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The extension of time-of-use (TOU) rates to residential buildings has incentivized the use of thermal energy storage (TES) to shift heating and cooling loads away from on-peak hours. At the same time, the growing use of solar photovoltaics (PV) for on-site energy generation with variable buy back rates also encourages the use of TES to store energy generated at hours of peak solar radiation. Metal hydrides are reversible chemical compounds that form when certain metals react with hydrogen. Since these reactions depend on both temperature and pressure, metal hydrides can be used for thermochemical energy storage across a range of temperatures. Because of this, metal hydrides can be used as storage for both heating and cooling, enabling year-round utilization. In this paper, we present and evaluate a system that combines metal hydride energy storage with heat pumps and on-site PV. The system is designed to reduce operating costs by discharging the energy storage system during on-peak hours when electricity is expensive and charging the system during off-peak periods when electricity is less expensive and there is less incentive to sell excess PV electricity generation back to the grid. The TOU rates considered are designed for a future scenario with high solar penetration, where greater solar generation in the afternoon leads to on-peak periods in the mornings and evenings rather than the afternoon. The payback period of the energy storage system is estimated using energy savings relative to a baseline of a solar home without an energy storage system along with estimates of additional installed costs for the storage system. Payback period calculations for a range of rates show that rates with on-peak demand charges result in larger cost savings than rates with high on-peak rates, but even for the most favorable rates, the payback period is too long for the system to be economically viable.

Most air conditioning and refrigeration systems that employ the vapor compression cycle rely on oil circulating with refrigerant to lubricate the bearings and other contact surfaces in the compressor. The lubricant acts as a sealant to reduce leakage losses during the compression process and it also helps to absorb some of the excess heat that is generated in the compression chamber. However, this oil circulation results in oil retention in various other components outside the compressor depending on the physical interaction between lubricant and refrigerant and their transport properties. Other factors, such as geometry and orientation of connecting lines and system operating conditions (e.g., refrigerant flow rate and oil circulation ratio), also impact the oil retention. As a result of oil retention, the oil level in the compressor reduces, which may ultimately affect its efficiency and life span. In addition, the pressure drop across the system increases and the efficiency of heat exchangers (evaporators and condensers) decreases with oil retention. The current line sizing rules reported in the ASHRAE Handbook Refrigeration have only limited consideration of the effects of oil in the system. With the increasing development of variable speed systems as well as future use of newer refrigerants, there is a need in the industry for upgrading the line sizing recommendations to consider the effects of oil retention, especially the connecting gas lines of unitary split systems. To address this issue, a physics based model has been developed to predict oil retention in horizontal lines. The model is validated using experimental data collected for R410A-POE32. The developed model will be a backbone of a design tool, which will provide more information on oil retention in refrigerant gas lines of the commonly used refrigerant-lubricant combinations in the HVAC&R industry.

There is a significant opportunity to improve building energy efficiency and indoor environmental quality by accurately monitoring CO2 levels. However, current CO2 sensors tend to be expensive or require regular recalibration. This work presents research related to the initial development and evaluation of two novel CO2 sensors based on chemiresistive and resonant mass sensing techniques. Prototype sensors were assessed in a bench-top test chamber at temperatures, humidity levels, and CO2 concentrations, typical of indoor environments. Under these conditions, prototype sensors required only 60 mW of power, or less. Further, each sensor was developed to have a footprint of less than 25 mm2 and a cost of less than $50. Given the relative low cost, small size, and potential for low power consumption, these sensors may serve as an attractive alternative to the commercial CO2 sensors that are currently available.

A future is envisioned where buildings are assembled on-site from factory manufactured modular elements that integrate the smart technology needed to enable scalable, cost-effective solutions with autonomous, occupant-responsive, healthy, and sustainable features. The use of modular elements would mean that buildings are assembled rather than constructed on-site with better quality control, less material waste, and more predictable schedules. The use of manufactured building elements can enable more cost-effective integration of new sensors, embedded intelligence, networking, adaptive interfaces, renewable energy, energy recovery, comfort delivery, and resiliency technologies, making high-performance buildings more affordable. To explore and evaluate these modular and intelligent comfort delivery concepts and advanced approaches for interaction with occupants, a new human-building interaction laboratory (HBIL) has been designed and is under development. The facility has a modular construction layout with thermally active panels. The interior surface temperature of each panel can be individually controlled using a hydronic system. Such configuration allows us to emulate different climate zones and building type conditions and perform studies such as the effect of different active building surfaces on thermal comfort, localized comfort delivery, and occupant comfort control, among others. Moreover, each panel is reconfigurable to allow investigating different interior surface treatments for different visual and acoustic comfort conditions. In this paper, the overall design approach of the facility is presented. Furthermore, a prototype panel has been constructed to validate the design and assess the dynamic and steady-state thermal performance. Test results for the prototype panel are also presented here with a discussion on their agreement with design phase modeling results.

