Predictive functional control based on fuzzy T-S model for HVAC systems temperature control

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on Takagi-Sugeno （T-S） fuzzy model was proposed to control HVAC systems. The T-S fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from T-S fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

Leveraging graph convolutional networks for semi-supervised fault diagnosis of HVAC systems in data-scarce contexts

The continuous accumulation of operational data has provided an ideal platform to devise and implement customized data analytics for smart HVAC fault detection and diagnosis.In practice,the potentials of advanced supervised learning algorithms have not been fully realized due to the lack of sufficient labeled data.To tackle such data challenges,this study proposes a graph neural network-based approach to effectively utilizing both labeled and unlabeled operational data for optimum decision-makings.More specifically,a graph generation method is proposed to transform tabular building operational data into association graphs,based on which graph convolutions are performed to derive useful insights for fault classifications.Data experiments have been designed to evaluate the values of the methods proposed.Three datasets on HVAC air-side operations have been used to ensure the generalizability of results obtained.Different data scenarios,which vary in training data amounts and imbalance ratios,have been created to comprehensively quantify behavioral patterns of representative graph convolution networks and their architectures.The research results indicate that graph neural networks can effectively leverage associations among labeled and unlabeled data samples to achieve an increase of 2.86%–7.30%in fault classification accuracies,providing a novel and promising solution for smart building management.

Reducing Electrical Consumption in Stationary Long-Haul Trucks

On average, long-haul trucks in the U.S. use approximately 667 million gallons of fuel each year just for idling. This idling primarily facilitates climate control operations during driver rest periods. To mitigate this, our study explored ways to diminish the electrical consumption of climate control systems in class 8 trucks through innovative load reduction technologies. We utilized the CoolCalc software, developed by the National Renewable Energy Laboratory (NREL), which integrates heat transfer principles with extensive weather data from across the U.S. to mimic the environmental conditions trucks face year-round. The analysis of the CoolCalc simulations was performed using MATLAB. We assessed the impact of various technologies, including white paint, advanced curtains, and Thinsulate insulation on reducing electrical demand compared to standard conditions. Our findings indicate that trucks operating in the eastern U.S. could see electrical load reductions of up to 40%, while those in the western regions could achieve reductions as high as 55%. Such significant decreases in energy consumption mean that a 10 kWh battery system could sufficiently manage the HVAC needs of these trucks throughout the year without idling. Given that many long-haul trucks are equipped with battery systems of around 800 Ah (9.6 kWh), implementing these advanced technologies could substantially curtail the necessity for idling to power air conditioning systems.

Comparative analysis of technical requirements for Heating,Ventilating,and Air Conditioning(HVAC)systems in high-biocontainment facility standards

In this study,standards of high-biocontainment facilities(including laboratories and large-scale production facilities)formulated by China and other countries were analyzed and compared,and the technical points and requirements for Heating,Ventilating,and Air Conditioning(HVAC)systems in different series of standards were discussed.The main focus was on expounding the design and verification of the containment area’s indoor parameters,ventilation system,filter design,integrity test,fan standby,airflow pattern,and system reliability.This study expects suggestions and opinions on the construction and development of biosafety facilities in China and the possible future revision of relevant national standards.

SIMPLE NONLINEAR OPTIMIZATION-BASED SELECTION OF INSULATION MATERIAL AND WINDOW TYPE IN TURKEY:EFFECT OF HEATING AND COOLING BASE TEMPERATURES

The energy-savings of four hypothetical households in different climatic regions of Turkey were calculated via a nonlinear mixed integer optimization model.The ideal insulation material,its optimum thickness,and the ideal window type were determined.The standard degree days method was used with five different base temperatures for heating and five different base temperatures for cooling.The climatic conditions of the region,the properties of the insulation options,the unit price of fuel and electricity and the base temperature are used as model inputs,whereas the combination of selected insulation material with its optimum thickness and window type are given as model outputs.Stone Wool was found to be the ideal wall insulation material in all scenarios.The optimum window type was found to depend on the heating or cooling requirements of the house,as well as the lifetime of insulation.The region where the energy saving actions are deemed most feasible has been identified as Erzurum(Region 4),followed by Antalya(Region 1).Finally,the effect of changing the base temperature on energy savings was investigated and the results showed that an approximate average increase of$15/℃ in annual savings is possible.Our model can be used by any prospective home-owner who would like to maximize their energy savings.

A systematic review on COVID-19 related research in HVAC system and indoor environment

The on-going COVID-19 pandemic has wrecked havoc in our society,with short and long-term consequences to people’s lives and livelihoods-over 651 million COVID-19 cases have been confirmed with the number of deaths exceeding 6.66 million.As people stay indoors most of the time,how to operate the Heating,Ventilation and Air-Conditioning(HVAC)systems as well as building facilities to reduce airborne infections have become hot research topics.This paper presents a systematic review on COVID-19 related research in HVAC systems and the indoor environment.Firstly,it reviews the research on the improvement of ventilation,filtration,heating and air-conditioning systems since the onset of COVID-19.Secondly,various indoor environment improvement measures to minimize airborne spread,such as building envelope design,physical barriers and vent position arrangement,and the possible impact of COVID-19 on building energy consumption are examined.Thirdly,it provides comparisons on the building operation guidelines for preventing the spread of COVID-19 virus from different countries.Finally,recommendations for future studies are provided.

Environmental parameters assessment of a new diffuser for air cooling/heating system:Measurements and numerical validation

Air distribution of HVAC systems is the most popular type used in the building sector,having a relevant impact on indoor air quality and occupant wellness.Many types of research developed optimal solutions for the HVAC system’s design,focusing on specific components of the distribution system,on the airflow and geometry of ducts,on the size of ducts,on the shape and position of air diffusers.However,few works in literature proposed a globally experimental and simulation analysis of an air distribution system with a variable mass flaw rate.Along this line,the presented research investigates the potentialities of a new ceiling diffuser,installed in an exhibition room.This system provides a variable mass flow rate thanks to its configuration,providing adequate thermal comfort.A warm wall is chosen as the heating system.Several tests are carried out,six for cooling and two for heating with different volumetric air rates and supply air temperature of the diffusers.The combination of two methods,the measurement campaigns and the computational fluid dynamics(CFD)technique represent a suitable approach to examine the thermal indoor environment.In general,results show a strong capability of this diffuser to provide a uniform temperature and velocity field inside the room.Moreover,experimental and numerical data are significantly comparable with an average deviation of 1%for the velocity and lower 1%for the temperature,guaranteeing an optimal distribution of the understudy environmental parameters on the vertical and horizontal planes.