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Dong Maolin,Tian Yufei,Wang Xin,Qian Jun 한국탄소학회 2023 Carbon Letters Vol.33 No.3
The rational evaluation of carbon-based conductive ink performance is critical to both industrial production and applications. Herein, a model to evaluate writing performance of conductive ink by line resistance was proposed by investigating possible relations among different parameters and establishing relevant model to estimate ink writing performance. Bulk conductive inks were prepared and characterized to provide samples for model. To improve the precision of model, the impact of external factors including writing speed and angle was studied. Nonlinear regression and back propagation artificial neural network were employed to estimate line resistance, and cross check validation was conducted to prove robustness and precision of model. Most importantly, the investigation will open up a new path for the exploration of other carbon-based handwritten electronic devices.
Luo, Haoze,Dong, Yufei,Li, Wuhua,He, Xiangning The Korean Institute of Power Electronics 2014 JOURNAL OF POWER ELECTRONICS Vol.14 No.6
A modular multilevel-clamped composited multilevel converter ($M-MC^2$) is proposed. $M-MC^2$ enables topology reconfiguration, power device reuse, and composited clamping. An advanced five-level converter ($5L-M-MC^2$) is derived from the concept of $M-MC^2$. $5L-M-MC^2$ integrates dual three-level T-type modules and one three-level neutral point clamped module. This converter can also integrate dual three-level T-type modules and one passive diode module by utilizing the device reuse scheme. The operation principle and SPWM modulation are discussed to highlight converter performance. The proposed $M-MC^2$ is comprehensively compared with state-of-the-art five-level converters. Finally, simulations and experimental results are presented to validate the effectiveness of the main contributions of this study.
Haoze Luo,Yufei Dong,Wuhua Li,Xiangning He 전력전자학회 2014 JOURNAL OF POWER ELECTRONICS Vol.14 No.6
A modular multilevel-clamped composited multilevel converter (M-MC²) is proposed. M-MC² enables topology reconfiguration, power device reuse, and composited clamping. An advanced five-level converter (5L-M-MC²) is derived from the concept of M-MC². 5L-M-MC² integrates dual three-level T-type modules and one three-level neutral point clamped module. This converter can also integrate dual three-level T-type modules and one passive diode module by utilizing the device reuse scheme. The operation principle and SPWM modulation are discussed to highlight converter performance. The proposed M-MC² is comprehensively compared with state-of-the-art five-level converters. Finally, simulations and experimental results are presented to validate the effectiveness of the main contributions of this study.
DRAG REDUCTION PREDICTION OF AHMED MODEL WITH TRAVELING WAVE BASED ON BP NEURAL NETWORK
Hu Xingjun Hu,Jinglong Zhang,Yufei Luo,Jingyu Wang,Pengzhan Ma,Wei Lan,Chunbo Dong 한국자동차공학회 2022 International journal of automotive technology Vol.23 No.5
In this paper, a traveling wave model is proposed to explore its influence on the aerodynamic drag of a Ahmed model, the experimental and numerical results of aerodynamic drag coefficient CD for the Ahmed model are in good agreement. Then by defining the aerodynamic benefit coefficient ΔCD as the evaluation index for the orthogonal experiment, range analysis is conducted to determine the influences of the amplitude A, wavelength λ and frequency ω of the wave and the vehicle speed u on ΔCD. After the analysis it can been found that λ has the least importance among these parameters, hence A, ω and u are used to construct the 105 samples for training the BP neural network to predict ΔCD, results show that ΔCD obtained from the neural network is significantly affected by the parameters of traveling wave. The prediction accuracy of the network is furtherly verified by another 15 samples which are also built on A, ω and u, and the corresponding data overlap rate of ΔCD is 96 %, so it can be concluded that the BP neural network constructed in this paper is accurate enough to predict ΔCD.