Engineers Optimise Motors and Generators Using Multiphysics Modelling | ANSYS Blog
June 13th, 2019
The wide range of power generation applications requires engineers to optimise each motor and generator for its intended function. For instance, a cruise ship generator must be relatively quiet so passengers aren’t disturbed. Whereas, a generator in a remote village must be optimized for efficiency to reduce fuel consumption and maintenance costs.
Optimising these generators for their intended application requires the use of multiphysics modelling to capture various phenomena. For example, both electrical and mechanical resistance will create heat that can stress apart. At the same time, fans or other cooling systems will dissipate this heat. Capturing this heat flow is an inherent multiphysics problem.
Therefore, to optimise it’s motor and generator designs, Marelli Motori couples structural, electromechanical and computational fluid dynamics (CFD) simulations within multiphysics models.
How Marelli Motori Sets Up Multiphysics Models of Motors and Generators
Marelli Motori models motors and generators using several types of physics simulations linked within the ANSYS Workbench platform.
ANSYS Mechanical is used to optimise the strength-to-weight ratio of Marelli Motori’s generator and motor components. To simulate fans and heat exchangers within these, Marelli Motori uses ANSYS CFX. The multiphysics first comes into play when the motor’s electromagnetics produce heat, vibrations and magnetic fields that affect these structural and fluids simulations. Marelli Motori links ANSYS Maxwell to Mechanical to reduce the vibrations and magnetic forces on the system. Next, its engineers link Maxwell to CFX to identify hotspots in the coils so they can optimise the system’s heat exchangers and fans.
Though these multiphysics simulations are accurate and efficient, Marelli Motori is always exploring ways to speed up its optimisation process early in development. With its adoption of ANSYS Discovery Live, the company has made great gains in this direction.
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This blog was originally posted on ANSYS’ website here.