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Overall cycle time and prototype testing are significantly decreased by assessment of cooling module performance in the design stage itself. Hence, Front End Cooling and Thermal Management are essential components of the vehicle design process. Performance of the cooling module depends upon a variety of factors like frontal opening, air flow, under-hood sub-systems, module positioning, front grill design, fan operation. Effects of design modifications on the engine cooling performance are quantified by utilizing computational fluid dynamics (CFD) tool FluentTM. Vehicle frontal configuration is captured in the FE model considering cabin, cargo and underbody components. Heat Exchanger module is modelled as a porous medium to simulate the fluid flow. Performance data for the Heat Exchanger module is generated using the 1D KuliTM software. In this paper, CFD simulation of Front End Cooling is performed for maximum torque and maximum power operating conditions.

To increase the comfort level of a vehicle cabin, vehicles today are equipped with rear cooling unit in addition to the primary heating ventilation and air conditioning (HVAC) system that supplies conditioned air into the cabin through the instrument panel (IP) duct and console or foot duct. Ducting for the rear unit is generally provided through C or D pillar and the roof of the vehicle. Owing to packaging and styling constraints, flow induced noise in roof duct has become a key parameter in design and development of the rear cooling unit. This paper, broadly discusses: Two Broadband Noise Source (BNS) Models namely (i) Proudman’s model for quadrupole source and (ii) Curle’s boundary layer model for dipole source and Ffowcs-Williams & Hawkings (FW-H) model for noise level information at receiver location.

Predicting the thermal comfort of the passenger compartment or the vehicle cabin using computational fluid dynamics (CFD) analysis helps reduce the cost and time of a heating ventilation and air-conditioning (HVAC) system development in any new vehicle program. This paper presents the simulation results of cabin soaking and cooling analysis done on an actual sports utility vehicle (SUV) prototype under constant solar load using the commercial CFD package Fluent™. These results are compared with test results. Cabin cooling and soaking analysis for a closed loop system that would include the HVAC system, the IP duct and the cabin with the air-conditioner (AC) operating in the recirculation mode is simulated. The heat rejected in the evaporator is assumed to be constant and this closed loop system analysis eliminates the need to be dependent on test results for input conditions like air flow rate and air temperature at duct inlet ports.

This paper broadly describes two computational fluid dynamics (CFD) analysis methods to predict the de-icing phenomenon over the vehicle windshield and front side windows. 1 Solid Modeling Method: In this method, the windshield and window glasses are modeled as solid and 2 Shell Modeling Method: Here, windshield and side window glasses are modeled as shell elements and considered as wall with defined thickness as input condition to capture the correct heat transfer effect due to the conduction and convection from warm air to ice layer. The CFD analyses by both methods are done in two key-steps: a) First, steady state velocity distributions for several different defroster flow rates are calculated; b) Secondly, based on the pre calculated velocity fields, the defogging time is estimated. The solidification and melting model is used to simulate the ice melting process over the glasses available with commercial CFD software Fluent.

Assessment of cooling performance in the design stage of vehicle allows a reduction in the number of needed prototypes and reduces the overall design cycle time. Frontend cooling and thermal management play an essential role in the early stages of commercial vehicle design. Sufficient airflow needs to be available for adequate cooling of the under-hood components. The amount of air mass flow depends on the under-hood geometry details, positioning and size of the grilles, fan operation and the positioning of the other components. Thermal performance depends on the selection of heat exchanger. This paper describes the effects of several design actions on engine cooling performance of a commercial vehicle with the help of Computational Fluid Dynamics (CFD) simulation tool Fluent™. Front of vehicle design is captured in detailed FE model, considering front bumper, grille, cabin, cargo and surrounding under-hood and underbody components.

A Coupled CFD - FE Analysis, referred as Conjugate Heat Transfer (CHT) Analysis or Fluid Structure Interaction (FSI), is very important for the processes that involves simultaneous energy exchange between solid and fluid domains. If we consider IC engines, Exhaust Manifold is one of the critical areas where above mentioned phenomenon takes place. In this paper, temperature distribution in solid parts of exhaust manifold is obtained through Computational Fluid Dynamics (CFD) analysis which uses Finite Volume Method (FVM) for solving Navier-stokes equation and energy equation. Whereas thermal stresses are predicted through FE analysis which is based on Finite Element Methods (FEM). It is obvious to validate CFD process before evaluating thermal stress. Therefore initially CFD results are compared with experimental results and found more than 88% correlation. Thereafter in FE analysis, temperature field from CFD is mapped to nodes of FE model and thermo-mechanical stresses are evaluated.

Investigation of fluid flow for three different modes of operation of an automotive heating ventilation and air conditioning (HVAC) system is carried out in the present work. The modes considered are: face mode, defroster mode and foot mode. The performance of the HVAC system is judged by parameters like air discharge rate at cabin level, pressure drop through the system, uniformity of the air flow at the outlet faces and distribution between different duct outlets. All these parameters are predicted by Computational Fluid Dynamics (CFD) analysis. Multiple reference frame (MRF) model is used to simulate the steady state flow through the rotating blower. Porous medium model is used to simulate the flow through the evaporator and heater. The standard k-▪ model is used to consider the turbulent effect of air flow.