Optimization of the Superconducting Linear Magnetic Bearing of a Maglev Vehicle

TL;DR

This paper develops a simplified 2D finite element model to optimize superconducting linear magnetic bearings in maglev vehicles, aiming to reduce costs or enhance performance while maintaining operational constraints.

Contribution

It introduces a combined 3D-2D modeling approach and stochastic optimization for maglev bearing design, improving cost-efficiency and performance prediction.

Findings

Bearing cost can be substantially reduced without performance loss.

Performance improvements are achievable at the same cost.

The optimized design maintains the minimum levitation force constraint.

Abstract

Considering the need for cost/performance prediction and optimization of superconducting maglev vehicles, we develop and validate here a 3D finite element model to simulate superconducting linear magnetic bearings. Then we reduce the 3D model to a 2D model in order to decrease the computing time. This allows us to perform in a reasonable time a stochastic optimization considering the superconductor properties and the vehicle operation. We look for the permanent magnet guideway geometry that minimizes the cost and maximizes the lateral force during a displacement sequence, with a constraint on the minimum levitation force. The displacement sequence reproduces a regular maglev vehicle operation with both vertical and lateral movements. For the sake of comparison, our reference is the SupraTrans prototype bearing. The results of the optimization suggest that the bearing cost could be substantially reduced, while keeping the same performances as the initial design. Alternatively, the performances could be significantly improved for the same original cost.