Seasonal performance assessments of air-conditioning and heat-pump systems are typically carried out based on performance measurement of equipment in a test laboratory. The performance ratings that arise from these assessments are important in providing information to consumers, and in influencing policymakers to determine appropriate incentives for high-efficiency equipment in the marketplace. The current testing and rating approach for performance evaluation of residential air-conditioning and heat-pump systems is based on steady-state performance measurements, with a degradation coefficient to account for the cycling losses that occur during part-load operating conditions. However, this current methodology fails to appropriately characterize the true performance characteristics of these systems in the field, and as a consequence, SEER (seasonal energy efficiency ratio) improvements have not resulted in proportional savings in energy. As an alternative, a load-based testing methodology has been developed with the motivation of capturing realistic equipment performance in a laboratory setting while operating similar to field application conditions. In this approach, the equipment responds to a simulated virtual building load, and the system dynamic performance is measured with its integrated controls and thermostat. However, there is a lack of field-testing data to characterize how well the load-based testing approach captures equipment performance and dynamic behavior compared to a typical field application. To fill this gap, a 3-ton heat pump system was tested within the Residential Home Ecosystem at the Helix Innovation Center where a 2-story house is located within an environmental chamber that can vary external ambient temperature and humidity conditions. During tests, the house was subjected to cooling loads resulting from different outdoor temperature conditions, and its air conditioning system responded accordingly. Similar cooling equipment was also tested within psychrometric chambers at the Ray W. Herrick Laboratories using the load-based testing methodology. A comparison of the test equipment performance and its dynamic behavior in cooling mode between testing performed at the Helix Center and at the Herrick Laboratories is presented in this paper.

Implementation of an ejector for expansion work recovery in transcritical carbon dioxide (CO2) cycles provides an opportunity to improve the efficiency of these environmentally-friendly refrigeration systems. However, literature outlining an approach to ejector design for a given application is lacking. This paper presents a tool to design a complete ejector applied in a vapor compression cycle. In this work, the developed design tool was validated using experimentally-derived polynomials for air-conditioning conditions. Then, constant values for nozzle and mixing section efficiencies were used as inputs into design tool to broaden the analysis outside of the application boundaries of the experimentally-derived polynomials to study a transcritical CO2 system with an ejector operating in the evaporating temperature and gas cooler pressure in the range of -15 °C to 20 °C and 80 bar to 110 bar, respectively. The design tool allows for the calculation of the motive and suction nozzle throat diameters, the mixing section diameter, and the diffuser outlet diameter, as well as the lengths of each section, to output a full internal geometry of the ejector based on performance requirements. Individual component sub-models are presented within the proposed model structure. The model which forms the basis of the design tool was experimentally validated with a mean absolute error (MAE) between 3% to 4%. Additionally, the sensitivity of the ejector geometry and performance to component efficiencies, operating conditions, and component versus system optimization was investigated. The optimization and parametric studies provided novel insights into the impact of desired efficiency and operating conditions on ejector geometry, thus allowing a designer to make decisions based on the tradeoff between ejector size and performance. For example, as the diffuser length increased by 5.1 mm to obtain an efficiency increase, to obtain a further efficiency increase of the same amount would require a 17.1 mm length increase in diffuser length. Potential model improvements and other future work are also discussed.

Compressor testing is an essential task to characterize compressor performance, but often requires significant time to be executed. This study suggests a method that could greatly reduce time needed for compressor testing by inferring steady state performance from transient data rather than waiting for true steady state conditions to be measured. The key finding is that the overall isentropic efficiency in transient operation is almost identical to its true steady state performance value after applying very simple data processing. The paper describes a simple data processing method that extracts steady-state performance from transient data. The proposed processing should not be understood as a general rule to all compressors, but as a positive result for this particular compressor and a first glimpse into the value of transient data for performance estimation.

HVAC, refrigeration, and water heating accounted for approximately 22 quads of primary energy consumed in the United States in 2018, according to US EIA. Most of HVAC&R industry still relies on vapor compression and heat-driven technologies. The development of highly efficient technologies that would significantly improve both COP and annual energy savings is an open challenge for the new decade. Among the novel technologies, the Chemical Looping Heat Pump (CLHP) combined with a reverse fuel cell has been modeled with estimates of a COP increase of over 20% relative to a conventional vapor compression (VC) cycle. However, limitations of simplified modeling efforts necessitate the development of a comprehensive mechanistic model to predict several physical phenomena for varying operating conditions and more accurately estimate performance. In this work, a charge-sensitive mechanistic modeling approach is utilized to predict the performance of the CLHP system. A thermodynamic model is coupled with a discretized fuel cell model to estimate the energy savings potential. A moving boundary model is adopted to assess the steady-state heat transfer rate in the heat exchanger. Sensitivity analyses are used to identify the system behaviors and performance.

