This paper proposes a systematic approach to model and optimize an integrated transformer for on-board chargers in electric vehicles. The proposed approach includes a comprehensive transformer loss model with accurate electromagnetic description of leakage inductance and optimization process. The multiobjective optimization using genetic algorithm is presented to optimize the performance-space variables, i.e., volume, weight, and losses, by appropriate selections of design-space parameters, i.e., winding specifications and core candidacies. Four sets of integrated transformers are optimally designed and compared in terms of the theoretical analyses; finite-element analyses and experimental performance. As verification to the proof-of-concept, the integrated transformers are implemented and tested on a 3.3-kW on-board charger prototype. It has been shown that the measured losses agree with the theoretical computation. The peak efficiency of CLLC stage with the optimal selection of transformer reaches 98.2%, achieving efficiency enhancement and temperature improvement in comparison to other feasible candidates.
No takes yet. Share an insight, caveat, or question.
Zou et al. (2018) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: