A compensation model for an NDIR-based CO2 sensor and its energy implication on demand control ventilation in a hot and humid climate

Tun Ping Teng, Wei Jen Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Non-dispersive infrared absorption spectroscopy (NDIR)-based CO2 sensors currently dominate the market for building applications. Yet, the affordable ones are frequently found to have a reading that deviates from the actual CO2 concentration, which hinders the proper operation of the demand control ventilation (DCV). This study aims to propose a compensation method to mitigate the CO2 sensor deviation due to water vapor interference. Its energy implication is simulated afterward by creating a 464 m2 office space model equipped with the DCV in EnergyPlus. Per the results of multiple standard gas experiments performed in a controlled environment, the proposed model has a coefficient of determination R2=0.899, and is able to reduce the normalized root mean square error from 8.1 % (before compensation) to 2.6 % (after compensation) for a selected NDIR CO2 sensor, showing a 67.9 % reduction. Meanwhile, the tested sensor is originally prone to underestimate the CO2 concentration, leading to less ventilation rate in DCV. As a result, there will be a 6.97 % increment in the annual ventilation electricity load of the modeled building after compensation, but in exchange for a better controlled indoor CO2 concentration that was underestimated by 3.0 to 13.1 % (on average 7.9 %) depending on zone conditions before compensation.

Original languageEnglish
Article number112738
JournalEnergy and Buildings
Volume281
DOIs
Publication statusPublished - 2023 Feb 15

Keywords

  • Carbon dioxide
  • Demand control ventilation
  • Indoor air quality
  • NDIR (Non-Dispersive Infrared)

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction
  • Mechanical Engineering
  • Electrical and Electronic Engineering

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