This paper presents a reduced order modeling approach for dynamic vapor compression cycles (VCC) based on a trajectory piecewiselinear (TPWL) approximation and Proper Orthogonal Decomposition (POD). Unlike other model order reduction techniques that apply to nonlinear dynamic heat exchanger (HX) models, the TPWL approach first represents a finite volume HX model with a weighted combination of linearized models along some state trajectories. Linearization points are selected by the kmeans clustering algorithm, which enables control of the number of linearized pieces. Then, each of the full order linear pieces is reduced by projection onto a POD basis to form a reduced order TPWL model. Reduced order HX models were generated and integrated with other quasistatic component models to complete a reduced order VCC model. Simulation results were compared with experimental data for cycle loadchange transients over a wide range of operating conditions. The proposed method is an alternative to a nonlinear model order reduction framework that is presented in a companion paper (Ma et al., 2020) and may be particularly useful for cases where it is challenging to stabilize nonlinear reduced order models. Comparisons were drawn between these two approaches in terms of generalization, stabilization and computational efficiency.

Current performance evaluation approaches for commercial packaged air conditioning and heat pump equipment (e.g. AHRI 340/360) utilize full-load steady-state performance tests to estimate system EER (energy efficiency ratio) at different ambient conditions and part-load steady-state tests to estimate an IEER (integrated energy efficiency ratio), a figure of merit for system part-load performance. There are some limitations of the current testing approaches and performance metric estimations, including that they do not consider the effects of: 1) test unit embedded controls and their realistic interactions with the building load; 2) different climate zones and building types; and 3) economizer operation. As a result, the overall performance measurement procedure does not appropriately incentivize the development of better performing controls and economizers. In this paper, an improved testing procedure applied to packaged air conditioning equipment, such as rooftop units (RTUs), that include the effects of embedded controls, economizers, climate, and building type is presented. The testing approach is based on allowing the integrated equipment system and controls to respond naturally to a “virtual building load”. This is termed load-based testing and involves dynamically adjusting the indoor room temperature and humidity setpoints for the psychrometric chamber reconditioning system in a manner that emulates the response of a building’s sensible and latent loads to the test equipment controls. The developed test methodology is demonstrated to evaluate the dynamic performance of a 5-ton variable-speed RTU with an integrated economizer in a psychrometric test facility.

Space heating is one of the primary components of residential energy usage in the U.S., accounting for nearly 43% (EIA, 2015) of the total residential energy consumption. To reduce this energy usage, heat-pumps provide an energy-efficient alternative to currently prevalent systems such as electric heaters and gas furnaces. Advanced control strategies have the potential to further improve heat-pump system energy efficiency and comfort delivery. In recent years, advancements in the microprocessor field have made it possible to widely implement advanced energy-efficient controls within heat-pump systems. However, still only a very small fraction of residential air-conditioners and heat-pumps currently sold in the U.S. market utilize these next-generation controls (ACEEE, 2019). To facilitate an acceleration in the development and implementation of advanced control architectures within heat-pump equipment, a load-based testing methodology can be utilized. Load-based testing allows realistic dynamic behavior and performance evaluation of energy efficiency and comfort delivery for heat pumping and air conditioning equipment with embedded controls in a laboratory setting. In the load-based testing methodology, the sensible and latent loads of a representative residential building are emulated in the indoor psychrometric test room by dynamically varying the test room conditions utilizing a virtual building model. The test equipment responds dynamically to this virtual building with its embedded controls based on the thermostat sensing response. This enables engineers to evaluate the performance of a heat-pump in a controlled setting under dynamic conditions that are similar to a field application but with a significant reduction in testing time and cost. This paper demonstrates the application of load-based testing for evaluating the performance of a 5-ton split-type residential heat-pump with its integrated controls in a heating mode application. Furthermore, the effect of equipment oversizing and undersizing on the heat-pump energy consumption and comfort delivery are also presented.

A computationally efficient and accurate modeling approach is critically important for designing and evaluating controls and fault detection and diagnosis (FDD) algorithms. This paper proposes a reduced order modeling approach for vapor compression cycles (VCC) that involves application of nonlinear model order reduction (MOR) methods to dynamic heat exchanger (HX) models to generate reduced order HX models. A reformulated finite volume HX model was first developed that matches the baseline MOR model structure. Then, a nonlinear MOR framework based on Proper Orthogonal Decomposition (POD) and a Discrete Empirical Interpolation Method (DEIM) was developed for generating nonlinear reduced order HX models. The proposed approach was implemented within a comprehensive VCC model. Reduced order HX models were constructed for a centrifugal chiller system and coupled to quasistatic models of a compressor and expansion valve to complete the reduced order VCC model. The reduced cycle model was implemented within the Modelicabased platform and used to predict loadchange transients over a wide range of operating conditions for comparison with measurements. The proposed reduced order modeling approach is computationally efficient and accurately captures cycle dynamics.

