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RISS 인기검색어
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- 저자 : ( Ruchuan Wang ) (검색결과 3 건)
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Dual-Phase Shifting Strategy for CLLC Resonant Converters
Wang Dangshu,Zhao Licong,Chang Menghu,Yang Yuxuan,Guan Zhimin,Zhang Ruchuan,Wang Xinxia 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.4
The CLLC resonant converter has the advantages of bidirectional power transmission, natural soft switching, and wide range voltage output. However, the gain curve is relatively smooth during high-frequency light-load operation, and it is diffi cult to adjust through frequency conversion; the traditional fundamental harmonic approximation (FHA) method has a large error in calculating the gain at a position away from the resonance point, which brings diffi culties to the design. In order to better design the converter, this paper proposes a dual phase-shift (DPS) control method based on time-domain analysis, which can achieve a wide voltage range output without losing soft switching, and has constant current source output characteristics. Firstly, the time-domain model of the CLLC converter is analyzed, and the output voltage gain and soft switching range under DPS control are solved; then a simulation is built for verifi cation; fi nally, a 200/80 V, rated power 500 W full-bridge CLLC resonant converter experimental prototype is built. The experimental results prove that the converter has good soft switching range and constant current source output characteristics.
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Wang Dangshu,Liu Mingyao,Zhang Ruchuan,Yang Jiahao,Wang Jing 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.5
In order to address the issues of low effi ciency, large size, and low output power quality in the two-stage inverter power supply, this paper focuses on the series-resonant push–pull converter and conducts an in-depth analysis of its diff erent operating modes. Two critical operating modes of the converter are identifi ed, and optimal parameter designs for the resonant components under diff erent critical operating modes are derived through time-domain analysis. The reasons and consequences of the double-frequency ripple voltage on the two-stage circuit bus are analyzed, and a modulation wave reconstruction nonlinear feedforward control strategy is proposed to real-time correct the modulation signal and reduce the impact of bus ripple voltage on the output power quality. Finally, simulation models and experimental platforms are built to validate the correctness of the theory. The experimental prototype is designed to operate in the second critical mode, and the results show that the proposed scheme can enhance the peak effi ciency of the power supply by 5%, reduce the volume by 40%, and decrease the output voltage total harmonic distortion (THD) by 0.56%, eff ectively improving the effi ciency and output power quality of the inverter power supply.
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Vehicle trajectory prediction based on Hidden Markov Model
( Ning Ye ),( Yingya Zhang ),( Ruchuan Wang ),( Reza Malekian ) 한국인터넷정보학회 2016 KSII Transactions on Internet and Information Syst Vol.10 No.7
In Intelligent Transportation Systems (ITS), logistics distribution and mobile e-commerce, the real-time, accurate and reliable vehicle trajectory prediction has significant application value. Vehicle trajectory prediction can not only provide accurate location-based services, but also can monitor and predict traffic situation in advance, and then further recommend the optimal route for users. In this paper, firstly, we mine the double layers of hidden states of vehicle historical trajectories, and then determine the parameters of HMM (hidden Markov model) by historical data. Secondly, we adopt Viterbi algorithm to seek the double layers hidden states sequences corresponding to the just driven trajectory. Finally, we propose a new algorithm (DHMTP) for vehicle trajectory prediction based on the hidden Markov model of double layers hidden states, and predict the nearest neighbor unit of location information of the next k stages. The experimental results demonstrate that the prediction accuracy of the proposed algorithm is increased by 18.3% compared with TPMO algorithm and increased by 23.1% compared with Naive algorithm in aspect of predicting the next k phases` trajectories, especially when traffic flow is greater, such as this time from weekday morning to evening. Moreover, the time performance of DHMTP algorithm is also clearly improved compared with TPMO algorithm.
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