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• Fast and accurate prediction of high-resolution 3D air distribution are achieved. • The two ANNs respectively use one-step prediction and two-step prediction strategies. • Two-step prediction ANN could be helpful for improving prediction accuracy. • The method can be used for real-time HVAC control targeting occupant areas. To meet the thermal comfort requirements of room occupants, a fast and accurate method for predicting indoor high-resolution 3D airflow distribution is necessary, which can be combined with heating, ventilation, and air conditioning (HVAC) systems to adjust the indoor environment. Artificial neural networks (ANN) can establish complex mappings between variables with nonlinear relationships. The aim of this study was to verify the feasibility of an ANN for the fast and accurate prediction of indoor 3D airflow distribution. Considering two prediction strategies, ANN A and B were constructed. The inputs of both ANNs were the air supply velocity, air supply direction, and section location. ANN A output the airflow distribution of the entire room directly, whereas ANN B output the airflow distribution of the characteristic sections first and then the airflow distribution of other sections according to the contribution of the characteristic sections. The two ANNs' performances on training and testing datasets were compared. Both ANNs performed well in the training and interpolation cases. However, their performances decreased rapidly in the extrapolation cases. In the case of a large gap between the input and output dimensions of the ANNs, the two-step prediction strategy improved the prediction accuracy, accelerated convergence, and alleviated data imbalance problems. The prediction time of ANN A and B was 0.89 s and 12.38 s, respectively. The ANN can predict indoor high-resolution 3D airflow distribution quickly and accurately, and can add functions that include identifying internal heat sources and air supply inlet position changes. ANN combined with HVAC could allow real-time control to regulate indoor airflow. [ABSTRACT FROM AUTHOR]

Liquid desiccant dehumidification, a clean energy technique for creating comfortable environments has received a lot of interest. Several dynamic models have been proposed to predict the outlet air humidity ratio and temperature, however, a study on presenting variations of heat and mass transfer coefficients and thermal mass of desiccant during the dynamic dehumidification process was not encountered according to authors' best knowledge. This gap is primarily due to the complex nature of the coupled heat and mass transfer processes, which make it challenging to capture the evolution of heat and mass transfer coefficients over time. In this study, variations of these parameters are analyzed at first. A theoretical study is conducted to show the thermal mass of the desiccant can be considered constant when changing the inlet air humidity ratio or desiccant temperature, simplifying the dynamic modeling process. While the variation of heat and mass transfer coefficients show significant impact in such conditions. Subsequently, a new method based on mass conservation is provided to determine the thermal mass of desiccant. By examining the cause-and-effect relationships between heat and mass transfer coefficients and outlet air humidity ratio, the evolution of heat and mass transfer coefficients following exponential laws is deduced by inversion. Then a dynamic model of packed dehumidifiers can be completed easily based on above derivations, and its viability is confirmed by experimental results. Compared to the existing method, the prediction accuracy can improve by 50% based on the proposed methods. This study characterizes evolution rules of heat and mass transfer coefficients over time, and with this, evolutions of outlet air parameters during the dynamic dehumidification process can be acquired conveniently based on the existing steady dehumidification model. • Variations of heat and mass transfer coefficients and thermal mass of desiccant are analyzed. • Simple methods are proposed to figure out the evolutions of thermal masses, and heat and mass transfer coefficients. • The prediction accuracy of air outlet humidity ratio could improve by 50% based on the proposed methods. [ABSTRACT FROM AUTHOR]

Liquid desiccant dehumidification technology as an efficient way of handling moisture load has attracted much attention, while the performance of liquid desiccant dehumidifiers has characteristics of uncertainty and time-varying in actual runtime, limiting its application fields. Thus, it is necessary to develop dynamic control methods to achieve stable and efficient operation. As the liquid desiccant dehumidification process is a multi-parameter, time-varying and large delay nonlinear dynamic process, therefore it is difficult to achieve the dynamic control. In this paper, dynamic control methods of the liquid desiccant dehumidification process were studied experimentally for the first time and main difficulties in the dynamic control of the liquid desiccant dehumidification process were presented clearly, helping to learn more knowledge on dynamic control process and facilitate the development of control methods. PID control as a classic control method was applied to control the liquid desiccant dehumidification process firstly, the result showed that it requires long adjusting time to follow the command and is not suitable to control nonlinear dynamic process with large delay. Novel fuzzy logic control (FLC) as an advanced control method was implemented as well, the result demonstrated that it follows command quickly while is unable to maintain the new set point accurately. Then reasons for shortcomings of each control method were analyzed. Along with the above analysis, a new control method, combining the PID control and novel FLC was developed. The command following experiment and disturbance rejection experiment for the newly developed control method were conducted. Control performances are great and validate the feasibility of the new control method. Besides, the newly developed control method also provides a good reference for achieving the dynamic control of a multi-parameter, time-varying, nonlinear dynamic process with large delay. [ABSTRACT FROM AUTHOR]

