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Technical Paper

Deployment of 1D Simulation with Multi Air Zone Cabin Model for Air Conditioning System Development for Passenger Car

2015-01-14
2015-26-0234
This paper presents a method for Mobile Air Conditioning cool down simulation of passenger car with Multi Air Zone Cabin Model. This approach allows the prediction of zone wise (head, body and foot) temperature and humidity distribution in the cabin for parameter studies for transient analysis. The complete simulation model is set up in the 1D code. The same cabin model can deal with multiple inlets into the cabin, solar radiation, and other loads on Air Conditioning (AC) system and also allows detailed definition of cabin walls, like doors, floor, roof and windows. 3D air flow pattern within the cabin has been captured by diffusion fields and mass flow field. For a given flow field, these data are generated by conducting cabin air flow analysis in 3D Computational Fluid Dynamics (CFD). The simulation was done along with AC system, consisting of evaporator, compressor, condenser, thermostatic expansion device and connecting pipe network.
Technical Paper

Deployment of 1D Simulation for Engine Cooling Performance and its Correlations with Vehicle Level Testing

2015-01-14
2015-26-0216
Upfront in a vehicle program, sizing of front end cooling module i.e. Condenser Radiator Fan Module (CRFM) and front grille opening is vital hence simulation tools like 1D have gained tremendous importance. This paper focuses on the modeling and analyzing performance behavior of engine cooling system using 1D simulation tool and also discusses the correlation of simulated results with test results. 1D model of engine cooling system is developed by inputting all necessary geometrical and performance data of all components (radiator heat load, coolant pipe geometry, CRFM, pump, thermostat etc.) with necessary assumptions. Air flow rates used on heat exchangers are predicted in 3D Computation Fluid Dynamics (CFD) analysis. First isothermal coolant circuit is modeled and coolant flow correlation is achieved to build confidence in modeling.
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