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Quantification of heat exchanger performance in its operative environment is in many engineering applications an essential task, and the air flow rate through the heat exchanger core is an important optimizing parameter. This paper explores an alternative method for quantifying the air flow rate through compact heat exchangers positioned in the underhood of a passenger car. Unlike conventional methods, typically relying on measurements of direct flow characteristics at discrete probe locations, the proposed method is based on the use of load-cells for direct measurement of the total force acting on the heat exchanger. The air flow rate is then calculated from the force measurement. A direct comparison with a conventional pressure based method is presented as both methods are applied on a passenger car’s radiator tested in a full scale wind tunnel using six different grill configurations. The measured air flow rates are presented and discussed over a wide range of test velocities.

Presented are results from numerical investigations of buoyancy driven flow in a simplified representation of an engine bay. A main motivation for this study is the necessity for a valid correlation of results from numerical methods and procedures with physical measurements in order to evaluate the accuracy and feasibility of the available numerical tools for prediction of natural convection. This analysis is based on previously performed PIV and temperature measurements in a controlled physical setup, which reproduced thermal soak conditions in the engine compartment as they occur for a vehicle parked in a quiescent ambient after sustaining high thermal loads. Thermal soak is an important phenomenon in the engine bay primarily driven by natural convection and radiation after there had been a high power demand on the engine. With the cooling fan turned off and in quiescent environment, buoyancy driven convection and radiation are the dominating modes of heat transfer.

This paper presents pressure drops and heat transfer rates for compact heat exchangers, where the heat exchangers are angled 90°, 60°, 30° and 10° relative to the incoming airflow. The investigation is based on three heat exchangers with thicknesses of 19mm and 52mm. Each heat exchanger was mounted in a duct, where it was tested for thermal and isothermal conditions. The inlet temperature of the coolant was defined to two temperatures; ambient temperature and 90°C. For the ambient cases the coolant had the same temperature as the surrounding air, these tests were performed for five airflow rates. When the coolant had a temperature of 90°C a combination of five coolant flow rates and five airflow rates were tested. The test set-up was defined as having a constant cross-section area for 90°, 60° and 30° angles, resulting in a larger core area and a lower airspeed through the core, for a more inclined heat exchanger.

Computational Fluid Dynamics (CFD) is today an important tool in the design process of fuel and energy efficient vehicles. Under-hood management is one of the fields where CFD has proven itself to be useful for cost-efficient development of products. Multiple Reference Frame (MRF) method is the most common used tool in the industry for modeling rotating parts. In previous papers, the modeling strategy with MRF has been documented for open fans and showed high capability to predict fan performance. One of the open points of this proposed method has been its applicability to closed fans (ring fans), as industry experience and discussions has indicated previous conclusions of open fans and MRF modeling may not apply across ranges of fan designs. This paper investigates the MRF method for a closed fan with U-shroud and analyzes several aspect of the modeling strategy.

Battery Electric Vehicles and Extended Range Electric Vehicles, like the Chevrolet Volt, can use electrical energy from the Grid to meet the majority of a driver�s transportation needs. This has the positive societal effects of displace petroleum consumption and associated pollutants from combustion on a well to wheels basis, as well as reduced energy costs for the driver. CO2 may also be lower, but this depends upon the nature of the grid energy generation. There is a mix of sources � coal-fired, gas -fired, nuclear or renewables, like hydro, solar, wind or biomass for grid electrical energy. This mix changes by region, and also on the weather and time of day. By monitoring the grid mix and communicating it to drivers (or to their vehicles) in real-time, electrically driven vehicles may be recharged to take advantage of the lowest CO2, and potentially lower cost charging opportunities.

Today CFD is an important tool for engineers in the automotive industry who model and simulate fluid flow. For the complex field of Underhood Thermal Management, CFD has become a very important tool to engineer the cooling airflow process in the engine bay of vehicles. To model the cooling airflow process accurately in CFD, it is of utmost importance to model all components in the cooling airflow path accurately. These components are the heat exchangers, fan and engine bay blockage effect. This paper presents CFD simulations together with correlating measurements of a cooling airflow system placed in a test rig. The system contains a heavy duty truck louvered fin radiator core, fan shroud, fan ring and fan. Behind the cooling module and fan, a 1D engine silhouette is placed to mimic the blockage done by a truck engine. Furthermore, a simple hood is mounted over the module to mimic the guiding of air done by the hood shape in an engine bay.

Underhood Thermal Management has become an important topic for the majority of automotive OEM's. To keep combustion engines cool and manage waste heat efficiently is an important part in the design of vehicles with low fuel consumption. To be able to predict cooling performance and underhood airflow with good precision within a virtual design process, it is of utmost importance to model and simulate the cooling fan efficiently and accurately, and this has turned out to be challenging. Simulating the cooling fan in a vehicle installation involves capturing complex fluid dynamic interaction between rotating blades and stationary objects in the vicinity of the fan. This interaction is a function of fan rotation rate, fan blade profile, upstream and downstream installation components. The flow is usually highly turbulent and small geometry details, like the distance between the blade tip and the fan shroud, have strong impact on the fan performance characteristics.

The most common fan model to use in commercial CFD software today is the Multiple Reference Frame (MRF) model. This is at least valid for automotive under hood applications. Within the industry, for this typical application, this model is commonly known to under predict performance. This under prediction has been documented by the authors' of this paper in SAE paper 2009-01-0178 and VTMS paper 2009-01-3067. Furthermore has this been documented by S.Moreau from Valeo in “Numerical and Experimental Investigation of Rotor-Stator Interaction in Automotive Engine Cooling Fan Systems”, ETC, 7th European Conference on Turbomachinery, 2007. In preceding papers a specific methodology of use has been documented and it has been shown that the MRF model under predicts performance for the airflow in a cooling system commonly with 14% in volumetric flow rate. This is for a system dominated by inertial effects.

A common fan model to use in automotive under hood simulations is the Multiple Reference Frame (MRF) model and within the industry, for this specific application, this model is well known to under predict performance. In this paper we have examined the possibilities of correcting this deficiency with a simple “speed correction”. This is done by testing and simulating a production fan in the Volvo Fan Test Rig for two operating speeds, 1200 rpm and 2400 rpm. Pressure rise, fan power and static efficiency are presented as functions of volumetric flow rate. The simulations verify that using the MRF model the common behavior of under predicting pressure rise and performance of the fan occur. In addition, this work shows that; although the MRF is not predicting fan performance correctly it constitutes a reliable fan modeling strategy.