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Multi-sensor information fusion based control for VAV systems using thermal comfort constraints

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Abstract

The conventional control methods of variable air volume (VAV) air conditioning systems usually assume that the indoor air is well mixed, and consider each building zone as one node with homogeneous temperature distribution. The average temperature is subsequently used as the controlled parameter in the VAV cascade control process, which might cause uneven temperature distribution and unsatisfactory thermal comfort. This paper presents a coupled simulation of computational fluid dynamics (CFD) and building energy simulation (BES) for the VAV system in an office building located in Shanghai for the purpose of simulating the building, the VAV control system, and indoor thermal environment simultaneously. An external interface is developed to integrate the CFD and BES models based on quasi-dynamic coupling approach. Based upon the developed co-simulation platform, the novel VAV control method is further proposed by fusing information from multiple sensors. By adding two temperature sensors to constrain the thermal comfort of the occupied zone, the supply air temperature setpoint of the VAV terminal unit can be reset in real time. The novel control method is embedded into the co-simulation platform and compared with the conventional VAV control approach. The results illustrate that the temperature distribution under the proposed method is more uniform. At most times of the typical test day, the air diffusion performance indexes (ADPIs) for the proposed method are above 80%, while the ADPIs for the conventional control method are between 60% and 80%. Due to multi-sensor information fusion, the proposed VAV control approach has better ability to ensure the indoor thermal comfort.

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Abbreviations

A :

area (m2)

A-C:

sensor positions

ADPI:

air diffusion performance index

AHU:

air handling unit

BES:

building energy simulation

CC:

pollutant concentration (ppm)

CFD:

computational fluid dynamics

DEM:

supply air temperature limitation

e :

difference of controlled variable and its setpoint

F :

mass flow rate (kg s−1)

G :

humidity (kg kg−1)

H :

control output

h :

heat transfer coefficient (W m−2 K−1)

HVAC:

heating, ventilation and air conditioning K gain

k 1 :

number of building zones with connecting walls

k 2 :

number of building zones without connecting walls

m :

air mass (kg)

M :

metabolic rate (W m−2)

P :

pressure (Pa)

PMV:

predicted mean vote

Q :

heat (kW)

R :

thermal resistance (K kW−1)

S :

moisture or pollutant generation rate

T :

temperature (°C)

t :

time (s)

V :

air volume (m3)

v :

volume flow rate (m3 s−1)

VAV:

variable air volume

W :

mechanical work (W)

ρ :

air density (kg m−3)

τ :

time constant

ave:

average

cl:

cloth

exf:

exfiltration

eq2 :

inside part of the wall

fur:

furniture

in:

inlet

inf:

infiltration

int:

internal

out:

outlet

plt:

pollutant

RA:

return air

SA:

supply air

set:

setpoint

str:

non-transparent layer

win:

transparent layer

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 51876119) and the Shanghai Pujiang Program (No. 17PJD017).

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Authors and Affiliations

  1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Xu Zhu, Taotao Shi, Xinqiao Jin & Zhimin Du

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  1. Xu Zhu
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  2. Taotao Shi
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  3. Xinqiao Jin
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  4. Zhimin Du
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Correspondence to Zhimin Du.

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Zhu, X., Shi, T., Jin, X. et al. Multi-sensor information fusion based control for VAV systems using thermal comfort constraints. Build. Simul. 14, 1047–1062 (2021). https://doi.org/10.1007/s12273-020-0736-9

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  • DOI: https://doi.org/10.1007/s12273-020-0736-9

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