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CO_2 sensors for occupancy estimations: Potential in building automation applications

机译：用于占用估计的CO_2传感器：在楼宇自动化应用中的潜力

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摘要

It is well established that model-based controllers with an integrated control model and information about indoor climate disturbances have the ability to drastically improve the performance of building automation systems. In offices, occupancy is one of the most important disturbances to account for in this context, but the available methods for accurately determining the number of people are commonly too complex for considering at most sites. However, since model-based controllers can be made robust, input deficiencies can to a certain degree be compensated for, and in this work, a two step procedure was applied to investigate the potential of utilizing simplified estimations generated from CO_2 sensor responses. First, the expected time delay and error of such estimations were derived experimentally for various occupancy changes and ventilation flow rates. Next, an office site was simulated and the occupancy information used by a model-based controller for ventilation control was stepwise subjected to various errors and time delays by considering the expected values as references. The results showed that the estimations in many case were sufficient for achieving a high control performance, but beyond a certain level, the deficiencies could only be met by an increased complexity of the controller.
机译：公认的是，具有集成控制模型和有关室内气候干扰信息的基于模型的控制器具有显着提高楼宇自动化系统性能的能力。在办公室中，占用率是在这种情况下要解决的最重要的干扰之一，但是准确地确定人数的可用方法通常过于复杂，以致于在大多数场所都无法考虑。但是，由于可以使基于模型的控制器变得健壮，因此可以在一定程度上补偿输入缺陷，并且在此工作中，采用了两步过程来研究利用从CO_2传感器响应生成的简化估算值的可能性。首先，通过实验得出各种占用率变化和通风流量的预期时间延迟和此类估计的误差。接下来，模拟一个办公地点，并通过将期望值作为参考，逐步将基于模型的控制器用于通风控制的占用信息遭受各种误差和时间延迟。结果表明，在许多情况下，这些估计值足以实现较高的控制性能，但超过一定水平，只能通过增加控制器的复杂性来弥补缺陷。

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