To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load ...To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load are proposed. The optimization method of excited capacitors to minimize the reactive power of the control winding at a variable speed is given. The calculation capacity of the machine with a diode bridge rectifier load is proposed. To achieve global searching, the integrated method with the improved real-coded genetic algorithm and the twodimensional finite element method （FEM） is introduced. Design results of the sample show that reactive power can be reduced by the method, and the converter capacity can be decreased to 1/3 of output rated power at the speed ratio of 1 ： 3, thus reducing the volume and the mass of the inverter.展开更多
In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of Ch...In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda(IDZSDAs),combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity(USDC).After obtaining USDC assessment results through the assessment system,an approach combining Least Absolute Shrinkage and Selection Operator(LASSO)regression and Random Forest(RF)based on machine learning is proposed for identifying influencing factors and characterizing key issues.Combining Coupling Coordination Degree(CCD)analysis,the study further summarizes the systemic patterns and future directions of urban sustainable development.A case study on the IDZSDAs from 2015 to 2022 reveals that:(1)the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process;(2)the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities;and(3)the machine learning-based combined recognition method is scalable and dynamic.It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.展开更多
Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM...Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM)strategy to suppress the ZSC.Five vectors are selected as basic voltage vectors in one switching period.The fundamental and harmonic planes and the zero-sequence plane are taken into consideration to synthesis the reference voltage vector.To suppress the ZSC,a non-zero zero-sequence voltage(ZSV)is generated to compensate the third harmonic back-EMF.Rather than triangular carrier modulation,the sawtooth carrier modulation strategy is used to generate asymmetric PWM signals.The modulation range is investigated to explore the variation of modulation range caused by considering the zero-sequence plane.With the proposed method,the ZSC can be considerably reduced.The simulated and experimental results are presented to validate the effectiveness of the proposed modulation strategy.展开更多
Dual mechanical port machine（DMPM）, as a novel electromechanical energy conversion device, has attracted widespread attention. DMPM with spoke type permanent magnet arrangements（STPM-DMPM）, which is one of several...Dual mechanical port machine（DMPM）, as a novel electromechanical energy conversion device, has attracted widespread attention. DMPM with spoke type permanent magnet arrangements（STPM-DMPM）, which is one of several types of DMPM, has been of interest recently. The unique coupling characteristics of STPM-DMPM are beneficial to improving system performance, but these same characteristics increase the difficulties of control. Now there has been little research about the control of STPM-DMPM, and this has hindered its practical application. Based on a mathematical model of STPM-DMPM, the coupling characteristics and the merits and demerits of such devices are analyzed as applied to a hybrid system. The control strategies for improving the disadvantages and for utilizing the advantage of coupling are researched. In order to weaken the interaction effect of torque outputs in the inner motor and the outer motor that results from coupling in STPM-DMPM, a decoupling control method based on equivalent current control is proposed, and independent torque control for the inner motor and outer motor is achieved. In order to solve address the problem of adequately utilization of coupling, minimizing the overall copper loss of the inner motor and the outer motor of STPM-DMPM is taken as the optimization objective for optimal control, and the purpose of utilizing the coupling adequately and reasonably is achieved. The verification tests of the proposed decoupling control and optimal control strategies are carried out on a prototype STPM-DMPM, and the experimental results show that the interaction effect of torque outputs in the inner motor and the outer motor can be markedly weakened through use of the control method. The overall copper loss of the inner motor and the outer motor can be markedly reduced through use of the optimal control method, while the power output remains unchanged. A breakthrough in the control problem of STPM-DMPM is accomplished by combining the control methods. Good performance in the control of STPM-DMPM will enhance its practicality, particularly as applied to hybrid systems.展开更多
Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co n...Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co ntinues to be major challenges for industries in addressing accuracy improvement . This study presents a method of improving machining accuracy in ECM by using a dual pole tool with a metallic bush outside the insulated coating of a cathode tool. The bush is connected with anode and so the electric field at the side gap area is substantially weakened. The modeling and simulation indicate that the p ositive bush brings down the current density at the side gap area of the machine d hole and hence reduces the stray material removal there. It has been experimen tally observed that the machining accuracy and the process stability are signifi cantly improved.展开更多
