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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