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To reduce noise in a HVAC system for railway application the usage of micro-perforated panels (MPP) is proposed. MPPs offer some favorable characteristics, like robustness and durability in harsh environments and the possibility to optimize absorption in desired frequency bands. The underlying acoustic mechanism can be modelled via an equivalent fluid in accordance with the Johnson-Champoux-Allard (JCA) approach, treating the MPPs as a porous material with rigid frame. This allows to conduct the necessary acoustic pre-evaluation in complex HVAC application scenarios in order for the MPPs to substitute the commonly used foam and fibrous absorber materials.

In the earth-moving industry manymachines work in typical loading cycles that are repeated periodically. For a statistic examination of the overall load configuration and the dynamic fatigue of these machines, it is necessary to develop an adaptive algorithm for the separation of the individual cycles. This article presents methods for an automatic detection of the cycle borders. Adaptive algorithms are constructed for a reliable separation at different points during the loading cycle. Additionally, each cycle can be divided into different operating phases by extending the algorithms to a tool for the identification of each single phase. To avoid problems during the cycle detection, the data are checked for outliers and sensor faults first. To guarantee a meaningful statistical analysis, the separated cycles have to be tested for incorrect or atypical characteristics. Therefore, statistical classification numbers are calculated and compared for each cycle.

Calibrating a vehicle’s powertrain for dynamic operation needs to focus on efforts to mitigate the risks of thermal overload which may arise in the stator or rotor components of an e-motor. Risks also may arise for expected NVH or durability targets, with torque and torque “oscillations” acting as primary sources for the vehicles’ NVH behavior. Both topics, temperature measurement of stator and rotor as well as dynamic torque measurements of the powertrain’s drive shaft are addressed with examples demonstrating the sensors applications in normal test bed and vehicle configurations.

Dynamometer (dyno) durability testing plays a significant role in reliability and durability assessment of commercial engines. Frequently, durability test procedures are based on warranty history and corresponding component failure modes. Evolution of engine designs, operating conditions, electronic control features, and diagnostic limits have created challenges to historical-based testing approaches. A physics-based methodology, known as Load Matrix, is described to counteract these challenges. The technique, developed by AVL, is based on damage factor models for subsystem and component failure modes (e.g. fatigue, wear, degradation, deposits) and knowledge of customer duty cycles. By correlating dyno test to field conditions in quantifiable terms, such as customer equivalent miles, more effective and efficient durability test suites and test procedures can be utilized. To this end, application of Load Matrix to a heavy-duty diesel engine is presented.

Over the past few years, the fuel mass measurement gained in importance to record the consumed fuel mass and the specific fuel consumption [g/kWh] with high accuracy. Measuring instruments, such as positive displacement meters, methods based on the burette or the Wheatstone bridge mass flow meter measure either the volumetric flow and a temperature-dependant fuel density correction is necessary or they have old technology and therefore poor accuracy and repeatability. A new-generation Coriolis sensor featuring an ideal measurement range for engine test beds but still with flow depending pressure drop has been integrated in a fuel meter to ensure that no influence is given to the engine behaviour for example after engine load change. The new Coriolis meter offers better accuracy and repeatability, gas bubble venting and easy test bed integration. For returnless fuel injection systems the fuel system supplies the fuel pressure.

There is a concern that the continuing trend on miniaturization (Moore's law) in IC design and fabrication might have a negative impact on the device reliability. To understand and to possibly quantify the physics underlying this concern and phenomenon, it is natural to proceed from the experimental bathtub curve (BTC) - reliability “passport” of the device. This curve reflects the combined effect of two major irreversible governing processes: statistics-related mass-production process that results in a decreasing failure rate with time, and reliability-physics-related degradation (aging) process that leads to an increasing failure rate. It is the latter process that is of major concern of a device designer and manufacturer. The statistical process can be evaluated theoretically, using a rather simple predictive model.

Validation of powertrain systems is nowadays performed with specific durability relevant load cycles, which represent the lifetime requirement of individual powertrain components. The definition of such durability relevant load cycles, which are used for vehicle testing should ideally be based on the actual vehicle's usage. Recording driving cycles within a vehicle is one of the most typical ways of collecting vehicle usage and relevant end customer behavior, but the generation of such measured vehicle data can be time consuming. In addition, this method of capturing on-road measurements has limitations in the variation of vehicle loadings (e.g., number of passengers, luggage, trailer usage etc.). Especially for new applications, entering new target markets, these kinds of in-vehicle measurements are not possible in early development stages, as the required vehicle or powertrain configuration is not available in hardware or incapable of measurements.