Vapor compression cycles would have many applications in the space industry if it was not for the uncertainty imposed by microgravity environments on two-phase systems. A first step towards Zero-G for technologies involving fluid dynamics can be terrestrial testing at different orientations. For vapor compression cycles, there is very little literature describing this type of research. This paper describes the anomalies encountered during the pursuit of a continuous operation of a R134a vapor compression cycle while positioning it at fixed angles around one axis between 0 and 360°. Experimental data was collected on a dedicated test stand across two configurations, one using a flat-plate evaporator and the other configuration using a tube-in-tube evaporator. Liquid flooding of the suction line was observed for both configurations but also continuous operation throughout a complete loop for certain cycle conditions. Charge migration towards the evaporator when it was put at the bottom was calculated based on differing measurements of the two mass flow meters in the liquid and suction line.

Space cooling and heating equipment account for nearly 32% of the total residential electricity consumption in the U.S. In the residential space conditioning equipment market, air-conditioning and heat-pumping systems are prevalent, so even a slight improvement in these system efficiencies can have a significant impact on reducing the overall energy consumption. Over the years, the energy efficiency benchmarks established by the U.S. Department of Energy have been successful in encouraging manufacturers to develop higher efficiency equipment. These benchmarks are based on an energy efficiency standard, and these standards are based on a rating test procedure that forms the technical basis. Currently, in the U.S., AHRI 210/240 is the rating procedure for residential air-conditioning and heat-pumping equipment, which is based on a steady-state performance measurement method with a degradation coefficient to account for the cycling losses in part-load conditions. Although it provides a standard metric to compare different equipment performances, there has been a debate that this current methodology fails to appropriately characterize the performance of systems with variable-speed compressors and advanced control design. This is largely attributed to the steady-state nature of this current testing approach, which also involves overriding the equipment native control. In contrast to this, a load-based testing methodology has been developed in which the equipment responds to a simulated virtual building load, and the system dynamic performance is measured with its integrated controls. The load-based testing methodology is described in detail by Hjortland and Braun (2019), Patil et al. (2018), and Cheng et al. (2021), which forms the basis for CSA standard draft EXP07:2019 (CSA, 2019). In this paper, these two performance measurement methodologies, steady-state and dynamic load-based, are compared for application to a 5ton residential heat-pump system. The equipment performance was measured in cooling mode and the seasonal performance estimates based on the two testing approaches are compared. The differences in the two test methodologies' performance evaluation results are discussed with a causal analysis of the observed differences.

Buildings account for 39% of the CO2 emissions in the U.S. Although emerging building energy-efficient technologies lead to improved energy efficiency and lower environmental impact in the operational phase, not much attention has been paid to the environmental impact associated with the materials and manufacturing of the building mechanical systems. This paper presents an integrated life-cycle assessment method for buildings that accounts for the embodied and use phase carbon impacts of the building and its mechanical systems. The proposed methodology relies on EnergyPlus to generate the use-phase energy consumption for any given building. A material 'grabber' routine was developed to automatically extract building envelope material information from EnergyPlus models, which is then used for envelope embodied carbon analysis. For the mechanical equipment, embodied carbon accounting was performed for two representative air-conditioning and heat pump units: a 4-ton packaged unit and a 4-ton split heat pump. The different elements were incorporated in the overall life-cycle assessment tool along with lighting embodied data to allow generation of a whole building environmental performance report. Five Department of Energy commercial building prototypes were used as case studies and analysis results for seven U.S. climate locations are presented in this paper. The results show that for the investigated prototypical buildings, the use phase energy consumption has a dominant impact on the overall building environmental performance: the embodied carbon contribution is less than 9% for all considered cases. However, the tradeoffs could change dramatically as the U.S. moves towards net-zero buildings and the tool presented in this paper could be used to consider these tradeoffs.

Vapor compression cycles (VCCs) are a promising technology for refrigeration needs on future space craft due to their generally high cooling COP. However, due to microgravity there lies a risk of liquid flooding the compressor during start-up. Thus, to better prepare VCCs for microgravity applications, it is significant to understand the dependence of two-phase refrigerant on gravity during start-up. In this work, liquid flooding is evaluated at the start-up of a VCC and a possibility for passive compressor protection is considered. The experimental setup has two configurations. In the first, two-phase phenomena can be observed in a transparent tube and different tube insertions can be tested for their effectiveness as a liquid flooding obstruction. In the second configuration, liquid flooding from a commercial evaporator can be evaluated for different charge levels. The results show a clear effect of tube insertions on liquid flooding in a straight tube and find the felt tube insertion to be most effective at impeding flow. The evaporator test results also present a strong correlation of liquid flooding parameters with the charge level and show only a small dependence on the orientation of the evaporator.

