A novel approach for design optimisation of radial active magnetic bearing

The purpose of this research is to demonstrate the use of a new and highly efficient population-based algorithm, known as Heat Transfer Search (HTS), for optimisation of an active magnetic bearing (AMB) system. In this research paper, the HTS algorithm is employed to minimise the overall bearing volume, considering turns per pole pair, the maximum required current, pole width, and coil length as the design variables. Constraints are imposed on the maximum flux density, current density, winding space, and maximum magneto-motive force. It is found that, for the operating conditions considered herein, the Heat Transfer Search algorithm yields around 23% lower bearing volume as compared to that obtained using more popular optimisation techniques such as Genetic Algorithms (GA) and Pattern Search (PS). Finally, a comparative study on the impact of magnetic core material presented herein reveals that Supermendur yields the best results. This is the first attempt to integrate the impact of magnetic core material on the optimisation of the AMB system.