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Neural Network aided PMSM multi-objective design and optimization for more-electric aircraft applications

Chinese Journal of Aeronautics 2022年第10期35卷 233-246页

作者： Yuan GAO Tao YANG Serhiy BOZHKO Pat WHEELER tomislav dragicevic Chris GERADA Power Electronics Machines and Control GroupUniversity of NottinghamNottingham NG72RDUK Department of Electrical Engineering Technical University of DenmarkKgs.Lyngby 2800Denmark

This study uses the Neural Network(NN)technique to optimize design of surfacemounted Permanent Magnet Synchronous Motors(PMSMs)for More-Electric Aircraft(MEA)*** key role of NN is to provide dedicated correction factors for the analytical PMSM mass and loss estimation within the entire design *** on that,a globally optimal design can be quickly *** the analytical estimation with Finite-Element Analysis(FEA)is the main research target of training the *** analytical formulae serve as the basis of this study,but they are prone to loss accuracy(especially for a large design space)due to their assumptions and *** the help of the trained NNs,the analytical motor model can give an estimation as accurate as the FEA but with super less time during the optimization *** Average Correction Factor(ACF)approach is regarded as the comparison method to demonstrate the excellent performance of the proposed NN ***,a NN aided three-stage-sevenstep optimization methodology is ***,a Pole-10-Slot-12 PMSM case study is given to demonstrate the feasibility and gain of the NN aided multi-objective optimization *** this case,the NN aided analytical model can generate one motor design in 0.04 s while it takes more than 1 min for the used FEA model.

关键词： Design and optimization Loss estimation Mean Length per Turn(MLT) More-Electric Aircraft(MEA) Neural Network(NN) Permanent Magnet Synchronous Motor(PMSM)

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Electric Vehicle Charging Management Based on Deep Reinforcement Learning

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 719-730页

作者： Sichen Li Weihao Hu Di Cao tomislav dragicevic Qi Huang Zhe Chen Frede Blaabjerg School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengduChina Department of Electrical Engineering Center for Electric Power and Energy Smart Electric Components Technical University of DenmarkCopenhagenDenmark Department of Energy Technology Aalborg UniversityAalborgDenmark

A time-variable time-of-use electricity price can be used to reduce the charging costs for electric vehicle(EV)*** the uncertainty of price fluctuation and the randomness of EV owner’s commuting behavior,we propose a deep reinforcement learning based method for the minimization of individual EV charging *** charging problem is first formulated as a Markov decision process(MDP),which has unknown transition probability.A modified long short-term memory(LSTM)neural network is used as the representation layer to extract temporal features from the electricity price *** deep deterministic policy gradient(DDPG)algorithm,which has continuous action spaces,is used to solve the *** proposed method can automatically adjust the charging strategy according to electricity price to reduce the charging cost of the EV *** other methods to solve the charging problem are also implemented and quantitatively compared with the proposed method which can reduce the charging cost up to 70.2%compared with other benchmark methods.

关键词： Deep reinforcement learning data-driven control uncertainty electric vehicles(EVs)

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Distributed and Decentralized Control Architectures for Converter-Interfaced Microgrids

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Chinese Journal of Electrical Engineering 2017年第2期3卷 41-52页

作者： tomislav dragicevic Dan Wu Qobad Shafiee Lexuan Meng Department of Energy Tech Aalborg UniversityDenmark

This paper gives a summary on recently available technologies for decentralized and distributed control of *** can be classified into two general categories:1)power line communication based architectures and 2)multi-agent based *** essential control methods and information sharing algorithms applied in these architectures are reviewed and examined in a hierarchical manner,in order to point out benefits they will bring to future microgrid *** paper is concluded with a summary on existing methods and a discussion on future development trends.

关键词： Decentralized control distributed bus signaling distributed control microgrids multi-agent systems power line communication

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