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Hybrid vehicles are gaining increasing global prominence, especially in the military, where unexpected breakdowns or even power deficits are not only associated with greater expense but can also cost the lives of military personnel. In some cases, it is extremely important that all battery cells and modules deliver the specified amount of capacity. Therefore, it is recommended to introduce a new measurement line of rapid diagnostics before deployment, in addition to the usual procedures. Using the results of rapid testing, we recommend the introduction of a hierarchical three-step diagnostics and assessment procedure. In this procedure, the key factor is the building up of a hierarchical tree-structured fuzzy signature that expresses the partial interdependence or redundancy of the uncertain descriptors obtained from the rapid tests. The fuzzy signature structure has two main important components: the tree structure itself, and the aggregations assigned to the internal nodes. The fuzzy signatures that are thus determined synthesize the results from the regular maintenance data, as well as the effects of the previous operating conditions and the actual state of the battery under examination; a signature that is established this way can be evaluated by “executing the instructions” coded into the aggregations. Based on the single fuzzy membership degree calculated for the root of the signature, an overall decision can be made concerning the general condition of the batteries.

This paper examines the sustainability of railways. A comprehensive international literature review was conducted on railway vehicles, traction, and railway permanent way. The main goal was to find the factors and parameters that affect railway sustainability the most. CO2 emissions from transportation, mining, raw material production, manufacturing, use, operation and maintenance, and demolition and restoration must be significantly reduced. Naturally, the attention will be on the considerable energy and financial savings. This article's main topics are sustainability, affordable and clean energy, industry, innovation, infrastructure, sustainable cities and communities, responsible consumption and production, climate action, and life on land. Building materials come from quarries and gravel pits, but availability is decreasing. Future pavement construction and maintenance require recycling demolition and industrial waste. Engineers must choose materials and technology that extend track lifetimes to ensure reliability, availability, maintainability, safety, sustainability, and economy in permanent railroad ways. Life-cycle costs can be reduced, e.g., by Building Information Modeling. Electric machinery is preferred for construction equipment, materials, and management. Sustainability, like grassed tracks and recyclable plastics, has improved urban life. Sheet metal forming using recycled materials and sustainability shows how important environmental protection is in car and train design. Electric road and rail propulsion are driven by environmental concerns, while supercapacitors and batteries are studied. In conclusion, by preferring rail for freight and passenger transport, both for private and public transport, energy savings and CO2 emissions can be up to 2-10 times higher than for other modes of transport.

Lithium-ion battery technology in the modern automotive industry utilizes highly temperature-sensitive batteries. Here, air cooling strategies will be the most applicable for the chosen example based on strategies for temperature control. Simulations have been utilized to evaluate the different thermal management strategies. A battery model was developed using the solutions offered by Computational Fluid Dynamics (CFD) simulation technology. It utilizes the heat produced by the discharge of the battery cells. Due to the simulation's limited computational capacity, the energy transfer model was implemented with a simplified but sufficiently complex physical mesh. Ten actual measurements were conducted in the laboratory to investigate the heating of the cell during the charging and discharging of 18650-type batteries. The results were applied to validate the simulation model. The simulation outcomes and thermal camera readings were compared. The cell-level numerical model was then extended to examine the temperature variation at the system level. The primary design objective is to achieve the highest energy density possible, which necessitates that the cells be constructed as closely as possible; however, increasing the distance between the cells can provide superior cooling from a thermal management perspective. The effect of varying the distance between individual cells on the system's heating was analyzed. Greater distance resulted in a more efficient heat transfer. It was also discovered that, in some instances, a small distance between cells produces inferior results compared to when constructed adjacently. A critical distance range has been established based on these simulations, which facilitates the placement of the cells.

The number of battery systems is also growing significantly along with the rise in electric and hybrid car sales. Different vehicles use different types and numbers of batteries. Furthermore, the layout and operation of the control and protection electronics units may also differ. The research aims to develop an approach that can autonomously detect and localize the weakest cells. The method was validated by testing the battery systems of three different VW e-Golf electric vehicles. A wide-range discharge test was performed to examine the condition assessment and select the appropriate state of charge (SoC) for all three vehicles. On the one hand, the analysis investigated the cell voltage deviations from the average; the tests cover deviations of 0 mV, 12 mV, 60 mV, 120 mV, and 240 mV. On the other hand, the mean value calculation was used to filter out possible erroneous values. Another important aspect was examining the relationship between the state of charges (SoC) and the deviations. Therefore, the 10% step changes were tested to see which SoC level exhibited more significant voltage deviations. Based on the results, it was observed that there are differences between the cases, and the critical range is not necessarily at the lowest SoC level. Furthermore, the load rate (current) and time of its occurrence play an important role in the search for a faulty cell. An additional advantage of this approach is that the process currently being tested on the VW e-Golf can be relatively simply transferred to other types of vehicles. It can also be a very useful addition for autonomous vehicles, as it can self-test the cells in the system at low power consumption.