Real-time power supply and demand balances are critical to ensure stable power frequency and quality power services. However, the growing integration of renewable energy increasingly challenges the power infrastructure because most of the renewable resources, e.g., solar and wind energy, are intermittent and difficult to predict. To meet the stringent power frequency requirements, more fast reacting frequency regulation resources are being brought online among which grid-level batteries are the dominant ones. Although batteries can provide fast and high quality regulation services, they suffer from high initial cost, high environmental impact and round-trip efficiency loss. When providing fast frequency regulation services, battery life span could be significantly reduced, leading to even higher cost per unit of frequency regulation service. Buildings consume more than 73% of the electricity in the US, offering significant regulation reserves for the power grid. Variable-speed air-conditioning systems are taking an increasing share of the market due to the higher efficiency requirements imposed by federal agencies. In addition to efficiency benefits, variable-speed cooling/heating systems are also perfectly suited for providing ancillary services as these units can modulate their power continuously over a wide range. Compared to batteries, HVAC systems have several advantages when providing frequency regulation services: 1) in theory, they do not incur any round-trip efficiency loss; 2) the time response of an AC unit could be faster than a battery (especially compared to energy batteries with slower ramping rates and relatively larger capacities); 3) the existing regulation capacity of HVAC systems is huge and the implementation cost is much lower; 4) the environmental impact of using HVAC systems for regulation services is lower than for battery systems. This paper presents lab test results of a variable-speed heat pump for providing ancillary services. Regulation performances for both the traditional (slow) and dynamic (fast) regulation services are reported. The tested performance scores were above 0.97 and the regulation performance even beats the average battery regulation performance. Preliminary economic analysis was also performed using historical PJM prices. It was shown that the credit received for providing ancillary services could easily offset 50% of the HVAC energy cost under the tested conditions.

Combined Cooling, Heat and Power (CCHP) systems have great potential to recover low-grade thermal energy, resulting in higher energy efficiency, reduced emission rates, lower operating costs and a higher level of energy security. In order to fully realize the benefits of CCHP systems in terms of reduced cost and carbon dioxide emissions, effective optimization and control strategies are required. This work presents an approach for optimizing the operation of the CCHP system using a detailed network energy flow model solved by genetic algorithm. The optimal energy dispatch algorithm provides operational signals associated with resource allocation ensuring that the systems meet campus electricity, heating, and cooling demands. The performance of the system will be compared and evaluated with respect to economic and environmental benefits.

This paper presents the results of the evaluation of a control algorithm for minimizing energy costs in cooling plants with chilled water storage. The control approach requires very little plant information, is computationally simple, and is general in the sense that it is applicable to different types of utility rate structures including real-time pricing (RTP), time-of-use (TOU) and TOU with demand charges. The control algorithm was evaluated using a model of an existing chiller plant of significant complexity built in a simulation testbed for different combinations of storage sizes, load profiles and electricity rates. The performance of the near-optimal algorithm was compared with three different approaches: optimum control (baseline), and two heuristic control strategies commonly used for thermal energy storage. The energy costs obtained with the near-optimal control algorithm were within approximately 2% of the costs associated with optimal control. Comparison with the heuristic control strategies shows that significant energy savings can be achieved with the proposed control method.

The recent availability of variable electric energy and demand rates for residential buildings is providing incentives for the application of thermal storage for cooling that previously has been limited to commercial buildings. This is particularly relevant for hot climates where air-conditioning (A/C) use is the primary cause for peak electricity demand. Thermal storage allows consumers to store “cooling” when demand is low and minimize operation of the A/C during peak periods. From an economic perspective, the use of storage can significantly reduce operating costs depending on the utility rate incentives. In addition, storage can lead to a reduction in the installed cost of the primary cooling equipment because of a reduction in the peak equipment cooling requirement. However, this reduced equipment cost is counteracted by the additional costs required for storage and a secondary loop. This paper considers the overall economics associated with a packaged A/C integrated with ice energy storage for residential cooling applications. The evaluation was performed using a model of the proposed system that estimates system performance and operating cost over a cooling season for different locations and utility rates and using a generalized control strategy presented in a companion paper. The proposed system is compared to a conventional spilt system A/C in terms of initial cost, operating cost, and economic payback. In addition, we investigate the trade-off between equipment cooling capacity and storage size to determine minimum payback period for each situation. The optimization results show that the systems with the shortest payback period have initial costs that are very similar to the baseline system. In addition, the payback periods are attractive in locations with favorable utility rates and long cooling seasons (i.e., hot climates).

