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Within the pre-development phase of a vehicle validation process, the role of computational simulation is becoming increasingly prominent in efforts to ensure thermal safety. This gain in popularity has resulted from the cost and time advantages that simulation has compared to experimental testing. Additionally many of these early concepts cannot be validated through experimental means due to the lack of hardware, and must be evaluated via numerical methods. The Race Track Simulation (RTS) can be considered as the final frontier for vehicle thermal management techniques, and to date no coherent method has been published which provides an efficient means of numerically modeling the temperature behavior of components without the dependency on statistical experimental data.

Modern exhaust systems contain not only a piping network to transport hot gas from the engine to the atmosphere, but also functional components such as the catalytic converter and turbocharger. The turbocharger is common place in the automotive industry due to their capability to increase the specific power output of reciprocating engines. As the exhaust system is a main heat source for the under body of the vehicle and the turbocharger is located within the engine bay, it is imperative that accurate surface temperatures are achieved. A study by K. Haehndel [1] implemented a 1D fluid stream as a replacement to solving 3D fluid dynamics of the internal exhaust flow. To incorporate the 3D effects of internal fluid flow, augmented Nusselt correlations were used to produce heat transfer coefficients. It was found that the developed correlations for the exhaust system did not adequately represent the heat transfer of the turbocharger.

The thermal prediction of a vehicle under-body environment is of high importance in the design, optimization and management of vehicle power systems. Within the pre-development phase of a vehicle's production process, it is important to understand and determine regions of high thermally induced stress within critical under-body components. Therefore allowing engineers to modify the design or alter component material characteristics before the manufacture of hardware. As the exhaust system is one of the primary heat sources in a vehicle's under-body environment, it is vital to predict the thermal fluctuation of surface temperatures along corresponding exhaust components in order to achieve the correct thermal representation of the overall under-body heat transfer. This paper explores a new method for achieving higher accuracy exhaust surface temperature predictions.

Noise and vibration have an important influence on a customer's perception of vehicle quality and cabin interior noise levels are a key criteria. The interior sound levels of automobiles have been significantly reduced over the years, with reductions in power train, tire and external wind noise. One of the highest in-cabin noise levels now arises from heating, ventilating and air conditioning systems, generated by the air-rush noise at various HVAC settings. Thus quieter climate control systems are desired by car manufacturers. A systematic benchmarking study was performed to investigate the in-cabin noise of vehicles. 21 passenger cars including compact, mid-size, full-size, and a truck were selected. Tests were conducted on relatively new production vehicles in various conditions. A binaural head system was used in front passenger seat to measure noise levels. The methodology used and the experimental results were presented in this paper.

Kinetic energy recovery systems (KERS) placed on one axle coupled to a traditional thermal engine on the other axle is possibly the best solution presently available to dramatically improve the fuel economy while providing better performances within strict budget constraints. Different KERS may be built purely electric, purely mechanic, or hybrid mechanic/electric differing for round trip efficiency, packaging, weights, costs and requirement of further research and development. The paper presents an experimental analysis of the energy flow to and from the battery of a latest Nissan Leaf covering the Urban Dynamometer Driving Schedule (UDDS). This analysis provides a state-of-the-art benchmark of the propulsion and regenerative braking efficiencies of electric vehicles with off-the-shelve technologies.

A unified approach to cooperative and non-cooperative Detect-and-Avoid (DAA) is a key enabler for Remotely Piloted Aircraft System (RPAS) to safely and routinely access all classes of airspace. In this paper state-of-the-art cooperative and non-cooperative DAA sensor/system technologies for manned aircraft and RPAS are reviewed and the associated multi-sensor data fusion techniques are discussed. A DAA system architecture is presented based on Boolean Decision Logics (BDL) for selecting non-cooperative and cooperative sensors/systems including both passive and active Forward Looking Sensors (FLS), Traffic Collision Avoidance System (TCAS) and Automatic Dependent Surveillance - Broadcast (ADS-B). After elaborating the DAA system processes, the key mathematical models associated with both non-cooperative and cooperative DAA functions are presented.

The implementation of Synthetic Jet Actuators (SJAs) on Unmanned Aerial Vehicles (UAVs) provides a safe test-bed for analysis of improved performance, in the hope of certification of this technology on commercial aircraft in the future. The use of high resolution numerical methods (i.e. CFD) to capture the details of the effects of SJAs on flows and on the hosting lifting surface are computationally expensive and time-consuming, which renders them ineffective for use in real-time flow control implementations. Suitable alternatives include the use of Reduced Order Models (ROMs) to capture the lower resolution overall effects of the jets on the flow and the hosting structure. This research paper analyses the effects of SJAs on aircraft wings using a ROM for the purpose of determining the unsteady aerodynamic forces modified by the presence of the SJAs. The model developed is a 3D unsteady panel code where the jets are represented by source panels.

Characterizing the acoustic properties of sound-absorbing materials is costly and time consuming. The acoustic material database helps the automotive designers design their interior trims in accordance with target level for interior noise. In this paper, a two-microphone impedance tube was used to measure the normal sound absorption coefficient. The main parameters that are used in the theoretical model for interior noise level assessment are investigated. These parameters include thickness, airflow resistivity, porosity, tortuosity, viscous and thermal characteristics length. The measured results have been validated by the theoretical models. The validation of normal sound absorption coefficient was found to be in agreement with its corresponding measurement data. Finally, the sensitivity of the sound absorption coefficient which is related to the physical properties mentioned above is further analyzed.

As computational methodologies become more integrated into industrial vehicle pre-development processes the potential for high transient vehicle thermal simulations is evident. This can also been seen in conjunction with the strong rise in computing power, which ultimately has supported many automotive manufactures in attempting non-steady simulation conditions. The following investigation aims at exploring an efficient means of utilizing the new rise in computing resources by resolving high time-dependent boundary conditions through a series of averaging methodologies. Through understanding the sensitivities associated with dynamic component temperature changes, optimised boundary conditions can be implemented to dampen irrelevant input frequencies whilst maintaining thermally critical velocity gradients.

At the rear of the vehicle an end acoustic silencer is attached to the exhaust system. This is primarily to reduce noise emissions for the benefit of passengers and bystanders. Due to the location of the end acoustic silencer conventional thermal protection methods (heat shields) through experimental means can not only be difficult to incorporate but also can be an inefficient and costly experience. Hence simulation methods may improve the development process by introducing methods of optimization in early phase vehicle design. A previous publication (Part 1) described a methodology of improving the surface temperatures prediction of general exhaust configurations. It was found in this initial study that simulation results for silencer configurations exhibited significant discrepancies in comparison to experimental data.

Traditional User/Maintenance Manuals provide useful information when dealing with simple machines. However, when dealing with complex systems of systems and highly miniaturized technologies, like UAVs, or with machines with millions of parts, a commercial aircraft is a case in point, new technologies taking advantage of Augmented Reality can rapidly and effectively support the maintenance operations. This paper presents a User/Maintenance Manual based on Augmented Reality to help the operator in the detection of parts and in the sequence to be followed to assemble/disassemble systems and subsystems. The proposed system includes a handheld device and/or an head mounted display or special goggles, to be used by on-site operators, with software management providing data fusion and overlaying traditional 2D user/maintenance manual information with an augmented reality software and appropriate interface.