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This basic course introduces the intent of the DO-254 standard for commercial avionics hardware development. The content will cover many aspects of avionic hardware including, aircraft safety, systems, hardware planning, requirements, design, implementation, and testing. Participants will learn industry-best practices for real-world hardware development, common DO-254 mistakes and how to prevent them, and how to minimize risks and costs while maximizing hardware quality.

This course is offered in China only and presented in Mandarin Chinese. The course materials are bilingual (English and Chinese). Participants in this course comprehensive understanding of the DO-254 standard including how the development of airborne electronic hardware (AEH) and the development of the aircraft system are related. It addresses the key objectives, activities, and generated data of the AEH lifecycle and presents common problems in the application of DO-254 and how to prevent them. This course also includes current AEH certification requirements and interprets some of the difficulties in gaining compliance approval.

This course will introduce participants to industry best practices for real-world aviation cyber-security risk-assessment, development & assurance. Participants will learn the information necessary to help minimize DO-326/ED-202-set compliance risks and costs, while also optimizing cyber-security levels for the development, deployment and in-service phases Topics such as aircraft security aspects of safety, systems-approach to security, security planning, the airworthiness security process, and security effectiveness assurance will be covered.

The ever-increasing networking and automation of vehicles make cybersecurity a core requirement for future vehicles and their components. Automobile manufacturers and suppliers are confronted with new requirements that address the cybersecurity of vehicle IT/OT. This certification, created in partnership between SAE International and TÜV SÜD, provides the necessary basic knowledge for people who work in the field of automotive cybersecurity, management, engineering, and auditing. Course participants will gain an understanding of the current challenges in the automotive industry and the relevance and importance of cybersecurity.

Homologation is an important process in vehicle development and aerodynamics a main data contributor. The process is heavily interconnected: Production planning defines the available assemblies. Construction defines their parts and features. Sales defines the assemblies offered in different markets, where Legislation defines the rules applicable to homologation. Control engineers define the behavior of active, aerodynamically relevant components. Wind tunnels are the main test tool for the homologation, accompanied by surface-area measurement systems. Mechanics support these test operations. The prototype management provides test vehicles, while parts come from various production and prototyping sources and are stored and commissioned by logistics. Several phases of this complex process share the same context: Production timelines for assemblies and parts for each chassis-engine package define which drag coefficients or drag coefficient contributions shall be determined.

The cost of this introductory course can be applied to the cost of the full courses: C2301, ARP4754B Guidelines for Development of Civil Aircraft and Systems C2302, ARP4761A Guidelines and Methods of Performing the Safety Assessment for Certification of Civil Aircraft This short course is a high-level introduction to the revised SAE standard ARP4761A and its application of the guidelines of practice for aircraft and systems safety assessment.

The cost of this introductory course can be applied to the cost of the full courses: C2301, ARP4754B Guidelines for Development of Civil Aircraft and Systems C2302, ARP4761A Guidelines and Methods of Performing the Safety Assessment for Certification of Civil Aircraft This short course is a high-level introduction to the revised SAE standard ARP4754B and its guidelines of practice for aircraft and systems development.

The modern automotive industry is facing challenges of ever-increasing complexity in the electrified powertrain era. On-board diagnostic (OBD) systems must be thoroughly validated and calibrated through many iterations to function effectively and meet the regulation standards. Their development and design process are more complex when prototype hardware is not available and therefore virtual testing is a prominent solution, including Software-in-the-loop (SiL) and Hardware-in-the-loop (HIL) simulations. Virtual prototype testing relying on real-time simulation models is necessary to design and test new era’s OBD systems quickly and in scale. The new fuel cell powertrain involves new and preciously unexplored fail modes. To make the system robust, simulations are required to be carried out to identify different fails.

The transition from ICE to electric power trains in new vehicles along with the application of advanced active and passive noise reduction solutions has intensified the perception of noise sources not directly linked to the propulsion system. This includes road noise as amplified by the tire cavity resonance. This resonance mainly depends on tire geometry, air temperature inside the tire and vehicle speed and is increasingly audible for larger wheels and heavier vehicles, as they are typical for current electrical SUV designs. Active technologies can be applied to significantly reduce narrow band tire cavity noise with low costs and minimal weight increase. Like ANC systems for ICE powertrains, they make use of the audio system in the vehicle. In this paper, a novel low-cost system for road induced tire cavity noise control (RTNC) is presented that reduces the tire cavity resonance noise inside a car cabin.

The engine acoustic character has always represented the product DNA, owing to its strong correlation with in-cylinder pressure gradient, components design and perceived quality. Best practice for engine acoustic characterization requires the employment of a hemi-anechoic chamber, a significant number of sensors and special acoustic insulation for engine ancillaries and transmission. This process is highly demanding in terms of cost and time due to multiple engine working points to be tested and consequent data post-processing. Since Neural Networks potentially predicting capabilities are apparently un-exploited in this research field, the following paper provides a tool able to acoustically estimate engine performance, processing system inputs (e.g. Injected Fuel, Rail Pressure) thanks to the employment of Multi Layer Perceptron (MLP, a feed forward Network working in stationary points).

Broadband active noise control algorithms require high-performance so multi-channel control to ensure high performance, which results in very high computational power and expensive DSP. When the control filter update part need a huge computational power of the algorithm is separated and calculated by the server, it is possible to reduce cost by using a low-cost DSP in a local vehicle, and a performance improvement algorithm requiring a high computational power can be applied to the server. In order to achieve the above goal, this study analyzed the maximum delay time when communication speed is low and studied response measures to ensure data integrity at the receiving location considering situations where communication speed delay and data errors occur.

When travelling in an open-jet wind tunnel, the path of an acoustic wave is affected by the flow causing a shift of source positions in acoustical maps of phased arrays outside the flow. The well-known approach of Amiet attempts to correct for this effect by computing travel times between microphones and map points based on the assumption that the boundary layer of the flow, the so-called shear-layer, is infinitely thin and refracts the acoustical ray in a conceptually analogy to optics. However, in reality, the turbulent nature of both the not-so thin shear-layer and the acoustic emission process itself causes an additional smearing of sources in acoustic maps, which in turn causes deconvolution methods based on these maps - the most prominent example being CLEAN-SC - to produce certain ring effects, so-called halos, around sources.