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- 저자 : Guangliang Ma (검색결과 3 건)
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Analysis of the performances of the CFD schemes used for coupling computation
Chen, Guangliang,Jiang, Hongwei,Kang, Huilun,Ma, Rui,Li, Lei,Yu, Yang,Li, Xiaochang Korean Nuclear Society 2021 Nuclear Engineering and Technology Vol.53 No.7
In this paper, the coupling of fine-mesh computational fluid dynamics (CFD) thermal-hydraulics (TH) code and neutronics code is achieved using the Ansys Fluent User Defined Function (UDF) for code development, including parallel meshing mapping, data computation, and data transfer. Also, some CFD schemes are designed for mesh mapping and data transfer to guarantee physical conservation in the coupling computation. Because there is no rigorous research that gives robust guidance on the various CFD schemes that must be obtained before the fine-mesh coupling computation, this work presents a quantitative analysis of the CFD meshing and mapping schemes to improve the accuracy of the value and location of key physical prediction. Furthermore, the effect of the sub-pin scale coupling computation is also studied. It is observed that even the pin-resolved coupling computation can also create a large deviation in the maximum value and spatial locations, which also proves the significance of the research on mesh mapping and data transfer for CFD code in a coupling computation.
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Wang, Bin,Wang, Chaohui,Hu, Qiao,Ma, Guangliang,Zhou, Jiahui The Korean Institute of Power Electronics 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.2
This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.
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Bin Wang,Chaohui Wang,Qiao Hu,Guangliang Ma,Jiahui Zhou 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.2
This paper proposes an adaptive sliding mode control (ASMC) strategy with an enhanced optimal reaching law (EORL) for the robust current tracking control of the boost converter based hybrid power source (HPS) in an electric vehicle (EV). A conventional ASMC strategy based on state observers and the hysteresis control method is used to realize the current tracking control for the boost converter based HPS. Then a novel enhanced exponential reaching law is proposed to improve the ASMC. Moreover, an enhanced exponential reaching law is optimized by particle swarm optimization. Finally, the adaptive control factor is redesigned based on the EORL. Simulations and experiments are established to validate the ASMC strategy with the EORL. Results show that the ASMC strategy with the EORL has an excellent current tracking control effect for the boost converter based HPS. When compared with the conventional ASMC strategy, the convergence time of the ASMC strategy with the EORL can be effectively improved. In EV applications, the ASMC strategy with the EORL can achieve robust current tracking control of the boost converter based HPS. It can guarantee the active and stable power distribution for boost converter based HPS.
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