Optimization of Center Console Duct Using Robust Assessment Methodology 2018-01-0072

The thermal comfort for the passenger inside the cabin is maintained by the HVAC system. To ensure a comfort for the 2^nd row passengers in the cabin, it is very essential to design an efficient HVAC and rear console duct system which can deliver sufficient airflow with less pressure drop. The primary focus of the study is to assess existing airflow of the center console duct using CFD and propose improvement in its duct shape to meet the passenger comfort sitting in the rear seat. In this study, the vehicle cabin model, HVAC system and duct design was modeled using the design software UG. To analyze and estimate the behavior of the air flow of the system, a steady state simulation was performed using STAR CCM CFD software. The performance of the console duct system is judged by parameters like distribution of airflow, velocity at console duct outlet, pressure drop through the duct and the uniformity of the air flow at the passenger locations. Robust assessment methodology is followed for optimization of console duct to reduce the simulation iterations and arrive at the combination of appropriate design factors which influences the airflow, pressure drop within the duct and velocity at second row passenger locations within the short span of time. The impacts of each design factors on the output results have been analyzed extensively and best combination of design factors have been found out quickly through this methodology. Robust assessment methodology significantly aids in reducing the CFD simulation iterations by 40% and much faster than conventional optimization process. Vehicle testing was carried out for the existing and optimized console duct design to measure the improvement in airflow and velocity at passenger locations. There is a good correlation agreement between simulation and test results for the optimized design within the error of 10%. This methodology is very useful in reducing the number of prototypes, minimize the testing cost and reduce the simulation iterations during design and development stages of the program.