With the increasing demand for high torque density in motors,more and more new topologies emerge.Furthermore,the magnetic field modulation principle is widely concerned and has evolved into an effective analysis metho...With the increasing demand for high torque density in motors,more and more new topologies emerge.Furthermore,the magnetic field modulation principle is widely concerned and has evolved into an effective analysis method for studying the new motor topology.This paper introduces the principle of magnetic field modulation.And the research on high torque density in recent years is reviewed from the perspective of magnetic field modulation,including permanent magnet vernier machine(PMVM),flux reverse machine(FRM),flux switching machine(FSM),dual permanent magnet(DPM)machine,and DC biased machine.The principle of magnetic field modulation makes it possible to propose higher torque density topologies in the future.展开更多
Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a chal...Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a challenge due to the large number of possible combinations,making exhaustive experimental or computational screening a daunting task.In this study,a density functional theory(DFT)-based machine learning(ML)-accelerated(DFT-ML)hybrid approach was developed to test a set of 406 dual transition metal catalysts on N-doped graphene(NG)for the electroreduction of CO_(2)to HCOOH.The results showed that the ML algorithms can successfully capture the relationship between the descriptors of the DACs(inputs)and the limiting potential for HCOOH generation(output).Of the four ML algorithms studied in this work,the feedforward neural network model achieved the highest prediction accuracy(the highest correlation coefficient(R^(2))of 0.960 and the lowest root mean square error(RMSE)of 0.319 eV on the test set)and the predicted results were verified by DFT calculations with an average absolute error of 0.14 eV.The DFT-ML approach identified Co-Co-NG and Ir-Fe-NG as the most active and stable electrocatalysts for the electrochemical reduction of CO_(2)to HCOOH.The DFT-ML hybrid approach exhibits exceptional prediction accuracy while enabling a significant reduction in screening time by an impressive 64%compared to conventional DFT-only calculations.These results demonstrate the immense potential of using ML methods to accelerate the screening and rational design of efficient catalysts for various energy and environmental applications.展开更多
One-step direct production of methanol from methane and water(PMMW)under mild conditions is challenging in heterogeneous catalysis owing to the absence of highly effective catalysts.Herein,we designed a series of“Sin...One-step direct production of methanol from methane and water(PMMW)under mild conditions is challenging in heterogeneous catalysis owing to the absence of highly effective catalysts.Herein,we designed a series of“Single-Atom”-“Frustrated Lewis Pair”(SA-FLP)dual active sites for the direct PMMW via density functional theory(DFT)calculations combined with a machine learning(ML)approach.The results indicate that the nine designed SA-FLP catalysts are capable of efficiently activate CH4 and H_(2)O and facilitate the coupling of OH^(*)and CH_(3)^(*)into methanol.The DFT-based microkinetic simulation(MKM)results indicate that CH_(3)OH production on Co1-FLP and Pt1-FLP catalysts can reach the turnover frequencies(TOFs)of 1.01×10^(−3)s^(-1)and 8.80×10^(−4)s^(-1),respectively,which exceed the experimentally reported values by three orders of magnitude.ML results unveil that the gradient boosted regression model with 13 simple features could give satisfactory predictions for the TOFs of CH_(3)OH production with RMSE and R^(2)of 0.009 s^(-1)and 1.00,respectively.The ML-predicted MKM results indicate that four catalysts including V_(1-),Fe_(1-),Ti_(1-),and Mn_(1)-FLP exhibit higher TOFs of CH_(3)OH production than the value that the most relevant experiments reported,indicating that the four catalysts are also promising catalysts for the PMMW.This study not only develops a simple and efficient approach for design and screening SA-FLP catalysts but also provides mechanistic insights into the direct PMMW.展开更多
文摘To minimize the reactive power of the converter of the control winding in the novel dual stator-winding induction generator based on the PWM converter, design features of the induction generator with a rectified load are proposed. The optimization method of excited capacitors to minimize the reactive power of the control winding at a variable speed is given. The calculation capacity of the machine with a diode bridge rectifier load is proposed. To achieve global searching, the integrated method with the improved real-coded genetic algorithm and the twodimensional finite element method （FEM） is introduced. Design results of the sample show that reactive power can be reduced by the method, and the converter capacity can be decreased to 1/3 of output rated power at the speed ratio of 1 ： 3, thus reducing the volume and the mass of the inverter.
基金supported by the National Key Research and Development Program of China under the sub-theme“Research on the Path of Enhancing the Sustainable Development Capacity of Cities and Towns under the Carbon Neutral Goal”[Grant No.2022YFC3802902-04].
