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This paper presents the development of a transient thermal model of the EVO Electric AFM 140 Axial Flux Permanent Magnet (AFPM) machine based on a hybrid finite difference and lumped parameter method. A maximum deviation between simulated and measured temperature of 2.4°C is recorded after using a Monte Carlo simulation to optimise model parameters representing a 53% reduction in temperature deviation. The simulated temperature deviations are lower than the measurement error on average and the thermal model is computationally simple to solve. It is thus suitable for transient temperature prediction and can be integrated with the system control loop for feed forward temperature prediction to achieve active thermal management of the system.

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