Representing multi-zone building envelope systems with linear time invariant state-space forms provides a way of applying various advanced control methodologies for better design and control of buildings. For example, system properties such as time constant and frequency response of building envelopes can be easily investigated with the help of control toolkits such as Matlab/Simulink and a reduced-order model can be developed by applying a model order reduction technique, once a reliable LTI building representation is developed. However, in order to make the LTI representation approach useful for industry, an interfacing tool that automatically extracts building system information from input files of popular building energy simulation (BES) tools and constructs a physical thermal network from the data is needed. This paper presents a conceptual strategy to interpret object (class) of a building energy simulation software and a methodology to develop a high fidelity LTI thermal network model. A case study applying this approach is provided which utilizes a model-order reduction method that converts a BES building envelope model for a multi-zone building into a reduced-order LTI model (ROM). Comparisons of predicted building load profiles and computation times between the BES model and ROM are also provided.

This paper presents results of testing variable-speed heat pumps using a new load-based testing methodology that is described in a companion paper. The testing methodology involves emulating the response of a building’s sensible and latent loads to equipment controls by dynamically adjusting the temperature and humidity setpoints of the psychrometric chamber reconditioning system using a simple building model. The advantage of this approach over existing testing approaches specified in ratings standards is that it considers the interaction of the integrated controls with the equipment. As a result, it better captures the full range of part-load operation and the benefits of improved controls. This paper presents performance results for application of the automated load-based testing methodology to different variable-speed residential heat pump systems. In order to assess the benefits of load-based testing versus existing standards, tests were also conducted based on AHRI 210/240 and seasonal performance estimates are compared using data obtained with the two testing approaches.

Compared to other types of compressors, linear compressors have drawn much attention for this application due to low friction, low power losses and compactness. Very little work was found in the open literature related to the comprehensive dynamic compressor modeling of linear compressors coupled with mechanical and electrical sub-models. This paper presents a comprehensive and generalized simulation model that is used to simulate the dynamic performance of a linear compressor. The model is based on mass and energy balance equations applied to open control volumes. The overall model is composed of several sub-models that include a piston dynamic model, an electrical motor model, a valve dynamic model, and a heat transfer model. When integrated together with an overall energy flow model for the compressor, it is possible to predict piston vibration, temperatures, and pressures within the compressor as well as overall performance. The results of the compressor model are being validated using experimental data from a commercially available linear compressor used in domestic refrigerator/freezers. The predictions by the compressor model have been compared to the measured mass flow rate, motor power and overall efficiencies. The comparisons indicate that the simulation model accurately predicts the compressor performance and can be used to study the performance of this type of compressor. The model will be used to improve the compressor design via parametric studies and to identify key parameters affecting the system transients.

A comprehensive mechanistic model of an open-drive single-screw expander for waste heat recovery applications by means of an Organic Rankine Cycle (ORC) has been previously developed and validated by the authors. The model included sub-models of geometry, leakage flows, in-chamber heat transfer, simplified friction losses and a single-lumped temperature overall energy balance. Furthermore, a non-symmetric approach was also implemented to simulate the simultaneous expansion process occurring on both side of the central rotor. In this work, the mechanistic model has been extended to compute the loads on the starwheels bearings as well as the main rotor. Forces and moments analyses allowed integration of a more detailed friction loss analysis and identification of a thermal resistance network of the housing with multiple lumped temperatures. To the best of the author’s knowledge such a detailed integrated thermal model of a single-screw machine has not been reported in the available literature. The multi-lumped temperature overall energy balance (OEB) is validated with experimental data obtained from a dedicated ORC test stand. A comparison between single-lumped and multi-lumped temperature approaches on the performance predictions is provided along with a discussion about the losses distribution inside the machine.

Positive displacement compressors are critical components in today’s vapor compression refrigeration, air conditioning, and heat pumping applications and can also be applied as expanders in power generation systems, such as organic Rankine cycles (ORC). The simulation of such systems is essential to predict and optimize the performance behavior at full- and part-load conditions. To this end, comprehensive system models are built by including different sub-models corresponding to each cycle component (e.g., heat exchangers, compressor, linesets). In general, the higher the complexity of each sub-models utilized to capture the physics, the higher the computational time required to solve a simulation run. In this work, deep learning is utilized to obtain high-accuracy performance predictions of positive displacement machines. A fixed-speed two-phase injected and vapor injected scroll compressor for air-conditioning applications and an oil-free scroll expander for low-grade waste heat recovery by means of an ORC are considered as test cases. In particular, Artificial Neural Network (ANN)-based models have been developed for each of the machines and trained using experimental data collected at the Ray W. Herrick Laboratories. The results of the training and testing of the models are presented as well as a discussion of the reliability of such models for extrapolating performance. In addition, the ANN models are compared with conventional empirical and semi-empirical modeling approaches. The models have been implemented in the Python programming language by using the open-source Keras package.