Researches on packed liquid desiccant dehumidifiers are abundant. However, only a few works concentrate on modeling the dynamic dehumidification process as it requires detailed heat and mass transfer coefficients along the dehumidifier, which are impacted by many factors such as flow pattern of liquid desiccant and hard to be obtained, hindering the development of dynamic models. Data driven modeling method could eliminate the requirement for detailed heat and mass transfer coefficient along the dehumidifier. A time delay neural network (TDNN) model is a general way to describe the dynamic process without the requirement of much knowledge on physical mechanism, yet the number of time steps for each inlet parameter is hard to be determined. In this paper, an improved time delay neural network (iTDNN) model was proposed. Through analyzing characteristics of dehumidification process, model inputs were simplified, which is the core of improvement of TDNN model. Besides, a new combined algorithm including back propagation (BP) algorithm and improved genetic algorithm (GA) was proposed to acquire the optimal weight values globally. The predicted results agree well with the experimental data for validation part. The method presented in the paper provides a reference for modeling multi-variables and large delay nonlinear dynamic systems. [ABSTRACT FROM AUTHOR]

Both temperature control and humidity control are important in buildings. However, usually only temperature is controlled in small and medium-sized buildings using direct expansion (DX) air-conditioning (A/C) systems, while dehumidification is a by-product of cooling, and indoor humidity is in an uncontrolled state. Weights-based fuzzy logic control algorithm (WBFLCA) is a novel fuzzy control algorithm that can be applied to DX A/C systems with good simultaneous temperature and humidity control performance. However, the setting of weight values for WBFLCA is still highly dependent on expert experience and lacks a systematic optimization theory, which hinders the application of WBFLCA. In order to establish a weights setting rule for WBFLCA used in DX A/C systems, a coupled control simulation model is built in this paper to simulate the effect of simultaneous control of temperature and humidity with all 16 basic weights distribution mode combinations. All the 16 combinations are also experimentally tested on an experimental DX A/C system to reveal the control performance of different combinations in a real system. Four of them with good control performance are found. The reasons why these four combinations are good are also analyzed in this paper. Based on the simulation and experimental results, the weights setting rule of WBFLCA applicable to the simultaneous temperature and humidity control of DX A/C systems are summarized. The approach proposed in this paper of finding appropriate pattern combinations from the basic weights distribution patterns has the potential to be applied to solve other decoupling control problems as well. [ABSTRACT FROM AUTHOR]

As the requirement for Li-ion battery thermal management system (TMS) in electric vehicles (EVs) rises, an integrated direct cooling thermal management system with high compactness and energy efficiency has been developed. The integrated system is based on a vapor-compression refrigeration cycle, forming a dual-evaporator system, and adopts a direct cooling scheme on the battery side, which brings high coupling effects. A novel decoupling control strategy was proposed and a weight-based fuzzy logic control algorithm was applied to implement the strategy, achieving effective temperature control and reasonable refrigerant distribution between the battery side and cabin side. Experiments conducted under various scenarios demonstrated that the average temperature of both the battery pack and cabin could be stably controlled around different target values. Maximum fluctuations were effectively limited to less than 0.7 °C in different scenarios. The implementation of this decoupling control strategy has opened up new possibilities for the application of direct cooling TMS in multi-target systems. [ABSTRACT FROM AUTHOR]

Different climate characteristics put forward different requirements for the performance of air conditioning system. Climatic division has been proposed to facilitate the selection or design of HVAC systems to match indoor cooling/heating loads of buildings better. However, humidity parameter and distinction of sensible and latent loads are usually ignored, bringing problems to the operation and control of HVAC systems. Therefore, this study proposed a novel climatic division method for China during the cooling period taking the coupling effect of cooling and dehumidification of HVAC systems into account. The humidity-based cooling degree-day was firstly taken as an index to evaluate the influence of outdoor humidity parameter. Then, 96 cities, whose cooling loads are particularly affected by the humidity, were selected for further analysis. Indoor cooling loads were calculated using EnergyPlus and the climatic division based on sensible heat ratio and total cooling load was presented. Finally, on the basis of the novel climatic division, hourly sensible cooling load and latent cooling load of representative cities in each zone were analyzed to get the characteristics of load boundary and frequency distribution. A new design method was therefore proposed and discussed, paving a new way for the customized design of HVAC systems for each climate zone. [ABSTRACT FROM AUTHOR]

