Bearing currents and associated high frequency effects in permanent magnet machines - improved computational and experimental methods

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Electrical machines are becoming ever-more important in the transition to a zero-carbon society, particularly in the decarbonisation of transport. Their use in electric and hybrid vehicles is already accelerating rapidly with hybrid propulsion also on the horizon for future small and regional aircraft. Electrical machines are almost always used in conjunction with power electronic controllers which apply a high frequency voltage pulse train to the machine to control the current and hence the speed or torque. In combination, the machine and its associated controller provide an efficient and highly controllable drive-train solution. However, the high frequency switching produced by the controller is not without its drawbacks, one of the most problematic being that high frequency parasitic currents can flow through the machine bearings unless precautions are taken in design and installation. These parasitic and unintended currents in the bearings lead to deterioration of the lubrication film and surface damage to the rolling parts of the bearings. This bearing damage could in turn cause catastrophic and unexpected failure of the electrical machine in service. The various phenomena which result in bearing currents are complex and, in many cases, poorly understood and the precautions which are adopted at present are rudimentary and compromise other aspects of performance. The proposed research programme investigates the high frequency capacitive and inductive effects in permanent magnet machines with a particular focus on innovative modelling and measurement approaches for high frequency bearing currents. This will lay the cornerstone for bearing current mitigation through improved design and simulation, enhancing reliability and safety and hence promote further electrification of transport. This is of particular importance in hybrid aerospace propulsion systems where the highest levels of reliability based on robust and rigorous understanding of physical phenomena is essential for the adoption of new technology.