文摘In response to the United Nations Sustainable Development Goals and China’s“Dual Carbon”Goals(DCGs means the goals of“Carbon Peak and carbon neutrality”),this paper from the perspective of the construction of China’s Innovation Demonstration Zones for Sustainable Development Agenda(IDZSDAs),combines carbon emission-related metrics to construct a comprehensive assessment system for Urban Sustainable Development Capacity(USDC).After obtaining USDC assessment results through the assessment system,an approach combining Least Absolute Shrinkage and Selection Operator(LASSO)regression and Random Forest(RF)based on machine learning is proposed for identifying influencing factors and characterizing key issues.Combining Coupling Coordination Degree(CCD)analysis,the study further summarizes the systemic patterns and future directions of urban sustainable development.A case study on the IDZSDAs from 2015 to 2022 reveals that:(1)the combined identification method based on machine learning and CCD models effectively quantifies influencing factors and key issues in the urban sustainable development process;(2)the correspondence between influencing factors and key subsystems identified by the LASSO-RF combination model is generally consistent with the development situations in various cities;and(3)the machine learning-based combined recognition method is scalable and dynamic.It enables decision-makers to accurately identify influencing factors and characterize key issues based on actual urban development needs.
基金supported in part by the National Natural Science Foundation of China under Grant 51977099。
文摘Dual three-phase permanent-magnet synchronous machines(DTP-PMSM)connected with a single neutral point provide a loop for zero-sequence current(ZSC).This paper proposes a novel space vector pulse width modulation(SVPWM)strategy to suppress the ZSC.Five vectors are selected as basic voltage vectors in one switching period.The fundamental and harmonic planes and the zero-sequence plane are taken into consideration to synthesis the reference voltage vector.To suppress the ZSC,a non-zero zero-sequence voltage(ZSV)is generated to compensate the third harmonic back-EMF.Rather than triangular carrier modulation,the sawtooth carrier modulation strategy is used to generate asymmetric PWM signals.The modulation range is investigated to explore the variation of modulation range caused by considering the zero-sequence plane.With the proposed method,the ZSC can be considerably reduced.The simulated and experimental results are presented to validate the effectiveness of the proposed modulation strategy.
基金Supported by National Hi-tech Research and Development Program of China (863 Program,Grant No.2011AA11A238)
文摘Dual mechanical port machine（DMPM）, as a novel electromechanical energy conversion device, has attracted widespread attention. DMPM with spoke type permanent magnet arrangements（STPM-DMPM）, which is one of several types of DMPM, has been of interest recently. The unique coupling characteristics of STPM-DMPM are beneficial to improving system performance, but these same characteristics increase the difficulties of control. Now there has been little research about the control of STPM-DMPM, and this has hindered its practical application. Based on a mathematical model of STPM-DMPM, the coupling characteristics and the merits and demerits of such devices are analyzed as applied to a hybrid system. The control strategies for improving the disadvantages and for utilizing the advantage of coupling are researched. In order to weaken the interaction effect of torque outputs in the inner motor and the outer motor that results from coupling in STPM-DMPM, a decoupling control method based on equivalent current control is proposed, and independent torque control for the inner motor and outer motor is achieved. In order to solve address the problem of adequately utilization of coupling, minimizing the overall copper loss of the inner motor and the outer motor of STPM-DMPM is taken as the optimization objective for optimal control, and the purpose of utilizing the coupling adequately and reasonably is achieved. The verification tests of the proposed decoupling control and optimal control strategies are carried out on a prototype STPM-DMPM, and the experimental results show that the interaction effect of torque outputs in the inner motor and the outer motor can be markedly weakened through use of the control method. The overall copper loss of the inner motor and the outer motor can be markedly reduced through use of the optimal control method, while the power output remains unchanged. A breakthrough in the control problem of STPM-DMPM is accomplished by combining the control methods. Good performance in the control of STPM-DMPM will enhance its practicality, particularly as applied to hybrid systems.
文摘Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co ntinues to be major challenges for industries in addressing accuracy improvement . This study presents a method of improving machining accuracy in ECM by using a dual pole tool with a metallic bush outside the insulated coating of a cathode tool. The bush is connected with anode and so the electric field at the side gap area is substantially weakened. The modeling and simulation indicate that the p ositive bush brings down the current density at the side gap area of the machine d hole and hence reduces the stray material removal there. It has been experimen tally observed that the machining accuracy and the process stability are signifi cantly improved.
