineering. Meanwhile. The fast development of computer resources has provided powerful tools to perform this new and complex model. One free software which was used to perform our analysis is Visual Recurrence Analysis - VRA developed by Eugene Kononov. As is presented in this paper, the recurrence plot investigation for the analyzing of the internal combustion engine shows some of the RPA capabilities in this domain. We chose two specific engine parameters measured in two different tests to perform the RPA. These parameters are injection impulse width and engine angular speed and the tests are I11n and I51n. There were computed graphs for each of them. Graphs were analyzed and compared to obtain a conclusion. This work is an incipient research, being one of the first attempts of using recurrence plot for analyzing automotive dynamics. It opens a wide field of action for future research programs.

The simulation procedure has always been considered as a giant leap forward, especially in the field of basic designing of a product. There is nothing new underneath the basic concept, but the scientific and technical progress always brings up new techniques that improve simulation in its whole. When we talk about a vehicle, especially about a military one, we consider that it is much cheaper to simulate a process involving the weapon system than performing countless tests that are rather expensive. In this respect, we tried to develop a simulation mathematical model, check its accuracy with a set of extensive tests, prove it reliability and further extrapolate the behavior of the simulated model to a larger number of military vehicles of the same kind. It could help in various fields, such as diagnose (by comparing the simulated results with the real ones got from a faulty vehicle) or automatically regulating some functions (an intelligent vehicle, having an implemented, simulated model, that is able to feel the status of a subsystem in real time and regulate its behavior, accordingly). Hence, the paper presents a model that simulates the longitudinal dynamics of a tracked vehicle. It has been issued using Simulink module of Matlab programming environment. It aims at pointing out the performances of the vehicle. The models interface is friendly and its structure is modular. The main modules of the model are the engine, the torque converter, the transmission and the track. The engine and the torque converter are modeled using the experimental maps obtained by the tests that have been previously developed by the manufacturer. The main principle of the equations that describe the system is to set a balance among the forces (both active and resistive) that load the vehicle. The inputs of the model are the technical and dimensional features, provided by the manufacturer or experimentally determined. The output of the model is a dynamic behavior. Comparing the results with the experimental data eventually validates or invalidates the model. But the results were excellent, so the model was validated. Also, the results proved that the developed model is able to predict the performances of the take-off stage of the tracked vehicle.

The paper presents a possible method to diagnose a mechanical fault of an automotive system. Starting from the point of view that every fault of a mechanical system should introduce an abnormal component within the signal that describes the time history of a mechanical parameter we tried to find a way to reveal it.We were performing some tests involving a military vehicle with respect to the performances of its braking system. The tests were aiming at identifying a way to bring up-to-date the old weapon system from the braking systems point of view. During these tests we observed some anomalies concerning the pressure evolution within the braking cylinders of the vehicle. Some unusual but also systematic noises occurred. As a main issue at this point, the source of the noise should have been identified and filtered if necessary. We had to decide whether the noisy component of the signal is just a noise that should be removed by filtering the signal or it is a physical component of the mechanical parameter itself (not noise but a useful information).These procedures take time and they also request accurate knowledge as well as fine expertise in automotive testing. Since our Dept. has a long and rich practice in this respect, we assumed to processing data and give them a thorough interpretation. So, the first thing we did was to perform a frequency analysis, using classical methods. Usually, a simple frequency analysis cant provide information about a time variation of the frequency spectra due to the Fourier Transforms behavior, since it freezes the signal in time. A much more accurate analysis is the time-frequency analysis. However, observing both the amplitude and power spectra can lead to a useful conclusion. We concluded that the noise we met within the signal is due to the brake drums loss of circular shape (they turned into an oval, the process being known as ovalization). Hence, we cant talk about a noise as it is usually defined.