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This course is verified by Probitas Authentication as meeting the AS9104/3A requirements for continuing Professional Development. In the Aerospace Industry there is a focus on Defect Prevention to ensure that quality goals are met. Failure Mode and Effects Analysis (PFMEA) and Control Plan activities are recognized as being one of the most effective, on the journey to Zero Defects. This two-day course is designed to explain the core tools of Design Failure Mode and Effects Analysis (DFMEA), Process Flow Diagrams, Process Failure Mode and Effects Analysis (PFMEA) and Control Plans as described in AS13100 and RM13004.

On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.

In electrified vehicles, auxiliary units can be a dominant source of noise, one of which is the re-frigerant scroll compressor. Compared to vehicles with combustion engines, e-vehicles require larger refrigerant compressors, as in addition to the interior, also the battery and the electric motors have to be cooled. Currently, scroll compressors are widely used in the automotive industry, which generate one pressure pulse per revolution due to their discontinuous compression principle. This results in speed-dependent pressure fluctuations as well as higher-harmonic pulsations that arise from reflections. These fluctuations spread through the refrigeration circuit and cause the vibration excitation of refrigerant lines and heat exchangers. The sound transmission path in the air con-ditioning heat exchanger integrated in the dashboard is particularly critical. Various silencer con-figurations can be used to dampen these pulsations.

Autonomous driving is a hot topic in the automotive domain, and there is an increasing need to prove its reliability. They use machine learning techniques, which are themselves stochastic techniques based on some kind of statistical inference. The occurrence of incorrect decisions is part of this approach and often not directly related to correctable errors. The quality of the systems is indicated by statistical key figures such as accuracy and precision. Numerous driving tests and simulations in simulators are extensively used to provide evidence. However, the basis of all descriptive statistics is a random selection from a probability space. The difficulty in testing or constructing the training and test data set is that this probability space is usually not well defined. To systematically address this shortcoming, ontologies have been and are being developed to capture the various concepts and properties of the operational design domain.

Increasingly stringent regulations relating to the emissions of passenger cars and commercial vehicles demand alternative powertrain technologies in order to effectively achieve the climate targets. Hydrogen can play a crucial role as alternative energy carrier regarding the EU targets for CO2-neutral mobility towards 2050. Therefore, it represents a reasonable choice not only for fuel cell powered vehicles, but also for fueling internal combustion engines (ICE). This paper focuses on the numerical investigation of high-pressure hydrogen injection and the mixture formation inside a high-tumble ICE with a conventional liquid fuel injector for passenger cars. Since the traditional 3D-CFD approach of simulating the inner flow of an injector requires a very high spatial and temporal resolution, the enormous computational effort, especially for full engine simulations, is a big challenge for an effective virtual development of modern ICEs.

Opposed-piston two-stroke engines offer numerous advantages over conventional four-stroke engines, both in terms of fundamental principles and technical aspects. The reduced heat losses and large volume-to-surface area ratio inherently result in a high thermodynamic efficiency. Additionally, the mechanical design is simpler and requires fewer components compared to conventional four-stroke engines. When combining this engine concept with alternative fuels such as hydrogen and pre-chamber technology, a potential route for carbon-neutral powertrains is observed. To ensure safe engine operation using hydrogen as fuel, it is crucial to consider strict safety measures to prevent issues such as knock, pre-ignition, and backfiring. One potential solution to these challenges is the use of direct injection, which has the potential to improve engine efficiency and expand the range of load operation.

When using "green" hydrogen, fuel cell technology plays a key role in emission-free mobility. A powertrain based on fuel cells (FC) shows its advantages over battery-electric powertrains when the requirement profile primarily demands high performance over a longer period of time, high flexible availability and short refueling times. In addition, FC achieves higher effi-ciencies than the combustion of hydrogen in a gas engine, meaning that the chemical energy is used more efficiently than with established combustion engines. When using FC technology, numerous companies in Baden-Württemberg can contribute their specific expertise from the traditional automotive construction and supplier business. This includes auxiliary units in the air (cathode) and hydrogen (anode) path, such as the air com-pressor, the H2 recycling pump, humidifier, cooling system, power electronics, valve and pressure tank technology as well as components of the fuel cell stack itself.

With the automotive industry's increasing focus on electromobility and the growing share of electric cars, new challenges are arising for the development of electric motors. The requirements for torque and power of traction motors are constantly growing, while installation space, costs and weight are increasingly becoming limiting factors. Moreover, there is an inherent conflict in the design between power density and efficiency of an electric motor. Thus, a main focus in today's development lies on space-saving and yet effective and innovative cooling systems. This paper presents an approach for a multi-physical optimization that combines the domains of electromagnetics and thermodynamics. Based on a reference machine, this simulative study examins a total of nine different stator cooling concepts varying the cooling duct positions and end-winding cooling concepts.

Due to its physical and chemical properties, hydrogen is an attractive fuel for internal combustion engines, providing grounds for studies on hydrogen engines. It is common practice to use a mathematical model for basic engine design and an essential part of this is the simulation of the combustion cycle, which is the subject of the work presented here. One of the most widely used models for describing combustion in gasoline and diesel engines is the Wiebe model. However, for cases of hydrogen combustion in DI engines, which are characterized by mixture stratification and in some cases significant incomplete combustion, practically no data can be found in the literature on the application of the Wiebe model. Based on Wiebe's formulas, a mathematical model of hydrogen combustion has been developed. The model allows making computations for both DI and PFI hydrogen engines. The parameters of the Wiebe model were assessed for three different engines in a total of 26 operating modes.