Compared to other types of positive displacement compressors, linear compressors show many advantages due to low friction, low power losses and compactness. Relatively little information is available in the literature with respect to linear compressor performance comparisons between oil-lubricated and oil-free linear compressors. Currently, there are two commercial linear compressors available in the market that are used in residential refrigerator/freezers. One of them uses synthetic POE oil while the other is oil-free. Both compressors operate over a wide range of capacity modulation instead of switching on and off, which results in smaller temperature variations and smaller vibration. The oil-free compressor has a special surface coating and a single bearing lubricated by the refrigerant gas itself. This paper presents experimental comparisons between the oil-lubricated and oil-free linear compressors for a domestic refrigerator/freezer. A hot-gas bypass test stand is used for testing the two compressors. During all tests, the following compressor measurements were recorded: compressor mass flow rate, suction and discharge temperatures, suction and discharge pressures, intermediate pressure and temperature, and compressor power consumption. Using these measurements, the two compressors were characterized and compared in terms of dimensionless performance parameters.

The characterization of heating and cooling performance of HVAC&R equipment is required of all manufacturers for determining seasonal energy efficiency ratings. The current rating standards, e.g. AHRI Standard 210/240, CSA C656, determine seasonal energy efficiency (e.g., SEER) using a bin method along with data from steady-state tests at different operating conditions. These standards were originally developed for equipment with single or two-stage thermostat control, but have been incrementally updated to consider equipment with variable-speed compressors and fans. However, the equipment testing is performed using control overrides and doesn’t consider the interaction of the integrated controls with the equipment. As a result, the standard ratings don’t capture the full range of part-load operation and don’t necessarily reward manufacturers who have superior controllers. To address this issue, we have been working with the Canadian Standards Association (CSA) to develop and evaluate a load-based testing methodology for evaluating the seasonal performance of variable-capacity equipment. This new testing methodology could be applied to both variable-speed and staged equipment, enabling a more direct and fair comparison of their performance. The testing methodology involves emulating the response of a building’s sensible and latent loads to equipment controls by dynamically adjusting temperature and humidity setpoints of the psychrometric chamber reconditioning system. Convergence criteria have been developed to automate the overall testing methodology so that the equipment performance can be fully evaluated using short-term tests (e.g., 1 day). Ultimately, automated load-based testing could lead to a practical approach for capturing equipment performance models that could be used in energy simulation programs for determining more accurate and application specific performance ratings. This paper presents the overall methodology of load-based testing in addition to a discussion of some of the experimental results.

Maintenance strategies currently used for commercial building rooftop units (RTU) can be classified into two categories: reactive strategies and proactive strategies. In reactive strategies, maintenance and service is performed only when needed, e.g. when a system is unable to maintain setpoint. In proactive strategies, maintenance is scheduled at routine intervals to avoid service interruptions regardless of whether the system actually needs it. While these strategies could not be more different, it is unclear which strategy is more optimal. Moreover, whether one strategy is more optimal than the other more than likely depends on the application – contributing to much uncertainty. A third category of maintenance has been enabled by automated fault detection and diagnostics (AFDD) technologies that aims to provide building operators and service providers more detailed information about the actual state of equipment in the field. This third strategy, called condition-based maintenance, aims to optimize service and maintenance decisions throughout the life of equipment based on updated measurements of performance and service costs. In this work, these three types of maintenance strategies are compared using a commercial building simulation model utilizing a fault impact equipment model. Along with comparing different strategies under the same fault scenario, ambient conditions, and loads, optimal maintenance schedules are generated using dynamic programming. Benefits of a condition-based maintenance approach utilizing a suite of AFDD methodologies are highlighted with respect to reducing operating costs.

In the last two decades, great progress has been made in improving the efficiency of air-conditioning equipment. In addition to improved performance of new equipment, there has been an increasing interest in technologies that can maintain performance over time. This has led to research and development of Fault Detection and Diagnosis (FDD) techniques for air conditioning systems, that can support building owners in scheduling cost-effective maintenance and repairs. Among FDD techniques, thermoeconomic diagnosis is a novel method for the identification of faults occurring in air conditioning systems. A very limited number of papers have focused on this topic, and the methodology is still at a very early stage of development. Thermoeconomic diagnosis is an exergy-based method to quantify the additional energy consumption (or the EER penalty) associated with individual or combinations of faults. It has been initially tested for very simple vapor compression systems through simulation, but has never been evaluated using experimental data. This work aims to assess the performance of thermoeconomic diagnosis using experimental data obtained from a five-ton variable-speed packaged rooftop air conditioning unit (RTU). The RTU was tested in psychrometric chambers under a wide range of operating conditions and fault levels. Three faults that are commonly found in rooftop systems were investigated: (i) evaporator fouling, (ii) condenser fouling and (iii) refrigerant undercharge. The experimental results were used as inputs in an equipment model, to characterize the exergy behavior of each component in presence of faults and apply the approach of Symbolic Exergoeconomics. Experimental results show the technique had difficulty in detecting some faults and its performance is quite sensitive to operating conditions. Based on these results, improvements to the FDD methodology based on empirical models of plant components are proposed. These improvements act to isolate the effects of operating conditions from the thermoeconomic effects of different faults, improving overall performance.

