The book chapter shows that a `good' model is one which only needs a small amount of reference experimental input magnetisation data and can predict accurately over a wide magnetisation range. It could be argued that, for many applications, it is not necessary for the model to be based on physical processes as long as it can be used effectively to predict the loss of a steel to a sufficient accuracy. The chapter summarises some approaches to loss modelling and shows that they each have their own virtues which can be assessed in terms of speed, complexity, wide applicability and accuracy. Loss separation approaches and hysteresis models are incorporated into some commercial computational electromagnetic software used for electrical machine performance predictions.

Chapter Contents:

• 4.1 Introduction
• 4.2 Hysteresis modelling
• 4.2.1 Preisach models
• 4.2.2 Jiles–Atherton Model
• 4.3 Micro-magnetic approaches to loss prediction
• 4.4 Loss separation methods
• 4.5 Loss prediction under arbitrary flux density waveforms
• 4.6 Statistical theory of losses (STL)
• 4.7 Other approaches to loss prediction
• 4.8 An anecdotal historic perspective
• References

Inspec keywords: ferromagnetic materials; magnetic leakage; silicon alloys; magnetic hysteresis; computer simulation; magnetisation; iron alloys

Other keywords: loss prediction; loss modelling; loss separation approaches; FeSi; computational electromagnetic software; hysteresis models; magnetisation; electrical steels

Subjects: Ferromagnetism of Fe and its alloys; Magnetization curves, hysteresis, Barkhausen and related effects; Numerical simulation studies of magnetic materials; Ferromagnetic materials