Abstract:Energy storage systems (ESS) provide a means for improving the efficiency of electrical systems when there are imbalances between supply and demand. Additionally, they are a key element for improving the stability and quality of electrical networks. They add flexibility into the electrical system by mitigating the supply intermittency, recently made worse by an increased penetration of renewable generation. One energy storage technology now arousing great interest is the flywheel energy storage systems (FESS), since this technology can offer many advantages as an energy storage solution over the alternatives. Flywheels have attributes of a high cycle life, long operational life, high round-trip efficiency, high power density, low environmental impact, and can store megajoule (MJ) levels of energy with no upper limit when configured in banks. This paper presents a critical review of FESS in regards to its main components and applications, an approach not captured in earlier reviews. Additionally, earlier reviews do not include the most recent literature in this fast-moving field. A description of the flywheel structure and its main components is provided, and different types of electric machines, power electronics converter topologies, and bearing systems for use in flywheel storage systems are discussed. The main applications of FESS are explained and commercially available flywheel prototypes for each application are described. The paper concludes with recommendations for future research.

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The steady and pulsating performance results of a turbocharger mixed-flow turbine are presented. The results are taken at an equivalent speed of 70% (42,000rpm) for a pulse frequency range of 20 to 80 Hz. All instantaneous parameters required for unsteady performance evaluation are measured and discussed. Significant improvements to the measurement of instantaneous actual power have been carried out. Large variations in the operating point of the turbine occur in each pulse cycle, a velocity ratio range of 0.43 to 1.28 is seen for a 20 Hz pulse, this range reduces as the pulse frequency increases and unsteady effects become more prominent. During periods of turbine freewheeling, negative efficiencies can arise due to momentum transfer from the turbine to the working gas, although detrimental to the efficiency the energy content in these regimes are low. The use of a modified Strouhal number (MSt.) and a pressure modified Strouhal number (PMSt.) has proved useful in assessing when the onset of unsteadiness of the flow will become significant, a value of 0.1 has been used as an appropriate limit to steadiness. The results suggest that for a typical engine speed range the rotor may be considered quasi-steady whilst the turbine stage is predominately operating in an unsteady regime. Inference from the experimental data would suggest it is adequate to capture the performance of a turbine under pulsating flow using a ‘quasi-steady’ model when the MSt. < 0.1, and a ‘filling and emptying’ code when a PMSt. < 0.1 and above this value a ‘wave action’ model is more appropriate.

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-Accurate thermal analysis of axial flux permanent magnet (AFPM) machines is crucial in predicting maximum power output. Stator convective heat transfer is one of the most important and least investigated heat transfer mechanisms and is the focus of this paper. Experimental measurements were undertaken using a thin-film electrical heating method, providing radially resolved steady state heat transfer data from an experimental rotor-stator system designed as a geometric mockup of a through-flow ventilated AFPM machine. The measurements are compared with computational fluid dynamics (CFD) simulations using both 2D axisymmetric and 3D models. These were found to give a conservative estimate of heat transfer, with inaccuracies near the edge and in the transitional flow regime. Predicted stator heat transfer was found to be relatively insensitive to the choice of turbulence model used in the CFD simulations. Permanent repository link