A Methodology to Optimize Fan Duty Cycle (FDC) by Deploying 1D CAE Simulation Tool Tata Motors Passenger Vehicles Limited

Format:

Book

Conference/Event

Author/Creator:

Jaybhay, Sambhaji, author.

Contributor:

Kapoor, Sangeet

Kulkarni, Shridhar Diliprao

Varma, Mohit

Conference Name:

SAENIS TTTMS Thermal Management Systems Conference-2022 (2022-11-16 : Rajasthan, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

Vehicle thermal management system (VTMS) is a means of monitoring and controlling temperatures of vehicular components and aggregates to within optimum limits, thereby ensuring the proper functioning of the component or aggregate in an automobile. An integrated approach is required for developing VTMS, to satisfy the complex requirements of performance, reliability, fuel economy and human thermal comfort in modern vehicles. Fan motors and blowers play a crucial role in vehicle thermal management. These fan motors/ blower systems need to be designed in a manner such that there is minimum parasitic load on the prime mover.This work comprises performing Transient Powertrain Cooling (T-PTC) and Transient Air-conditioning (T-AC) simulation on a vehicle for prediction of parameters affecting fan operation of Condenser Radiator Fan Module (CRFM) during simulated city drive cycles. T-PTC model is built with addition of engine point mass, thermostat and heat conduction components to an existing steady state model. Dynamic solver is used to simultaneously solve for advection, convection and conduction within the fluid. T-AC model is built with a simple cabin model which helps to predict the average cabin temperature and average vent temperature along with the AC refrigerant discharge and suction pressures. T-PTC and T-AC models are integrated with fan logic sub-system and simulation is performed using 1-Dimensional Computer Aided Engineering (1D CAE) tool. Correlation of >96% accuracy is achieved with the physical test data for Fan Duty Cycle (FDC). Further, to check robustness of the 1D CAE model, FDC is predicted for the same vehicle program with a different CRFM. In this case, it is observed that, the predicted result correlates well with the physical test data with >96% accuracy.In this work, a robust simulation methodology is demonstrated, which can reduce cost and time in intensive physical test iterations and enable validation of different fan strategies for optimizing FDC in the early stages of vehicle development

Notes:

Vendor supplied data

Publisher Number:

2022-28-0440

Access Restriction:

Restricted for use by site license