Efficiency Optimization of IPOP DC/DC System for HEV

Input parallel output parallel (IPOP) DC/DC system is widely utilized in many occasions like data center and hybrid electric vehicle (HEV). However, the efficiency characteristics of different converters usually differs from each other, and the conventional control strategy has difficult to realize...

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Veröffentlicht in:IEEE access 2021, Vol.9, p.31553-31561
Hauptverfasser: Lu, Fengwang, He, Liangzong, Tan, Qingyang, Zhou, Hongyan
Format: Artikel
Sprache:eng
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Zusammenfassung:Input parallel output parallel (IPOP) DC/DC system is widely utilized in many occasions like data center and hybrid electric vehicle (HEV). However, the efficiency characteristics of different converters usually differs from each other, and the conventional control strategy has difficult to realize efficient conversion of overall power of the system. To address this issue, Buck converter is taken as the module and whose efficiency model under current continuous conduction mode (CCM) is presented. Meantime, parameter identification method based on least square (LS) algorithm is proposed as well. In order to realize the efficiency optimization of the whole parallel system, the constraint conditions of each module are analyzed, and the current distribution calculation method based on sequential quadratic programming (SQP) algorithm for the parallel system is introduced. On this basis, a control strategy of proportional current distribution (PCD) is proposed, which not only ensures that the parallel system can always run as efficiently as possible under different loads, but also realizes the flexible switching between the current-sharing mode and current distribution mode. Finally, the simulation and experimental results prove that the proposed method can achieve 4.46% higher efficiency than conventional method within the given power range of each converter, and realize the efficiency optimization of the IPOP DC/DC system to the greatest extent.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2021.3060018