Liquid desiccant dehumidifiers (LDDs) has attracted much attention due to its advantages of energy-saving and environmental protection. However, dynamic characteristics of LDDs, which are essential to develop appropriate control methods, are still not clear at present. In this paper, the performance of a packed LDD was investigated under changes of desiccant inlet temperature and flow rate as well as air inlet humidity ratio, temperature and flow rate. Due to the random packings and interaction between air and desiccant, the air is normally distributed randomly during a dynamic process of LDDs and air outlet humidity ratio at the sampling point is serrated with time going. It was found that exponent function could be utilized to smooth the experimental result of air outlet humidity ratio, providing a simple way to determine the evaluation indexes like the response delay and response time as well as response rate, which could facilitate to evaluate dynamic characteristics of the dehumidifier. And through comparing those evaluation indexes corresponding to changes of different inlet parameters, it was revealed that air outlet humidity ratio was more sensitive to the change of desiccant or air flow rate, but not desiccant inlet temperature as indicated in a previous research getting from quasi-steady state experiments. Therefore, it would be more reasonable to select the desiccant or air flow rate as control variables instead of desiccant inlet temperature. Furthermore, preliminary control experiments were conducted to compare the performance of control algorithms developed based on the steady state characteristics and expert experience of dynamic characteristics. Results show that the control algorithm developed based on the expert experience of dynamic characteristics performs much better, which indicates that the obtained steady state characteristics in existing researches are unsuitable for developing control algorithms for a packed LDD. The dynamic characteristics revealed in current research paves the way for the future development of appropriate control algorithms. [ABSTRACT FROM AUTHOR]

In the field of fluid mechanics, it is a potential consensus that nonlinear dimensionality reduction (DR) techniques outperform linear methods. However, this conclusion has been obtained based on simple fluid phenomena and an incomplete evaluation system of dimensionality reduction algorithms. In this study, we use an improved evaluation system of DR methods to compare and evaluate the performance of four DR methods, including two linear techniques: Principal Component Analysis (PCA) and Independent Component Analysis (ICA), and two non-linear techniques: Isometric Mapping (ISOMAP) and Locally Linear Embedding (LLE). The four methods are applied to analyze a complex hydrodynamic flow field with cavitation by considering the joint features of multiple variables. Results show that LLE can capture redundant features that do not contribute to understanding the characteristics of flow fields, while ISOMAP is more suitable for handling datasets with multiple scales than LLE. PCA and ISOMAP can successfully capture the characteristics and evolution of flow fields. In addition, 3D supplementary information can assist ICA in improving the problem of identifying unstable flow field states. • A comprehensive evaluation of linear and nonlinear dimensionality reduction methods applied to cavitation flow fields. • The evaluation system for dimensionality reduction methods has been enhanced by measuring data structure preservation. • Considering the joint features of multiple variables by combining dimensionality reduction with joint representation. • Utilizing different dimensionality reduction algorithms to identify the states of cavitation flow fields. [ABSTRACT FROM AUTHOR]

The large ownership of direct-expansion (DX) air-conditioning (A/C) systems in small and medium-sized buildings brings with it the need to reduce their energy consumption without damaging the thermal comfort of the occupants. Model predictive control (MPC) is an effective method to optimally control the operation of air-conditioners. However, most existing MPC methods require the investment of additional equipment and labor-intensive work, which greatly increases the cost of MPC and hinders its practical application. To solve the problem, this paper presents an economical and practical MPC algorithm for DX A/C systems, capable of achieving a balance between thermal comfort and energy saving. The proposed algorithm was experimentally validated on both an experimental DX A/C system and a market available split-type air-conditioner. Experimental results on the experimental DX A/C system show that temperature and humidity set-points selected at α = 1 saved 23.3% of energy consumption compared to those selected at α = 0, while keeping indoor thermal comfort within acceptable range. And results on the split-type air-conditioner demonstrate energy savings of up to more than 32% compared to the baseline and proved that the algorithm can be practically applied on market available D/X air-conditioners. • A practical application-oriented model predictive control algorithm is developed for DX A/C systems. • A cooling capacity prediction ANN model of the DX A/C system is used to predict the cooling load. • An ANN model for predicting the operational status of the DX A/C system is developed without increasing the training data. • A cost function is used to balance indoor thermal comfort levels and energy consumption. • The algorithm has been validated in both an experimental DX A/C system and a market available split-type air-conditioner. [ABSTRACT FROM AUTHOR]

The cooling capacity of a radiant ceiling panel (RCP) is highly limited in hot and humid climates as the panel surface temperature must be controlled higher than the air dew point to avoid condensation. Previous research suggested that condensation risks can be mitigated by using superhydrophobic surface materials, making ceiling panels applicable with the surface temperature below the air dew point. In this study, the enhanced cooling capacity of RCP due to latent heat transfer is estimated. Firstly, the condensation heat transfer of a superhydrophobic aluminum surface under natural convection in humid air with subcooling degrees between 3 °C and 12 °C was investigated by experiments. The data proved that the heat and mass transfer analogy method can be used to well predict the condensation heat transfer of the superhydrophobic surface with an error within 15%. Based on the finding, the heat and mass transfer analogy and traditional empirical methods were employed to predict the total heat flux of RCP with latent heat transfer. The results indicated an enhancement of 3% to 500% for the total heat flux compared with RCP with only sensible cooling, depending on the panel surface temperature, air temperature and humidity. This study draws a clear picture of how the cooling capacity of RCP can be enhanced via a latent heat transfer process, and this can be realized not necessarily with net moisture removal capacities with hydrophobic surfaces due to the droplet jumping phenomenon and the due re-evaporation process, showing a hidden potential of radiant cooling panels. [ABSTRACT FROM AUTHOR]