Demand-controlled ventilation (DCV) is commonly implemented to provide variable amounts of outdoor air according to an internal ventilation demand. The objective of the present study is to investigate the applicability and the performance of occupancy-based DCV schemes in comparison with time-based and CO₂-based DCV schemes. To do this, we apply the occupancy estimation method by the Bayes theorem to control the ventilation rate of an office building in real-time. We investigated six cases in total (two cases for each control scheme). Experiments were conducted in a small office room with controllable ventilation equipment and relevant sensors. The observed results indicated that the occupancy-based schemes relying on Bayes theorem could be applied successfully to perform continuous control of ventilation rates without causing recursive problems. Additionally, we discussed the time delays associated with the control procedure, including dispersion time, sensor-response time, and data processing time. Finally, we compared the performance of the proposed approach in six DCV cases in terms of a resultant indoor CO₂ level and the total ventilation-air volume. We concluded that DCV control based on both occupancy and floor area provided the best conformity to the ASHRAE standard among the analyzed schemes.

需求控制通风（DCV）通常用于根据内部通风需求提供可变数量的室外空气。本研究的目的是与基于时间的和CO ₂相比，研究基于占用的DCV方案的适用性和性能。基于DCV的方案。为此，我们采用贝叶斯定理的占用率估算方法来实时控制办公楼的通风率。我们总共调查了六个案例（每个控制方案两个案例）。在具有可控通风设备和相关传感器的小型办公室中进行了实验。观测结果表明，基于贝叶斯定理的基于占用率的方案可以成功地应用于通风率的连续控制而不会引起递归问题。此外，我们讨论了与控制程序相关的时间延迟，包括分散时间，传感器响应时间和数据处理时间。最后，我们根据产生的室内CO ₂比较了六种DCV情况下该方法的性能液位和总通风量。我们得出结论，在分析方案中，基于占用率和占地面积的DCV控制提供了与ASHRAE标准的最佳一致性。