An intelligent air conditioning control system that reduces the energy consumption of the vehicle and improves its efficiency was presented. An intelligent air conditioning system controls the operation of the A/C (Air Conditioning), blower, and fresh air and recirculation gates to provide the desired comfort temperature and indoor air quality. It also uses intelligent energy management that is able to reduce the energy consumption of vehicle air conditioning and improve its efficiency by using the look-ahead system and road power demand by considering rolling power, up and down hill power and aerodynamic drag from the wind. The look-ahead system is an algorithm that estimates future road slope within a distance of 300-500 m ahead of the vehicle by determining the sampling locations of slope. In order to calculate the prediction slope angle, the geometric means is used and then the angle result can be calculated by using look-ahead function between the current angle and the predicted angle. Two simulations were performed under sunny conditions, without/with look-ahead system and controlling the blower, air conditioning, and the gates. These simulation results also have been compared with CEMS (Coordinated Energy Management System) method. A reduced amount of energy consumption can be achieved for the desired comfort temperature and indoor air quality within the cabin. The developed fuzzy air conditioning enhanced look-ahead system reduced the energy usage under the reported simulation conditions by approximately 3% compared with using the ordinary fuzzy air conditioning controller and 12% with CEMS method.


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    Title :

    Intelligent energy management control of vehicle air conditioning via look-ahead system


    Additional title:

    Intelligente Energiemanagementregelung der Fahrzeugklimatisierung mit Hilfe eines Look-Ahead-Systems


    Contributors:

    Published in:

    Applied Thermal Engineering ; 31 , 16 ; 3147-3160


    Publication date :

    2011


    Size :

    14 Seiten, 19 Bilder, 11 Tabellen, 31 Quellen




    Type of media :

    Article (Journal)


    Type of material :

    Print


    Language :

    English




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