Surrogate-based optimization of coupled inductors

Purpose The purpose of this paper is to present an application-specific optimization methodology for the design of coupled inductors used in multilevel interleaved power converters. This study focuses on minimizing core losses to meet power density requirements, reducing component volume to address cost constraints and maximizing longitudinal inductance to enhance electromagnetic interference (EMI) performance. Design/methodology/approach A multiobjective optimization (MOO) approach based on the NSGA-II algorithm is used to determine the Pareto-optimal design of the coupled inductor that satisfies the target power rating of 120 kW while minimizing volume for improved cost-effectiveness. The optimization incorporates key functional parameters, including main inductance, core losses and coil leakage inductance, the latter serving as an element for EMI filtering. To efficiently address the MOO problem, analytical models of the main inductance and core losses are integrated with a surrogate model of the device under test leakage inductance, derived from 2.5D finite element simulations. Findings Three Pareto-optimal designs are evaluated against a commercial reference in terms of core losses, inductance and cost. The low-loss design minimizes losses but requires a core twice as large as the reference, increasing cost by 60%. The compact design cuts material use by an order of magnitude but leads to substantially higher losses. The high-inductance design more than doubles inductance yet demands the largest core, raising cost by 70%. These results highlight a clear trade-off between magnetic efficiency, inductive performance and cost-effectiveness. Research limitations/implications This study is limited by practical factors affecting manufacturability and performance. The proposed designs require complex multilayer windings that increase leakage inductance, parasitics and fabrication difficulty. Winding capacitance and thermal effects are not modeled, though both significantly impact high-frequency and high-loss operation. Assumed filling factors may not reflect real winding technologies, affecting packing density and losses. Moreover, the smallest-volume designs may demand extra cooling, reducing practical benefits. Future work should include detailed winding models, parasitic capacitance and coupled thermal–electromagnetic analysis to better capture real-world performance and reliability. Practical implications The proposed methodology provides a quantitative framework to support informed trade-off decisions between key functional parameters – such as loss efficiency, inductance and space utilization – while also addressing EMI-related aspects and ensuring economic competitiveness. Originality/value The novelty of this work lies in its integrated optimization workflow for coupled inductor design, which simultaneously accounts for key functional parameters – such as efficiency, inductance and space utilization – while incorporating EMI-related factors and cost considerations within a unified framework.