According to the special section entitled `Robust design and analysis of electric machines and drives', to be published in IEEE Transactions on Energy Conversion, the authors present an introduction to tolerance analysis, robust optimization, and measures to improve the reliability of electric machines, power electronics and drives, and their robust control in general. A comprehensive review of modeling uncertainties and evaluating robustness and reliability based measures is presented. In addition, techniques facilitating solving dedicated optimization scenarios are introduced. The most recent research activities will be illustrated. The article thus enables to easily catch up with the state-of-the-art in these fields and to take notice of ongoing and future work.

This paper presents an effective methodology for robust optimization of electromagnetic devices. To achieve the goal, the method improves the robustness of the minimum of the objective function chosen as a design solution by minimizing the second-order sensitivity information, called a gradient index (GI) and defined by a function of gradients of performance functions with respect to uncertain variables. The constraint feasibility is also enhanced by adding a GI corresponding to the constraint value. The distinctive feature of the method is that it requires neither statistical information on design variables nor calculation of the performance reliability during the robust optimization process. The validity of the proposed method is tested with the TEAM Workshop Problem 22.