Search

This paper explores the potential of thermal storage as an energy storage technology with cost advantages. The study uses numerical simulations to investigate the impact of adding porous material to the HTF side during solidification to improve the heat transfer effect of TES using AlSi 12 alloy as the phase-change material. The research also examines the effects of adding porous dielectric materials and increasing air velocity on the discharge temperature, discharge power, and discharge time of high-temperature phase-change energy storage systems. The study found that the temperature difference of the PCM (increased), solidification time (reduced more than 85%), the outlet temperature of the air, and heat discharge power of the LHS did not vary significantly across different porous materials (copper foam, nickel foam, and silicon carbide foam) added to the HTF tube. These findings offer important information for the design of high-temperature phase-change energy storage devices and can guide future developments in this field. [ABSTRACT FROM AUTHOR]

In this study, the effect of nanoparticle concentration was tested for both CuO and TiO2 in eutectic mixture of sodium and potassium nitrate. Results showed an enhancement in specific heat capacity (Cp) for both types of nanoparticles (+10.48% at 440 °C for 0.1 wt % CuO and +4.95% at 440 °C for 0.5 wt % TiO2) but the behavior toward a rise in concentration was different with CuO displaying its highest enhancement at the lowest concentration whilst TiO2 showed no concentration dependence for three of the four different concentrations tested. The production of cluster of nanoparticles was visible in CuO but not in TiO2. This formation of nanostructure in molten salt might promote the enhancement in Cp. However, the size and shape of these structures will most likely impact the energy density of the molten salt. [ABSTRACT FROM AUTHOR]

This paper is focused on the characterisation and demonstration of Newtonian behaviour of salt at both high and low shear rate for sodium and potassium nitrate eutectic mixture (60/40) ranging from 250 °C to 500 °C. Analysis of published and experimental data was carried out to correlate all the numbers into one meaningful 4th order polynomial equation. Addition of a low amount of copper oxide nanoparticles to the mixture increased viscosity of 5.0%-18.0% compared to the latter equation. [ABSTRACT FROM AUTHOR]

Phase change dispersions are useful for isothermal cooling applications. As a result of the phase changes that occur in PCDs, they are expected to have greater storage capacities than those of single-phase heat transfer fluids. However, for appropriate heat exchanger dimensions and geometries for use in phase change dispersions, knowledge about the convective heat transfer coefficients of phase change dispersions is necessary. A test unit for measuring the local heat transfer coefficients and Nusselt numbers of PCDs was created. The boundary condition of constant heat flux was chosen for testing, and the experimental heat transfer coefficients and Nusselt numbers for the investigated phase change dispersion were established. Different experimental parameters, such as the electrical wall heat input, Reynolds number, and mass flow rate, were varied during testing, and the results were compared to those of water tests. It was found that, due to the tendency of low-temperature increases in phase change dispersions, the driving temperature difference is greater than that of water. In addition, larger heat storage capacities were obtained for phase change dispersions than for water. Through this experimentation, it was acknowledged that future investigation into the optimised operating conditions must be performed. [ABSTRACT FROM AUTHOR]

A lithium-ion battery cell's electrochemical performance can be obtained through a series of standardized experiments, and the optimal operation and monitoring is performed when a model of the Li-ions is generated and adopted. With discrete-time parameter identification processes, the electrical circuit models (ECM) of the cells are derived. Over their wide range, the dual-polarization (DP) ECM is proposed to characterize two prismatic cells with different anode electrodes. In most of the studies on battery modeling, attention is paid to the accuracy comparison of the various ECMs, usually for a certain Li-ion, whereas the parameter identification methods of the ECMs are rarely compared. Hence in this work, three different approaches are performed for a certain temperature throughout the whole SoC range of the cells for two different load profiles, suitable for light- and heavy-duty electromotive applications. Analytical equations, least-square-based methods, and heuristic algorithms used for model parameterization are compared in terms of voltage accuracy, robustness, and computational time. The influence of the ECMs' parameter variation on the voltage root mean square error (RMSE) is assessed as well with impedance spectroscopy in terms of Ohmic, internal, and total resistance comparisons. Li-ion cells are thoroughly electrically characterized and the following conclusions are drawn: (1) All methods are suitable for the modeling, giving a good agreement with the experimental data with less than 3% max voltage relative error and 30 mV RMSE in most cases. (2) Particle swarm optimization (PSO) method is the best trade-off in terms of computational time, accuracy, and robustness. (3) Genetic algorithm (GA) lack of computational time compared to PSO and LS (4) The internal resistance behavior, investigated for the PSO, showed a positive correlation to the voltage error, depending on the chemistry and loading profile. [ABSTRACT FROM AUTHOR]