Jesús Alberto Moctezuma-Hernández

Thermal regulation of lithium-ion (Li-ion) battery modules is a critical constraint for electric vehicle (EV) safety and durability, particularly during high-C-rate operation. Phase change materials (PCMs) have emerged as promising passive solutions due to their latent heat storage capability; however, current literature is heavily biased toward organic paraffin-based systems and lacks structured benchmarking across PCM categories and integration architectures. This review provides a systematic comparative assessment of PCM-based battery thermal management systems (BTMSs) comprising organic, inorganic, and eutectic materials under EV-relevant discharge conditions. The review is structured according to the conventional classification of PCMs; however, the available literature is predominantly focused on organic materials, particularly paraffin-based PCMs, leading to greater depth of analysis for this category. Thermophysical properties are analyzed in conjunction with discharge rate, module configuration, and hybrid cooling strategies. The results indicate that peak temperature mitigation is weakly correlated with latent heat magnitude when thermal conductivity remains below critical values. Conductivity-enhanced composites incorporating expanded graphite or metal foams significantly improve heat diffusion, reducing hotspot intensity and inter-cell temperature gradients under medium-to-high C-rates. Pure passive PCM systems exhibit thermodynamic limitations during sustained high-power operation due to saturation effects, underscoring the need for hybrid architectures for continuous heat rejection. This work establishes a structured benchmarking framework and demonstrates that effective thermal conductivity, integration strategy, and discharge-dependent design dominate BTMS performance over latent heat alone. The findings also reveal that inorganic and eutectic PCM-based BTMSs remain comparatively less explored in the literature, particularly at the battery module level and under realistic electric vehicle operating conditions, highlighting opportunities for future research.

This study develops and optimizes a hybrid plant that couples a recompression sCO₂ Brayton cycle to a central-tower particle receiver with a bottoming Organic Rankine Cycle (ORC), including environmental and exergy balances. The two scenarios revealed Pareto points that raised the exergy efficiency to 0.65 in winter and reduced the fuel flow to 15 kg/s. Scenario number two achieves an overall thermal efficiency of 0.50 with total daily emissions of 2520 t CO₂ and 2850 kg NO_x, enabling nearly constant net power. Exergy destruction is concentrated in the high-temperature recuperator (HTR) and ORC turbines (27% each) and the ORC condenser (25%). Compared to a non-optimized baseline, the best solutions increased the ORC and Brayton efficiencies by 6.8–12.66% and 33.4–33.5%, respectively; cut gas-turbine power by 34% and ORC power to 10%; and lowered daily CO₂ and NO_x emissions by 52%. The gains stem from the coordinated adjustments of key levers: lower gas-turbine inlet temperature (about 10%), reduced Brayton mass flow (23%), and tuned ORC turbine inlet pressure.

This study presents a comprehensive thermodynamic model and energetic analysis of a hybrid Concentrated Solar Power (CSP) system incorporating a supercritical carbon dioxide (sCO2) Brayton cycle and an Organic Rankine Cycle (ORC). The CSP system uses a central tower receiver with a fluidized bed of silicon carbide particles and air as the heat transfer medium. Operating at a temperature of 650°C, the system demonstrates a heat transfer coefficient of 411 W/m2K. Key findings highlight the sensitivity of the convective coefficient to gas velocity and the effect of particle mass flow on receiver efficiency. Fuel mass flow reductions of up to 3.7% were achieved through particle mass flow adjustments, while variations in compression ratio and steam turbine inlet temperature affected overall cycle performance and efficiency. The study highlights the potential of such integrated systems to improve thermal efficiency, although further optimization is needed to balance fuel consumption and environmental impact.

Parabolic dish collectors (PDCs) focus solar radiation onto a small area, minimizing the heat-loss area of the solar receiver and improving the heating of the working fluid. This fluid usually drives a Stirling-like or micro-gas turbine (Brayton-like) power generator. PDCs, initially intended for small-capacity applications, are well-suited for electricity and heat generation in remote rural areas, working alone and/or as parabolic dish arrays. PDCs have received considerable attention among solar thermal collectors due to their high concentration ratios and the high temperatures they achieve. However, nowadays, they are the least developed and least commissioned among concentrated solar power configurations, lacking a well-established technology. This review aims to compile the evolution of research on PDCs over recent years from a global perspective and is mainly focused on the subsystems constituting a PDC plant, their integration, and overall system optimisation, thereby addressing a gap in the current literature. Methodological tools used in the field are comprehensively revised, and recent related projects are summarized. Some innovative and promising applications are also highlighted.

In this study, the development of a physical model for a miniature refrigeration system is presented. The model is based on physical foundations and the incorporation of information provided in the manufacturers’ catalogs. The model is able to adequately predict the energy behavior of the refrigeration system, showing a maximum error of 10% in comparison with the experimental information found in the literature. Thus, the model is used to perform a multi-objective optimization by comparing two algorithms, nondominated storing genetic algorithm II and multi-objective particle swarm optimization algorithm. For this purpose, three scenarios are proposed whose objective functions involve parameters such as coefficient of performance, compressor discharge temperature, energy consumption, and refrigerant mass flowrate. The decision variables are the evaporation and condensation temperatures, the rotational speed of the compressor, and the degrees of subcooling and superheating. Thus, an overview of the optimal operating conditions that represent the best energy performance of the refrigeration system is provided.