To better characterize the performance of variable-speed DX (Direct Expansion) equipment in a laboratory environment, a load-based psychrometric chamber testing methodology has been developed as an alternative to existing steady-state testing approaches. The methodology allows equipment to respond dynamically to a virtual building model using its integrated controls. To mimic an actual building, a virtual building model incorporates sensible and latent loads along with simple lumped capacitance building dynamics that interact with the variable-speed equipment. The rated capacity of the test equipment is used along with a specified sizing factor and target sensible heat ratio (SHR) to specify the building sensible and latent load models. In addition, heuristic approaches are used to specify and scale sensible and latent capacitances of the virtual building model. Two companion papers present the overall methodology and results for different variable-speed heat pumps using default building parameters. This paper studies the impact of the virtual building load parameters on overall performance and dynamic behavior of the equipment for load-based testing. It is shown that equipment seasonal performance can increase significantly with increasing sizing factor. In addition, performance increases with decreasing building SHR results. In addition to simple lumped capacitance models, more detailed two-node models are investigated to evaluate more realistic dynamics and their impacts on seasonal efficiency ratings. In addition, the impact of the thermostat location on equipment dynamics and performance ratings is considered.

Passenger cars roughly represent 12% of the CO2 emissions in EU. Passenger car gasoline engines present large losses in thermal energy (roughly 60% in engine coolant and exhaust gases). This paper presents a new architecture of organic Rankine cycle using both sources of heat to decrease the emissions of the car with the cooling engine fluid as working fluid. It allows to decrease the cost, the complexity, environmental and safety issues. In this paper, the main losses of the system are taken into account: under and over-expansion of the expander, bypass flow, thermal power at the condenser limitation and exhaust gas exchanger pinch-point. Two working fluids are considered (mixture of water and ethanol and mixture of glycol and water). New improvements of the cooling engine loop of passenger cars allow to reach 20 bar and 200°C, which are used as constraints in the simulation. First, a parametric study emphasizes the main losses of the proposed architecture and how to minimize them by adjusting control variables (fraction of bypass flow and pressure). Following this, the performance is presented in function of the speed of the vehicle. The simulations show a high benefit in terms of fuel consumption for speeds higher than 75 km/h. Following this, the consumption improvements are analysed on two driving cycles and are compared with other classical architectures. The maximum consumption decrease on a WLTP cycle reaches 6% with an optimal control and a steady-state model. This theoretical investigation shows the potential of this new architecture and would require experimental investigations to validate the promising results.

It has been previously demonstrated that the most significant computational requirements for vapor compression system models are associated with evaluation of thermodynamic properties. This is particularly important for transient models because properties are evaluated at each time step and the overall model can often run less than real time. The typical approach for evaluating thermodynamic properties involves the use of complicated equations of state (EOS), such as utilized in standard software tools such as RefProp and CoolProp. Overall computation speed can be significantly enhanced using interpolation methods that are based on pre-calculated thermodynamic properties. This paper presents an improved interpolation method to quickly and accurately retrieve refrigerant properties based on the neural networks. Since the approach has an explicit functional form, it is able to avoid the computation time to find nearest points in the thermodynamic database. Comparisons between the proposed method and Refprop are provided for a wide range of pressure and enthalpy to show its accuracy. Then, performance comparisons between the proposed and conventional interpolation methods for a transient vapor compression cycle simulation are provided.

Electrochemical cells have been widely explored for their use in high efficiency energy systems. In this paper a novel heat pump cycle is proposed which utilizes chemical looping driven by electrochemical cells. Chemical looping is a method that has been applied to various applications such as combustion and air separation. It consists of the cycling of a substance between different chemical compositions in order to produce a desired effect. When the chemical composition of a fluid changes, various properties such as its saturation pressure will also change. In the proposed concept, the chemical looping of electrochemically active fluids was leveraged in order to generate a heat pumping effect. A number of electrochemically active liquid organic hydrogen carriers including alcohols such as cyclohexanol and isopropanol have been investigated for use in conjunction with electrochemical cells. These organic fluids were integrated into a thermodynamic model of the proposed cycle. When operating as an air conditioner the model indicated that an increase in cooling COP of over 20% could be achieved in comparison to a conventional vapor compression system using R410A.