The growing number of electric vehicles and devices drives the demand for lithium-ion batteries. The purpose of the batteries used in electric vehicles and applications is primarily to preserve the cells and extend their lifetime, but they will wear out over time, even under ideal conditions. Most battery system failures are caused by a few cells, but the entire system may have to be scrapped in such cases. To address this issue, the goal is to create a concept that will extend the life of batteries while reducing the industrial and chemical waste generated by batteries. Secondary use can increase battery utilization and extend battery life. However, processing a large number of used battery cells at an industrial level is a significant challenge for both manufacturers and users. The different battery sizes and compositions used by various manufacturers of electric vehicles and electronic devices make it extremely difficult to solve the processing problem at the system level. The purpose of this study is to look into non-destructive battery diagnostic options. During the tests, the condition of the cells is assessed using a new diagnostic technique, 3D surface digitalization, and the fusion of electrical parameters. In the case of surface digitalization, the digital image correlation (DIC) technique was used to estimate the cell state. The tests were conducted on various cells with widely used geometries and encapsulations. These included a lithium polymer (soft casing), 18650 standard sizes (hard casing), and prismatic cells (semi-hard). The study also included testing each battery at various charge states during charging and discharging. The findings help to clarify the changes in battery cell geometry and their localization. The findings can be applied to cell diagnostic applications such as recycling, quality assurance, and vehicle diagnostics.

Unmanned Aerial Vehicles, also known as UAVs, play an increasingly important part in daily life. However, the ever-increasing number of UAVs pose an ever-increasing threat to the transportation infrastructure. Despite their precision and general efficiency, infrastructural-scale Unmanned Aerial Systems (UASs) have a disadvantage regarding their capability of being implanted in the ecosystem. There are several reasons for this, but the primary bottleneck is that their systems are not transparent to society and have very complicated processes. As a result, the authors decided to investigate the functional properties of UASs and make improvements to those properties. Throughout the study, the authors’ primary focus was on analysis, which boosts productivity and ensures a significant level of safety for routine flights. The amount of power that a UAV uses depends on several variables, including the amount of power that its individual components require, the temperature of its surroundings, and the condition of the battery that it is powered by. Therefore, critical parameters and interdependencies are taken into account in the risk assessment strategy for energy-efficient Unmanned Aerial Vehicles (UAVs). In the case of UAVs, the algorithm performs a risk calculation before take-off to estimate the amount of risk that can be associated with the given flight time when using the provided battery. On the one hand, several instances of the pre-take-off state and how its parameters interact are investigated. On the other hand, they demonstrate the calculation of the risk while in flight, which is based on actual flight data.

The current paper deals with the numerical investigation of a unique designed pre-stressed reinforced concrete railway sleeper for the design speed of 300 km/h, as well as an axle load of 180 kN. The authors applied different methodologies in their research: traditional hand-made calculations and two types of finite element software. The latter were AxisVM and ABAQUS, respectively. During the calculations, the prestressing loss was not considered. The results from the three methods were compared with each other. The hand-made calculations and the finite element modeling executed by AxisVM software are adequate for determining the mechanical inner forces of the sleeper; however, ABAQUS is appropriate for consideration of enhanced and sophisticated material models, as well as the stress-state of the elements, i.e., concrete, pre-stressed tendons, etc. The authors certified the applicability of these methodologies for performing the dimensioning and design of reinforced concrete railway sleepers with pre-stressing technology. The research team would like to continue their research in an improved manner, taking into consideration real laboratory tests and validating the results from FE modeling, special material models that allow calculation of crackings and their effects in the concrete, and so that the real pattern of the crackings can be measured by GOM Digital Image Correlation (DIC) technology, etc.

Automatic transmission is a key factor for autonomous driving. The transmission condition is highly affected by the quality and quantity of transmission oil in the system. However, the oil condition is not monitored in the system, and the oil change interval and method are still a subject of discussion. This paper analyzes the effects of oil changes in automatic transmissions. The measurements were carried out before and after the oil change with the same external conditions. With the vibration measurement method, data can be collected without disassembling the parts and during operational conditions. Furthermore, time- and frequency-based analyses were conducted to compare different transmissions’ operations. The results have shown that the effect of oil degradation is measurable on the amplitude of the signals and, therefore, predictable with vibration diagnostics. During the evaluation, the maximum values were compared on measurements with at least a 2-s length.

Vehicle safety risk can be decreased by diagnosing the lithium-ion battery system of electric road vehicles. Real-time cell diagnostics can avoid unexpected occurrences. However, lithium-ion batteries in electric vehicles can significantly differ in design, capacity, and chemical composition. In addition, the battery monitoring systems of the various vehicles are also diverse, so communication across the board is not available or can only be achieved with significant difficulty. Hence, unique type-dependent data queries and filtering are necessary in most cases. In this paper, a Volkswagen e-Golf electric vehicle is investigated; communication with the vehicle was implemented via an onboard diagnostic port (so-called OBD), and the data stream was recorded. The goal of the research is principally to filter out, identify, and localize defective/weak battery cells. Numerous test cycles (constant and dynamic measurements) were carried out to identify cell abnormalities (so-called deviations). A query and data filtering process was designed to detect defective battery cells. The fault detection procedure is based on several cell voltage interruptions at various loading levels. The methodology demonstrated in this article uses a fault diagnosis technique based on voltage abnormalities. In addition, it employs a hybrid algorithm that executes calculations on measurement and recorded data. In the evaluation, a status line comprising three different categories was obtained by parametrizing and prioritizing (weighting) the individual measured values. It allows the cells to be divided into the categories green (adequate region), yellow (to be monitored), and red (possible error). In addition, several querying strategies were developed accordingly to clarify and validate the measurement results. The several strategies were examined individually and analyzed for their strengths and weaknesses. Based on the results, a data collection, processing, and evaluation strategy for an electric vehicle battery system have been developed. The advantage of the developed algorithm is that the method can be adapted to any electric or hybrid vehicle battery.