Numerical analysis of a flywheel energy storage system for low carbon powertrain applications

Shahed Motaman, Mahmoud Eltaweel, Mohammad Reza Herfatmanesh, Tobias Knichel, Andrew Deakin

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Flywheel energy storage has emerged as a viable energy storage technology in recent years due to its large instantaneous power and high energy density. Flywheel offers an onboard energy recovery and storage system which is durable, efficient, and environmentally friendly. The flywheel and the housing surface temperatures can be considerably influenced by the friction induced windage losses associated with non-vented airflows in the air-gap of a high-speed rotating flywheel. Many engineering applications have been interested in the features of radial and axial air-gap flows. The flow within the annulus of a flywheel is extremely complicated. This study has developed a numerical technique using ANSYS Fluent solver to model turbulent Taylor vortices formation and oscillation for thermal performance evaluation, and windage loss prediction of high-speed flywheel storage systems, operating under atmospheric and partial vacuum conditions. The numerical model has been experimentally validated with good accuracy. Several rotational speeds and pressures were investigated experimentally and numerically. The results demonstrated that a 40% reduction in the operating pressure can reduce the flywheel surface temperature and windage loss by 20% and 30%, respectively. Consequently, a partial vacuum environment can achieve better energy conversion efficiencies provided an appropriate bearing seal is achieved to maintain the pressure inside the housing. The investigated flywheel energy storage system can reduce the fuel consumption of an average light-duty vehicle in the UK by 22% and decrease CO2 emission by 390 kg annually.
Original languageEnglish
Article number106808
Pages (from-to)1-13
Number of pages13
JournalJournal of Energy Storage
Early online date11 Feb 2023
Publication statusPublished - 11 Feb 2023


  • Computational fluid dynamics
  • Model validation
  • Rotor skin friction coefficient
  • Taylor-Couette flow
  • Windage loss
  • Flywheel energy storage


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