Optimising flywheel energy storage systems for enhanced windage loss reduction and heat transfer: A computational fluid dynamics and ANOVA-based approach

Abstract

Concerns about global warming and the need to reduce carbon emissions have prompted the creation of novel energy recovery systems. Continuous braking results in significant energy loss during urban driving. Flywheel energy storage systems (FESS) can recover and store vehicle kinetic energy during deceleration. In this work, Computational Fluid Dynamics (CFD) simulations have been carried out using the Analysis of Variance (ANOVA) technique to determine the effects of design parameters on flywheel windage losses and heat transfer characteristics. The influence of five parameters was studied: flywheel operating speed, radial airgap size, axial airgap size, rotor surface roughness and housing surface roughness. Two models were developed to assess the significance and effects of the studied parameters on windage losses and Nusselt number to determine the most optimal conditions. The significance and dependency of these parameters are investigated using the ANOVA technique. The ANOVA interaction analysis showed that all the studied parameters interact significantly. The results indicate that optimising the radial and axial airgap sizes led to a significant 19 % reduction in windage losses, while increasing the radial airgap significantly enhanced the Nusselt number by 33 %, thereby improving convective heat transfer. The study also found that increasing rotor and housing surface roughness improved heat dissipation, as observed by up to a 2.7 % increase in the Nusselt number. It was concluded that optimal configurations of radial radius ratio and axial radius ratio, in combination with targeted surface roughness, can lower rotor surface temperatures, reducing energy loss from frictional heating and enhancing the system’s energy efficiency. The findings of this study can be used to develop guidelines for the design optimisation of FESS.