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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.

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.

The paper considers a novel waste heat recovery (WHR) system integrated with the engine architecture in a hybrid electric vehicle (HEV) platform. The novel WHR system uses water as the working media and recovers both the internal combustion engine coolant and exhaust energy in a single loop. Results of preliminary simulations show a 6% better fuel economy over the cold start UDDS cycle only considering the better fuel usage with the WHR after the quicker warm-up but neglecting the reduced friction losses for the warmer temperatures over the full cycle.

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.

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.

A pressure-based technique has been developed for the purpose of radiator cooling airflow measurement. The technique was effectively utilised to quantify the local time-averaged air velocity through radiator cores in a small wind tunnel. The pressure difference indicated by the technique was found to be a function of the normal component of the air velocity. This paper describes the development and use of the technique which is compact, robust and non-intrusive. By applying this technique, the airflow distribution across the radiator face has been measured for a complete vehicle in an aerodynamic wind tunnel and in an environmental chamber. Results are compared for the different test environments. The influence of airflow distribution on the Specific Dissipation (a parameter used for evaluating radiator cooling performance) is examined and results for propeller-based methods and pressure-based methods are compared.

In this paper, a theoretical model for the calculation of Specific Dissipation (SD) was developed. Based on the model, the effect of ambient and coolant radiator inlet temperatures on SD has been predicted. Results indicate that the effect of ambient and coolant inlet temperature variation on SD is small (less than 2%) when ambient temperature varies between 10 and 50°C and coolant radiator inlet temperature between 60 and 120°C. The effect of coolant flowrate on SD is larger if there is a larger flowrate variation. Experimental results indicate that a 1 % variation at 1.0 L/s will cause about ±0.6% SD variation. Therefore the flowrate should be carefully controlled.