Providing thermal comfort and saving energy are two main goals of HVAC (heating, ventilation and air conditioning) systems. A controller with temperature feedback cannot best achieve the thermal comfort. This is because thermal comfort is influenced by many variables such as, temperature, relative humidity, air velocity, environment radiation, activity level and cloths insulation. In this study Fanger's PMV (predicted mean value) index is used as controller feedback. It is simplified without introducing significant error. Thermal models of the cabin and HVAC system are developed. Evaporator cooling capacity is selected as a criterion for energy consumption. Two fuzzy controllers one with temperature as its feedback and the other PMV index as its feedback are designed. Results show that the PMV feedback controller better controls the thermal comfort and energy consumption than the system with temperature feedback. Next, the parameters of the fuzzy controller are optimized by genetic algorithm. Results indicate that thermal comfort level is further increased while energy consumption is decreased. Finally, robustness analysis is performed which shows the robustness of optimized controller to variables variations.


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    Title :

    Controlling automobile thermal comfort using optimized fuzzy controller


    Additional title:

    Kontrolle des Wärmekomforts von Kraftfahrzeugen mittels optimierter Fuzzy-Regler


    Contributors:

    Published in:

    Applied Thermal Engineering ; 28 , 14/15 ; 1906-1917


    Publication date :

    2008


    Size :

    12 Seiten, 19 Bilder, 5 Tabellen, 34 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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