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CO2 (GWP = 1) is considered as a promising natural alternative refrigerant to HFC-134a in mobile air conditioning (MAC) applications. The objective of this study is to investigate the cooling performance characteristics of a CO2 MAC system. A prototype CO2 MAC system, consisting of a CO2 electrical compressor, CO2 parallel flow microchannel heat exchangers, and an electrical expansion valve, was developed and tested. Factor analysis experiments were conducted to reveal the effect of outdoor temperature on the cooling performance of this CO2 MAC system. Compared with a conventional R134a MAC system, the prototype CO2 MAC system achieved comparable cooling capacity, but had COP reductions of 26% and 10% at 27 °C and 45 °C outdoor conditions, respectively. In addition, based on refrigerant properties, theoretical cycle analysis was done to reveal the impact of evaporator, gas cooler and compressor, on the system cooling performance. It is concluded that the increase of overall compressor efficiency or the decrease of gas cooler approaching temperature could greatly improve the COP of this CO2 MAC system.

Machine learning (ML) approaches have admirable potential to forecast the performance of the mobile air-conditioning (MAC) system with low global warming potential R1234yf instead of conventional mathematical and simulation approaches. In this work, three different ML algorithms—artificial neural network (ANN), simple recurrent neural network (SRNN), and extreme gradient boosting (XGB)—have been employed for predicting the energy and exergy performance. Compressor speed, condenser-side air velocity/temperature, and evaporator-side air flow rate/temperature were considered as influencing input parameters. In energy analysis, performance indexes, namely refrigerant flow rate, cooling capacity, compressor power, and coefficient of performance (COP), were considered as output parameters, while total exergy destruction and exergy efficiency (η ex ) were accounted for as exergy metrics. First, the heat mapping method was used to rank the correlation among the input and output factors, and results revealed that compressor speed and evaporator-side air temperature are identified as the most and least influencing parameters on the forecast of energy and exergy performance metrics. Among the three models, the use of the XGB model showed excellent prediction efficiency on COP and η ex with root-mean-squared error of 0.0756 and 0.9786, respectively, while the corresponding correlation coefficients were 0.9749 and 0.9119. Predicting η ex using ANN and SRNN showed weak performance with a determination coefficient less than 0.70; moreover, prediction performance on energy indexes using ANN and SRNN models was good and almost identical. Overall, it is inferred that using XGB over ANN and SRNN can deliver superior prediction efficiency with enhanced reliability and can be employed as a forecasting platform for MACs under widespread working conditions.

In response to environmental concerns, R1234yf is used in mobile air conditioning (MAC) systems, yet it can produce trifluoroacetic acid (TFA) in water bodies, a persistent pollutant with moderate phytotoxicity and high mobility. However, R152a, an alternative, faces challenges due to its flammability (classified as A2). To address this, we propose new R152a-R13I1 mixtures (M10–M50) as R1234yf replacements in MAC units. A Simscape/MATLAB model was developed to elucidate the thermodynamic performance of an MAC unit. Theoretical estimations showed a significant reduction in burning velocity (BV) and an increase in the lower flammability limit (LFL) when R13I1 was added to R152a. For instance, at 0.20 mole fraction of R13I1, BV decreased from 23.1 to 11.3 cm s −1 ; while, LFL increased from 4.9 to 6.28 vol. %. Hence, M20 emerged as the optimal choice due to its A2L flammability classification and superior thermal properties. Simscape/MATLAB results revealed M20's 11.5–35.4% higher coefficient of performance compared to R1234yf. The model was validated against R1234yf data, showing 3.8–13.8% error. Additionally, M20's impact on MAC CO 2 emissions was evaluated, showing a potential 34.1% reduction compared to R1234yf. This highlights the environmental benefits of transitioning to R152a-R13I1 blends in MAC systems.

This study analyzes four alternative cycle configurations for the traditional vapor compression system used in conventional, hybrid, and electric vehicles, taking low-GWP alternatives for the substitution of R134a. These are cycle with an internal heat exchanger and thermostatic expansion valve (IHX + TEV); cycle with an internal heat exchanger and short tube (IHX + ST); cycle with an ejector (EC); and cycle with an ejector and internal heat exchanger (EC + IHX). Similarly, the energy, exergy, exergoeconomic, and environmental impact of these configurations were analyzed using synthetic refrigerants with a GWP of less than 150. The results indicate that, using the EC + IHX configuration, the COP for refrigerants R1234yf, R1234ze(E), R1243zf, and R516A is the highest, increasing by more than 20%. Using R1243zf in the EC configuration can reduce the total cost ratio compared to other refrigerants. On the other hand, the use of IHX cycle configurations with R444A and R445A decreases the exergy efficiency and increases the total cost ratio by up to 35% and 70%, respectively. Additionally, the Total Equivalent Warming Impact (TEWI) analysis showed reductions up to 20% for ejector cycle configurations using R1234ze(E), R1234yf, R1243zf, and R516A.

