Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
An improved approach for solving the adaptive coefficient in the aPMV (adaptive predictive mean vote) index
https://orcid.org/0000-0002-3357-3935
https://orcid.org/0000-0003-4269-7224
Abstract An accurate evaluation of thermal environments in buildings is beneficial not just for occupant comfort but also for reducing unnecessary overheating or overcooling energy. The aPMV (adaptive Predictive Mean Vote) index can take into account occupants’ thermal adaptations and is stipulated in Chinese standards for evaluating thermal conditions in free-running buildings. Even though substantial studies have validated the efficiency of the aPMV index, it occasionally exhibits limited performance in certain scenarios. This paper proposes a novel algorithm for solving the key adaptive coefficient λ in the aPMV index, aiming to enhance its predictive advantage. Validation conducted using the public ASHRAE thermal comfort database across 14 climate zones demonstrates that the new algorithm-based aPMV index can effectively avoid the “zero crossing” problems in its original solving process and fit data with low errors under various thermal conditions, improving average performance by 34.5–37.7% compared to the previous optimization method. In specific climate condition, its performance improves by more than doubling. The different λ values in the aPMV index are able to quantify specific patterns of occupant thermal adaptations in cold, mild, and hot climates, respectively. Some aPMV outcomes with large deviations can also be explained adequately by the specific properties of the original data sources. The code is available at https://github.com/SuDBE/aPMV-calculation.
Highlights An improved method for solving λ in aPMV index was proposed and validated. The aPMV index can indicate occupant thermal adaptations in various climates. Our method improved on current optimization method by 34.5%–37.7% on average. A calculation package was uploaded on GitHub for better dissemination.
An improved approach for solving the adaptive coefficient in the aPMV (adaptive predictive mean vote) index
https://orcid.org/0000-0002-3357-3935
https://orcid.org/0000-0003-4269-7224
Abstract An accurate evaluation of thermal environments in buildings is beneficial not just for occupant comfort but also for reducing unnecessary overheating or overcooling energy. The aPMV (adaptive Predictive Mean Vote) index can take into account occupants’ thermal adaptations and is stipulated in Chinese standards for evaluating thermal conditions in free-running buildings. Even though substantial studies have validated the efficiency of the aPMV index, it occasionally exhibits limited performance in certain scenarios. This paper proposes a novel algorithm for solving the key adaptive coefficient λ in the aPMV index, aiming to enhance its predictive advantage. Validation conducted using the public ASHRAE thermal comfort database across 14 climate zones demonstrates that the new algorithm-based aPMV index can effectively avoid the “zero crossing” problems in its original solving process and fit data with low errors under various thermal conditions, improving average performance by 34.5–37.7% compared to the previous optimization method. In specific climate condition, its performance improves by more than doubling. The different λ values in the aPMV index are able to quantify specific patterns of occupant thermal adaptations in cold, mild, and hot climates, respectively. Some aPMV outcomes with large deviations can also be explained adequately by the specific properties of the original data sources. The code is available at https://github.com/SuDBE/aPMV-calculation.
Highlights An improved method for solving λ in aPMV index was proposed and validated. The aPMV index can indicate occupant thermal adaptations in various climates. Our method improved on current optimization method by 34.5%–37.7% on average. A calculation package was uploaded on GitHub for better dissemination.
An improved approach for solving the adaptive coefficient in the aPMV (adaptive predictive mean vote) index
https://orcid.org/0000-0002-3357-3935
https://orcid.org/0000-0003-4269-7224
Abstract An accurate evaluation of thermal environments in buildings is beneficial not just for occupant comfort but also for reducing unnecessary overheating or overcooling energy. The aPMV (adaptive Predictive Mean Vote) index can take into account occupants’ thermal adaptations and is stipulated in Chinese standards for evaluating thermal conditions in free-running buildings. Even though substantial studies have validated the efficiency of the aPMV index, it occasionally exhibits limited performance in certain scenarios. This paper proposes a novel algorithm for solving the key adaptive coefficient λ in the aPMV index, aiming to enhance its predictive advantage. Validation conducted using the public ASHRAE thermal comfort database across 14 climate zones demonstrates that the new algorithm-based aPMV index can effectively avoid the “zero crossing” problems in its original solving process and fit data with low errors under various thermal conditions, improving average performance by 34.5–37.7% compared to the previous optimization method. In specific climate condition, its performance improves by more than doubling. The different λ values in the aPMV index are able to quantify specific patterns of occupant thermal adaptations in cold, mild, and hot climates, respectively. Some aPMV outcomes with large deviations can also be explained adequately by the specific properties of the original data sources. The code is available at https://github.com/SuDBE/aPMV-calculation.
Highlights An improved method for solving λ in aPMV index was proposed and validated. The aPMV index can indicate occupant thermal adaptations in various climates. Our method improved on current optimization method by 34.5%–37.7% on average. A calculation package was uploaded on GitHub for better dissemination.
An improved approach for solving the adaptive coefficient in the aPMV (adaptive predictive mean vote) index
Zhang, Shaoxing (Autor:in) / Yao, Runming (Autor:in) / Li, Baizhan (Autor:in)
Building and Environment ; 256
02.04.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
A theoretical adaptive model of thermal comfort - Adaptive Predicted Mean Vote (aPMV)
| British Library Online Contents | 2009
A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)
| Online Contents | 2009
A theoretical adaptive model of thermal comfort – Adaptive Predicted Mean Vote (aPMV)
| Online Contents | 2009