Abstract
This article proposes a holistic codesign optimization framework (COF) to simultaneously optimize a power conversion stage and a controller stage using a dual-loop control scheme for multiphase SiC-based DC/DC converters. In this study, the power conversion stage adopts a non-isolated interleaved boost converter (IBC). Besides, the dual-loop control scheme uses type-III controllers for both inner- and outer- loops to regulate the output voltage of the IBC and tackle its non-minimum phase issue. Based on the converter architecture, a multi-objective optimization (MOO) problem including four objective functions (OFs) is properly formulated for the COF. To this end, total input current ripple, total weight of inductors and total power losses are selected as three OFs for the power conversion stage whilst one OF called integral of time-weighted absolute error is considered for the controller stage. The OFs are expressed in analytical forms. To solve the MOO problem, the COF utilizes a non-dominated sorted genetic algorithm (NSGA-II) in combination with an automatic decision-making algorithm to obtain the optimal design solution including the number of phases, switching frequency, inductor size, and the control parameters of type-III controllers. Furthermore, compared to the conventional ‘k-factor’ based controller, the optimal controller exhibits better dynamic responses in terms of undershoot/overshoot and settling time for the output voltage under load disturbances. Moreover, a liquid-cooled SiC-based converter is prototyped and its optimal controller is implemented digitally in dSPACE MicroLabBox. Finally, the experimental results with static and dynamic tests are presented to validate the outcomes of the proposed COF.
Highlights
In electric vehicle (EV) drivetrains, multiport converters (MPCs) consisting of multiple DC/DC converters have been widely adopted to manage power between different energy sources (i.e., battery, fuel cell (FC) and supercapacitor (SC)) [1]
As this paper focuses on high power converter applications, only critical and major losses will be considered for the loss model of semiconductors
The optimization process based on the NSGA-II and the average ranking (AR) entails the selection of number of phases, switching frequency, inductor sizing, and control parameters of type-III
Summary
In electric vehicle (EV) drivetrains, multiport converters (MPCs) consisting of multiple DC/DC converters have been widely adopted to manage power between different energy sources (i.e., battery, fuel cell (FC) and supercapacitor (SC)) [1]. High reliability and high power-density converters are normally required in EV applications. To this end, wide bandgap technology such as silicon carbide (SiC) MOSFETs have recently been used to replace traditional silicon (Si) IGBTs, which leads to an overall reduction of 30% for the total converter volume [3]. Energies 2020, 13, 5167 leads to an overall reduction of 30% for the total converter volume [3]. By applying a multiphase concept along with interleaving operation and current sharing control techniques for the concept converter, along withitsinterleaving operation andthe current control techniques the DC/DC
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