Over the last two decades, extensive research has consistently highlighted the significant potential of nano-based materials in revolutionizing refrigeration systems as efficient alternatives to traditional refrigerants. The integration of nanotechnology into refrigeration systems has demonstrated remarkable efficacy, particularly in enhancing thermal performance metrics for example coefficient of performance as well as reducing power consumption. By leveraging nanomaterials, especially nanorefrigerants derived from HFC-R134a, organic-refrigerants like isobutane R-600a and propane R290 as a base, significant improvements in system efficiency have been achieved across various thermal applications including heat pumps, heat pipes, multi-refrigerant systems, and climate control units. Recent advancements in literature underscore the profound impact of nanoparticle-infused lubricating oils and refrigerants on holistic enhancement approach not only to optimize the thermophysical properties but also tribological attributes, and heat transfer efficiency, to facilitate denser system designs, thereby minimizing energy consumption and compressor workload. The incorporation of nanomaterial, nanolubricants, and their composites (such as HNL/HNR) offers a multifaceted solution to bolster system efficiency and reliability, setting a new paradigm for next-generation refrigeration technologies. The current research article performed a thorough comparative study of nano-applications to various HVAC and R applications along with a new era series of nature-friendly refrigerants.

This paper investigates the results of a Second Law analysis applied to a mobile air conditioning system (MACs) integrated with an internal heat exchanger (IHX) by considering R152a, R1234yf and R1234ze as low global warming potential (GWP) refrigerants and establishing R134a as baseline. System simulation is performed considering the maximum value of entropy generated in the IHX. The maximum entropy production occurs at an effectiveness of 66% for both R152a and R134a, whereas for the cases of R1234yf and R1234ze occurs at 55%. Sub-cooling and superheating effects are evaluated for each one of the cases. It is also found that the sub-cooling effect shows the greatest impact on the cycle efficiency. The results also show the influence of isentropic efficiency on relative exergy destruction, resulting that the most affected components are the compressor and the condenser for all of the refrigerants studied herein. It is also found that the most efficient operation of the system resulted to be when using the R1234ze refrigerant.

This study focuses on developing and optimizing of a microchannel gas cooler model for evaluating the performance of a transcritical CO2 mobile air-conditioning system. A simulation model is developed with the aid of MATLAB R2022a. A segment-by-segment modeling approach is utilized by applying the effectiveness-NTU method. State-of-the-art heat transfer and pressure drop correlations are used to obtain air and refrigerant side heat transfer coefficients and friction factors. The developed model is validated through a wide range of available experimental data and is able to predict a gas cooler capacity and pressure drop within an acceptable range of accuracy. The average errors for a gas cooler capacity and pressure drop are 3.79% and 10.24%, respectively. Furthermore, a parametric optimization method is applied to obtain optimal microchannel heat exchanger dimensions, including the number of tubes, microchannel ports, and passes. Different combinations were selected within the practical range to obtain optimal dimensions while keeping the total core volume constant. The simultaneous effect of the number of tubes, the number of ports in each tube, and the number of passes is determined. The objective of the current optimization technique is to minimize the pressure drop for the specific design capacity under different operating conditions without changing the overall volume of the gas cooler. The average pressure drop reduction for the optimal geometry as compared with the baseline geometry under all operating conditions is about 15%. The results from this study can be used to select an optimal geometric design for the required design capacity with a minimal pressure drop without the need for expensive prototype development and testing.

A vapor compression cycle (VCC) with integrated thermoelectric (TE) modules to boost the heating capacity of the system in an energy-efficient way, especially for cold climate operation, is suggested in this paper. While a baseline heat pump (HP) cycle absorbs heat from a source through an evaporator, the proposed system utilizes TE modules as an intermediate (or third) stage of an otherwise two-stage vapor compression system with a vapor injection compressor. This increases the overall system efficiency and augments the system capacity through the high coefficient of performance (COP) of the TE for small temperature lift conditions. To demonstrate the concept, a prototype refrigerant-to-solid (TE) heat exchanger, consisting of TE modules and microchannel flat tubes, was designed and fabricated so that the whole system could realize an additional 1 kW of heating capacity compared with the baseline system. The TE heat exchanger was integrated into a residential HP unit that uses R-410A as a refrigerant, and the system was tested in a laboratory under the severe condition of −17.8°C, in order to investigate the capacity improvement and the overall COP. Finally, an application of this technique in an automotive heating, ventilating, and air-conditioning system with HFC134a working fluid has been studied for the purpose of providing supplemental heating for electric vehicles and hybrid electric vehicles by establishing a detailed simulation model of a HP system with the TE heat exchanger. Both the laboratory test and the calculation study show that a VCC with integrated TE modules has both reasonable efficiency and increased heating capacity.

Global warming poses serious global concerns, and the mobile air conditioning (MAC) industry must be promoted to reduce greenhouse gas emissions. In this paper, the development of the MAC system and components for new energy vehicles, low global warming potential (GWP) refrigerants, methods to control refrigerant leakage, and new energy-saving technologies in China are introduced.