When machines designers, researchers or technology leaders seek innovative designs that push the envelope of existing technology, there can be numerous in-depth analyses to perform, and many costly and time-consuming steps. Very small tweaks can have a substantial impact on the performance of the machine and for the most-part machines prototypes need to be built in order to validate every step in the design process. Without knowing very accurately the exact phenomena going on inside the machine, it is impossible to predict how a new design will perform.
Allowing the simulation of detailed fields inside an axial flux machine can expand the area covered by simulation in the design process, all the way from idea through the implementation of an optimized prototype. Following this process means drastically cutting down on the number of prototypes needing to be built and opening up the possibility to investigate thousands of possible variations.
The axial flux machine, despite it being in use since the beginning of electrical machine design, with both Faraday and Tesla developing axial flux prototypes, still remains a distant second choice to the radial flux machine. The use of the axial flux machine is mostly driven by a limited number of applications, where the volume available for the electrical motor or generator dictates the choice of the topology. For example, for in-wheel traction applications, the axial flux machine offers the best use of the available space. Similarly, for generation of renewable energy, like wind turbines, the axial flux machine can be employed in direct drive conditions, where the removal of the gear system can result in significant efficiency gains.
There are a number of reasons why the axial flux machine has not gained much ground when compared to the radial flux topology, from the inherently large axial forces which require the use of stiff materials or sandwich topologies to difficulties relating to the winding shape. However, another big reason why the axial flux machine is less used is the complex modelling required to predict its capabilities. Before the advent of modern technology and 3d finite element analysis, it was extremely difficult to predict the complex 3d flux paths that occur in the axial machine.
Whereas the radial flux machine can be analysed, at least initially, using a 2d approximation and analytical models, for the axial flux machine there are very limited analytical methods that can be applied and they all rely on very strict representations of the flux tubes in the machine. Hence, generalizations are very difficult to make.
Using simulation software, the modelling process of these axial flux machines becomes fast enough to allow not only rapid analysis of their performance, but also design optimization. Hence, the process of evaluating and improving them is now much more accessible which will likely lead to a higher uptake of axial flux machine in future applications. With Opera’s interface, designers can build and define designs down to the most minute detail. Complex geometries can be built through the intuitive graphical interface. Models can also be imported from third-party CAD packages through a variety of formats. New features can then be added and the model can be solved using a powerful solver technology.
Conductors can be easily built, with multiple pre-defined shapes available. Any type of complex shape can be defined from the standard conductor library. Conductors can be included in the mesh and they can be connected to external circuits. Any type of drive circuit can be defined, with the help of active and passive circuit components, like switches, diodes or capacitors. Functional drive sources allow the excitation to be linked to the simulation time or the rotor position.
Scripts can greatly improve your productivity and ensure that the models are built, solved and post-processed in a reproducible way. Users can build their own library of parts which they can use to analyse variations of their devices. There is no need for learning to write a script from scratch. By simply copying commands that are issued when you build a model through the interface, users can easily automate model setup.
If you are confronted with a completely new design or tasked with obtaining that incremental efficiency gain in an existing design, simulation software can make this entire process much more efficient, productive and reliable.
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