Simulating Thermal comfort for a vehicle

The vehicle HVAC system is designed to meet both the safety and thermal comfort requirements of the passengers inside the cabin. The thermal comfort requirement, however, is highly subjective and is usually met objectively by carrying out time dependent mapping of parameters like the velocity and temperature at various in-cabin locations. These target parameters are simulated for the vehicle interior for a case of hot soaking and its subsequent cool-down to test the efficacy of the AC system. Typically, AC performance is judged by air temperature at passenger locations, thermal comfort estimation alongwith time to reach comfortable condition for human. Simulating vehicle cabin for thermal comfort evaluation is computationally expensive and requires complex cabin material modelling. Coupled simulation between LBM based Powerflow and Finite element based Powertherm solver is employed and discussed here to simulate thermal comfort. Additionally, the human thermal physiology is modelled, to account for subjective evaluation of the in-cabin thermal environment, by Berkeley model defined in the commercial software Powertherm. The model takes care of the vasodilation and vasoconstriction effects, based on the external human ambient, along with the effects of clothing and the passenger metabolic rate. Vasodilation and vasoconstriction are the phenomenon by which blood vessels widened or narrow the blood flow through it depending upon the ambient which could be warm or cold. Lattice Boltzmann Method based flow solver is used to predict convective heat transfer phenomenon from both the exterior and interior of the cabin. The conduction and the radiation effects including the solar loading were solved using a finite-element based radiation-conduction thermal solver. Glazing material sensitivity is carried out for absorbing and reflective glass material. Physical test is carried under controlled ambient conditions of climate chamber for a car cabin. Results from the coupled approach correlates well the test results for both hot soaked and cool-down conditions with a significant reduction in simulation time. During the cabin cool-down phase passenger thermal comfort is predicted using Predictive Mean Vote. This process is further used to study the effect of change in properties of the glazing areas and roof insulation on the cabin thermal ambient including passenger thermal comfort, cabin heat ingress and part temperatures during test cycle. The process is deployed and found useful for vehicle level thermal comfort prediction.