TY - JOUR
T1 - Modeling and optimization of an integrated transformer for electric vehicle on-board charger applications
AU - Zou, Shenli
AU - Lu, Jiangheng
AU - Mallik, Ayan
AU - Khaligh, Alireza
N1 - Funding Information:
Manuscript received October 11, 2017; revised December 13, 2017; accepted February 3, 2018. Date of publication February 9, 2018; date of current version June 6, 2018. This work was supported by the National Science Foundation under Grant 1602012. (Corresponding author: Alireza Khaligh.) The authors are with the Maryland Power Electronics Laboratory, Department of Electrical and Computer Engineering, Institute for Systems Research, University of Maryland, College Park, MD 20742 USA (e-mail: khaligh@ece.umd.edu). Digital Object Identifier 10.1109/TTE.2018.2804328
Publisher Copyright:
© 2015 IEEE.
PY - 2018/6
Y1 - 2018/6
N2 - 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.
AB - 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.
KW - Finite-element analysis (FEA)
KW - integrated transformer
KW - loss model
KW - on-board charger
KW - optimization
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U2 - 10.1109/TTE.2018.2804328
DO - 10.1109/TTE.2018.2804328
M3 - Article
AN - SCOPUS:85048228806
SN - 2332-7782
VL - 4
SP - 355
EP - 363
JO - IEEE Transactions on Transportation Electrification
JF - IEEE Transactions on Transportation Electrification
IS - 2
ER -