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Digital Implementation of Optimal Phase Calculation for Buck-Boost LLC Converters
Qinsong Qian,Bowen Ren,Qi Liu,Chengwang Zhan,Weifeng Sun 전력전자학회 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.6
Buck-Boost LLC (BBLLC) converters based on a PWM + phase control strategy are good candidates for high efficiency, high power density and wide input range applications. Nevertheless, they suffer from large computational complexity when it comes to calculating the optimal phase for ZVS of all the switches. In this paper, a method is proposed for a microcontroller unit (MCU) to calculate the optimal phase quickly and accurately. Firstly, a 2-D lookup table of the phase is established with an index of the input voltage and output current. Then, a bilinear interpolation method is applied to improve the accuracy. Meanwhile, simplification of the phase equation is presented to reduce the computational complexity. When compared with conventional curve-fitting and LUT methods, the proposed method makes the best tradeoff among the accuracy of the optimal phase, the computation time and the memory consumption of the MCU. Finally, A 350V-420V input, 24V/30A output experimental prototype is built to verify the proposed method. The efficiency can be improved by 1% when compared with the LUT method, and the computation time can be reduced by 13.5% when compared with the curve-fitting method.
An Accurate Small Signal Modeling and Control Loop Design of Active Clamp Flyback Converter
Shengyou Xu,Qinsong Qian,Bowen Ren,Qi Liu 전력전자학회 2019 ICPE(ISPE)논문집 Vol.2019 No.5
An accurate small signal model of active clamp flyback (ACF) converter is proposed in this paper. To obtain a precise model, the ESR of output capacitor was considered. Different to traditional flyback converter, because of the resonant effect, at the three to five times of switching frequency, ACF converter was added two poles which result in high oscillation in frequency responses curve. To get sufficient phase margin and avoid resonant inductor oscillation affect, a fundamental error compensator was given to keep control loop stabled. Then a 65W prototype was implemented to verify the performance of the designed control loop, the simulation and experimental results showed that the adjusted process between different load status haven’t result in much voltage overshoot or undershoot and need a long regulate time.
Digital Implementation of Optimal Phase Calculation for Buck-Boost LLC Converters
Qian, Qinsong,Ren, Bowen,Liu, Qi,Zhan, Chengwang,Sun, Weifeng The Korean Institute of Power Electronics 2019 JOURNAL OF POWER ELECTRONICS Vol.19 No.6
Buck-Boost LLC (BBLLC) converters based on a PWM + phase control strategy are good candidates for high efficiency, high power density and wide input range applications. Nevertheless, they suffer from large computational complexity when it comes to calculating the optimal phase for ZVS of all the switches. In this paper, a method is proposed for a microcontroller unit (MCU) to calculate the optimal phase quickly and accurately. Firstly, a 2-D lookup table of the phase is established with an index of the input voltage and output current. Then, a bilinear interpolation method is applied to improve the accuracy. Meanwhile, simplification of the phase equation is presented to reduce the computational complexity. When compared with conventional curve-fitting and LUT methods, the proposed method makes the best tradeoff among the accuracy of the optimal phase, the computation time and the memory consumption of the MCU. Finally, A 350V-420V input, 24V/30A output experimental prototype is built to verify the proposed method. The efficiency can be improved by 1% when compared with the LUT method, and the computation time can be reduced by 13.5% when compared with the curve-fitting method.
Development of smart machining system for optimizing feedrates to minimize machining time
Hong-seok Park,Bowen Qi,Duck-Viet Dang,Dae Yu Park 한국CDE학회 2018 Journal of computational design and engineering Vol.5 No.3
Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simula-tion, constraint-based optimization scheme was used to maximize the cutting force by calculating acceptable feedrate levels as the optimizing strategy. The intelligent algorithm was integrated into auton-omous machining system to modify NC program to accommodate these new feedrates values. The exper-iment using optimized NC file which generates by our smart machining system were conducted. The result showed autonomous machining system, was effectively reduced 26%.
( Yu Zou ),( Shengwen Qi ),( Songfeng Guo ),( Zhifa Zhan ),( Xiaolin Huang ),( Bowen Zheng ),( Ning Liang ),( Jiaguo Xia ),( Xingxing Li ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2
Strong earthquakes such as the 2008 Wenchuan earthquake often induced numerous landslides, which resulted in a large number of casualties and property losses. Under a strong earthquake, a rock slope often produced a dynamic progressive failure. Understanding the process of the dynamic progressive failure of the rock slope is of great significance for the prediction and prevention of the co-seismic landslide. Generally, the numerical method is a feasible and economic alternative to solve this problem. However, previous studies presumed the failure surface and area in the numerical model, which cannot reproduce the dynamic progressive failure of the rock slope. In this paper, we applied the Universal Discrete Element method (UDEC) was adopted to quantitatively characterize the dynamic progressive failure process of the Wangjiayan co-seismic landslide triggered by 2008 Wenchan earthquake. Different from previous studies, there exists no presumed failure surface and area was was presumed in the UDEC model. The initiation, coalescence of the local fractures and the formation of the final failure surface were well simulated in a real-time way. Some key factors influencing the dynamic progressive failure of the rock slope were systematically explored. This study provided a new insight to understand the disaster-pregnant mechanism, evolution, and formation of the co-seismic landslide.
Development of smart machining system for optimizing feedrates to minimize machining time
Park, Hong-seok,Qi, Bowen,Dang, Duck-Viet,Park, Dae Yu Society for Computational Design and Engineering 2018 Journal of computational design and engineering Vol.5 No.3
Feedrate optimization is an important aspect of getting shorter machining time and increase the potential of efficient machining. This paper presents an autonomous machining system and optimization strategies to predict and improve the performance of milling operations. The machining process was simulated and analyzed in virtual machining framework to extract cutter-workpiece engagement conditions. Cutting force along the cutting segmentation is evaluated based on the laws of mechanics of milling. In simulation, constraint-based optimization scheme was used to maximize the cutting force by calculating acceptable feedrate levels as the optimizing strategy. The intelligent algorithm was integrated into autonomous machining system to modify NC program to accommodate these new feedrates values. The experiment using optimized NC file which generates by our smart machining system were conducted. The result showed autonomous machining system, was effectively reduced 26%.
Digital twin-based smart monitoring and control system for double-sided grinding process
Hong Seok Park(박홍석),Saurabh Kumar(사우라브쿠마르),Bowen Qi(재박문) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
Digital twin gives an approach to manufacturers to gain a clearer picture of real-world performance and operating conditions of a manufacturing as-set via near real-time data captured from the asset and make proactive optimal operation decisions. Grinding is one of the most common precision machining methods because of its high machining efficiency and good finish quality. The presented paper relates to the digital twin based smart monitoring and control of the double sided grinding process. The mechanics, mechanical and electrical behavior of the process is described in detail. By collecting the current value of the motor in real time, the grinding force is calculated in real time along the force flow. Monitoring system displays the signals coming from the digital twin and smart control algorithm optimizes the process parameter accordingly. The digital twin system is 95 % accurate in terms of predicting the grinding force. The findings of this paper can surely give an advantage to the manufacturers in terms of process monitoring and control in case of quality failure detection.