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Predictive charge control for LLC resonant converters
Siqiang Chen,Guiping Du,Yanxiong Lei,Tuhuan Li 전력전자학회 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.5
A predictive charge control method based on an LLC resonant converter is proposed in this paper. The input charge in each cycle is reflected in the change of the resonant capacitor voltage. The threshold is set to compare it with the resonant capacitor voltage to control the input charge. Based on an LLC discrete predictive model, the predictive charge control predicts the threshold of the resonant capacitor voltage to regulate the output voltage. When compared with existing control methods, the predictive charge control has the advantages of an intuitive concept, a strong robustness, a simple implementation, and a simple model. It has excellent dynamic performance under various working conditions. The resonant tank can enter the steady state within one cycle without affecting the steady-state performance of the system. Through a mode analysis, this paper analyzes the proposed predictive charge control in detail. A 500 W LLC resonant converter prototype is built to verify the proposed method. Results show that both the output voltage and the resonant tank return to the steady state without fluctuations in one cycle during the processes of input voltage change and load switching.
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Lee, Jun-Seok,Baldridge, Anthony,Feng, Suihan,SiQiang, Yang,Kim, Yun Kyung,Tolbert, Laren M.,Chang, Young-Tae American Chemical Society 2011 ACS combinatorial science Vol.13 No.1
<P>Using a fluorescence response profile, a systematic examination was performed for synthetic chromophores of the green fluorescent protein (GFP) to discover new small molecule sensors. A group of 41 benzylideneimidazolinone compounds (<B>BDI</B>) was prepared and screened toward 94 biologically relevant analytes to generate fluorescence response profiles. From the response pattern, compounds containing aminobenzyl and heteroaromatic cyclic substructures revealed a pH dependent emission decrease effect, and unlike other fluorescence scaffolds, most <B>BDIs</B> showed fluorescence quenching when mixed with proteins. On the basis of the primary response profile, we obtained three selective fluorescence turn-on sensors for pH, human serum albumin (HSA), and total ribonucleic acid (RNA). Following analysis, a fluorescence response profile testing four nucleic acids revealed the alkyloxy (Ph−OR) functional group in the <I>para</I> position of benzyl analogues contributes to RNA selectivity. Among the primary hit compounds, <B>BDI 2</B> showed outstanding selectivity toward total RNA with 5-fold emission enhancement. Finally, <B>BDI 24</B> showed selective fluorescence increase to HSA (<I>K</I><SUB>d</SUB> = 3.57 μM) with a blue-shifted emission max wavelength (Δλ<SUB>em</SUB> = 15 nm). These examples of fluorescence sensor discovery by large-scale fluorescence response profiling demonstrate the general applicability of this approach and the usefulness of the response profiles.</P><P><B>Graphic Abstract</B> <IMG SRC='http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/acsccc/2011/acsccc.2011.13.issue-1/co100012k/production/images/medium/co-2010-00012k_0007.gif'></P><P><A href='http://pubs.acs.org/doi/suppl/10.1021/co100012k'>ACS Electronic Supporting Info</A></P>
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Tuhuan Li,Guiping Du,Yanxiong Lei,Siqiang Chen 전력전자학회 2022 JOURNAL OF POWER ELECTRONICS Vol.22 No.2
An open-end winding permanent magnet synchronous motor (OEW-PMSM) fed by dual inverters has good application value in the drive system of electric vehicles due to the motor’s advantages, such as high output power, wide speed range and excellent fault-tolerant ability. However, the symmetry of dual-inverter topology causes difficulty in identifying the specific faulty switch when an open-circuit fault occurs. Thus, this study proposes a switch open-circuit fault diagnosis strategy for OEW-PMSM based on finite-control-set model predictive control (FCS-MPC). With the known and unchanged switching state in each control period of FCS-MPC, the proposed strategy uses the predicted switching state to predict the phase voltage. According to the error of predicted voltage and measured voltage under switch failure, the faulty phase and faulty switch pair are identified. Finally, the relationship between switching states and error voltage is analyzed, and a diagnosis function is constructed to identify the specific faulty switch. The validity of the proposed diagnosis strategy is confirmed by the simulation and experimental results.
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