基金supported in part by the National Natural Science Foundation of China(NSFC)under Project No.51737010the National Key R&D Program of China under Grant 2020YFA0710500。
文摘With the increasing demand for high torque density in motors,more and more new topologies emerge.Furthermore,the magnetic field modulation principle is widely concerned and has evolved into an effective analysis method for studying the new motor topology.This paper introduces the principle of magnetic field modulation.And the research on high torque density in recent years is reviewed from the perspective of magnetic field modulation,including permanent magnet vernier machine(PMVM),flux reverse machine(FRM),flux switching machine(FSM),dual permanent magnet(DPM)machine,and DC biased machine.The principle of magnetic field modulation makes it possible to propose higher torque density topologies in the future.
基金partially sponsored by the Development and Reform Commission of Ningbo Municipality(Ningbo Municipal Engineering Research Centre for Solid Carbonaceous Wastes Processing and Utilization Technologies)the National Natural Science Foundation Youth Science Fund Project(52203300),the National Natural Science Foundation of China(22308195)+4 种基金the Natural Science Foundation of Shandong Province(ZR2023QB237)Ningbo Science and Technologies Innovation 2025 Major Special Project(2018B10027)The Zhejiang Provincial Department of Science and Technology is acknowledged for sponsorship under its Provincial Key Laboratory Program(2020E10018)Ningbo Bureau of Science and Technology is also thanked for its support to the Key Laboratory of Clean Energy Conversion TechnologiesThe University of Nottingham Ningbo China provides the first author with a full scholarship。
文摘Dual-atom catalysts(DACs)have emerged as potential catalysts for effective electroreduction of CO_(2)due to their high atom utilization efficiency and multiple active sites.However,the screening of DACs remains a challenge due to the large number of possible combinations,making exhaustive experimental or computational screening a daunting task.In this study,a density functional theory(DFT)-based machine learning(ML)-accelerated(DFT-ML)hybrid approach was developed to test a set of 406 dual transition metal catalysts on N-doped graphene(NG)for the electroreduction of CO_(2)to HCOOH.The results showed that the ML algorithms can successfully capture the relationship between the descriptors of the DACs(inputs)and the limiting potential for HCOOH generation(output).Of the four ML algorithms studied in this work,the feedforward neural network model achieved the highest prediction accuracy(the highest correlation coefficient(R^(2))of 0.960 and the lowest root mean square error(RMSE)of 0.319 eV on the test set)and the predicted results were verified by DFT calculations with an average absolute error of 0.14 eV.The DFT-ML approach identified Co-Co-NG and Ir-Fe-NG as the most active and stable electrocatalysts for the electrochemical reduction of CO_(2)to HCOOH.The DFT-ML hybrid approach exhibits exceptional prediction accuracy while enabling a significant reduction in screening time by an impressive 64%compared to conventional DFT-only calculations.These results demonstrate the immense potential of using ML methods to accelerate the screening and rational design of efficient catalysts for various energy and environmental applications.
文摘One-step direct production of methanol from methane and water(PMMW)under mild conditions is challenging in heterogeneous catalysis owing to the absence of highly effective catalysts.Herein,we designed a series of“Single-Atom”-“Frustrated Lewis Pair”(SA-FLP)dual active sites for the direct PMMW via density functional theory(DFT)calculations combined with a machine learning(ML)approach.The results indicate that the nine designed SA-FLP catalysts are capable of efficiently activate CH4 and H_(2)O and facilitate the coupling of OH^(*)and CH_(3)^(*)into methanol.The DFT-based microkinetic simulation(MKM)results indicate that CH_(3)OH production on Co1-FLP and Pt1-FLP catalysts can reach the turnover frequencies(TOFs)of 1.01×10^(−3)s^(-1)and 8.80×10^(−4)s^(-1),respectively,which exceed the experimentally reported values by three orders of magnitude.ML results unveil that the gradient boosted regression model with 13 simple features could give satisfactory predictions for the TOFs of CH_(3)OH production with RMSE and R^(2)of 0.009 s^(-1)and 1.00,respectively.The ML-predicted MKM results indicate that four catalysts including V_(1-),Fe_(1-),Ti_(1-),and Mn_(1)-FLP exhibit higher TOFs of CH_(3)OH production than the value that the most relevant experiments reported,indicating that the four catalysts are also promising catalysts for the PMMW.This study not only develops a simple and efficient approach for design and screening SA-FLP catalysts but also provides mechanistic insights into the direct PMMW.
