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Front end cooling module which consists of condenser, intercooler, radiator and fan is an important part of vehicle design as it affects radiator thermal performance. The current study describes a CFD based method to predict air-to-boil (ATB) temperature of a sport utility vehicle radiator. The predicted ATB values were compared with experimental data obtained from outdoor cooling trials. The predicted and the experimental values agreed to within 3-5 °C for operating conditions ranging from low gear-low speed condition to high gear-high speed conditions. It is anticipated that such analyses will lead to reduction of design cycle time and prototyping costs.

Braking performance of a vehicle is affected by the temperature rise in the wheel end components. In this study, the brake cooling performance of drum brake assembly for a heavy truck has been simulated using a three-dimensional time-transient CFD model. The predicted brake drum temperatures were compared with the indoor dynamometer test results. The agreement between the predictions and the test data was within 8°C for the braking cycle analyzed. The validated model was used to asses the effect of air flow angle of attack on the brake drum and rim temperatures.

Passenger comfort and safety are major drivers in a typical automotive design and optimization cycle. Addressing thermal comfort requirements and the thermal management of the passenger cabin within a car, which involves accurate prediction of the temperature of the cabin interior space and the various aggregates that are present in a cabin, has become an area of active research. Traditionally, these have been done using experiments or detailed three-dimensional Computational Fluid Dynamics (CFD) analysis, which are both expensive and time-consuming. To alleviate this, recent approaches have been to use one-dimensional system-level simulation techniques with a goal to shorten the design cycle time and reduce costs. This paper describes the use of Modelica language to develop a one-dimensional mathematical model using Modelica language for automotive cabin thermal assessment when the car is subjected to solar heat loading.

Increasing demands on engine power to meet increased load carrying capacity and adherence to emission norms have necessitated the need to improve thermal management system of the vehicle. The efficiency of the vehicle cooling system strongly depends on the fan and fan-shroud design and, designing an optimum fan and fan-shroud has been a challenge for the designer. Computational Fluid Dynamics (CFD) techniques are being increasingly used to perform virtual tests to predict and optimize the performance of fan and fan-shroud assembly. However, these CFD based optimization are mostly based on a single performance parameter. In addition, the sequential choice of input parameters in such optimization exercise leads to a large number of CFD simulations that are required to optimize the performance over the complete range of design and operating envelope. As a result, the optimization is carried out over a limited range of design and operating envelope only.