The paper deals with the detection process of energy loss in electric railway hauling vehicles. The importance of efficient energy use in railways and cost-effective rail transport tendency toward regenerative braking energy are considered. In addition, the current situation and improvement opportunities to achieve efficient energy use are examined. Seven measurement series were performed with scheduled Railjet trains between Hegyeshalom and Győr railway stations in Hungary. This railway section is related to the Hungarian State Railways' No. 1 main railway line (between Budapest-Kelenföld and Hegyeshalom state board), which is a part of the international railway line between Budapest and Vienna (capitals of Hungary and Austria, respectively). This double-track, electrified railway line with traditional ballasted superstructures and continuously welded rail tracks is important due to the international passenger and freight transport between Germany, Austria, and Hungary. The value of the regenerative braking energy can be even 20-30% of the total consumed energy. This quite enormous untapped energy can be used for several aims, e.g., for comfort energy demand (air conditioning, heating-cooling, lighting, etc.) or energy-intensive starts. The article also investigates the optimization of regenerative braking energy by seeking the energy-waste locations and the reasons for the significant consumption. The train operator's driving style and habit have been identified as one of the main reasons. Furthermore, train driver assistance systems are recommended to save energy, which is planned for future research.

This research aims to investigate the adaptability of a measurement system or a process in determining the parameters of batteries. Methods are suggested for different applications, and properties gained by these measurements are specified. Deformations of lithium polymer batteries measured by various methodologies are also analyzed in detail. Changes in the geometry of worn-out batteries and the localization of the changes can be better understood by applying the results. The GOM ATOS and the GOM ARAMIS systems were applied to characterize lithium polymer batteries. Discontinuous tests were performed and the battery was discharged to 0 V and then fully charged for both methods. The advantages and disadvantages and the applicability of the two measurement systems were analyzed in this topic.

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.

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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.