Abstract
Constant air volume (CAV) air-conditioning system is still widely used for cooling/heating buildings because of the requirement of air changes in many occasions and its simple system design as well as low primary cost. The space temperature of the CAV air-conditioning system is usually controlled by using conventional proportional-integral (PI) control algorithm, which tracks the space temperature by regulating the opening of the water valve directly. However, the control performance of the space temperature is usually unsatisfactory because of the significant thermal inertia of the building mass and the large volume of the indoor air. This paper proposes a model-based cascade control method for the space temperature control of the CAV system aiming to improve the control robustness and accuracy. A supply air temperature prediction model is developed to predict the system demand supply air temperature based on the real-time load condition and space temperature. The prediction is used as the set-point, and the space temperature is well controlled by regulating the water valve opening. The proposed control method was validated in a simulation CAV system as well as on an experimental platform. The validation results show that the proposed model-based cascade control method achieves better space temperature control performance than the conventional PI control. This control method may well track the space temperature directly both in the virtual CAV system and the real experimental system.
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