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A New Electric Machine Model and its Relevance for Vehicle Level Diagnosis

With the electrification of society, especially transportation, the control and supervision of electrical machines become more and more important due to its bearing on energy, environment, and safety. To optimise performance in control and supervision, appropriate modelling is crucial, and this regards both the ability to capture reality and the computational complexity to be useful in real-time. Here, a new low complexity model of the electric machine is proposed and developed. The new model treats the machine constants in a different way compared to a previous standard model, which results in a different expression for power losses. It is shown that this increases model expressiveness so when adapted to real data the result is significantly better. The significance of this modelling improvement is demonstrated using a task in vehicle diagnosis where it is shown that the separation between the non-faulty and faulty cases is better and the resulting performance is improved.

Christofer Sundström, Erik Frisk and Lars Nielsen

International Journal of Modeling, Identification and Control (IJMIC), 2015

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