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Technical Paper

HVAC System Bench Test Analysis for TXV Tuning

2018-04-03
2018-01-0070
In today’s automotive industry, the A/C (Air-conditioning) system is emerging into a high level of technological growth to provide quick cooling, warm up and maintaining the air quality of the cabin during all-weather conditions. In HVAC system, TXV plays vital role by separating high side to low side of vapor compression refrigeration system. It also regulates the amount of refrigerant flow to the evaporator based on A/C system load. The HVAC system bench laboratory conducts the test at different system load conditions to evaluate the outputs from tests during initial development stage to select the right TXV in terms of capacity and Superheat set point for a given system. This process is critical in HVAC developmental activity, since mule cars will be equipped with selected TXV for initial assessment of the system performance.
Technical Paper

Robust 1D Modelling for Automotive HVAC Warmup Prediction Using DFSS Approach

2017-03-28
2017-01-0179
In an automotive air-conditioning (AC) system, the heater system plays a major role during winter condition to provide passenger comforts as well as to clear windshield defogging and defrost. In order to meet the customer satisfaction the heater system shall be tested physically in severe cold conditions to meet the objective performance in wind tunnel and also subjective performance in cold weather regions by conducting on road trials. This performance test is conducted in later stage of the program development, since the prototype or tooled up parts will not be available at initial program stage. The significance of conducting the virtual simulation is to predict the performance of the HVAC (Heating ventilating air-conditioning) system at early design stage. In this paper the development of 1D (One dimensional) model with floor duct systems and vehicle cabin model is studied to predict the performance. Analysis is carried out using commercial 1D simulation tool KULI®.
Technical Paper

Optimization of HVAC Panel Aiming Studies using Parametric Modeling and Automated Simulation

2014-04-01
2014-01-0684
In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.
Technical Paper

Studies on AC Suction Line Pressure Drop using 1D Modeling

2013-04-08
2013-01-1503
In an automotive air-conditioning (AC) system, the amount of work done by the compressor is also influenced by the suction line which meters the refrigerant flow. Optimizing the AC suction line routing has thus become an important challenge and the plumbing designers are required to come up with innovative packaging solutions. These solutions are required in the early design stages when prototypes are not yet appropriate. In such scenarios, one-dimensional (1D) simulations shall be employed to compute the pressure drop for faster and economical solution. In this paper, an approach of creating a modeling tool for suction line pressure drop prediction is discussed. Using DFSS approach L12 design iterations are created and simulations are carried out using 1D AMESim software. Prototypes are manufactured and tested on HVAC bench calorimeter. AC suction line pressure drop predicted using the 1D modeling co-related well with the test data and the error is less than 5%.
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