As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of ...As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.展开更多
An ant colony optimization （ACO）-simulated annealing （SA）-based algorithm is developed for the target assignment problem （TAP） in the air defense （AD） command and control （C2） system of surface to air missi...An ant colony optimization （ACO）-simulated annealing （SA）-based algorithm is developed for the target assignment problem （TAP） in the air defense （AD） command and control （C2） system of surface to air missile （SAM） tactical unit. The accomplishment process of target assignment （TA） task is analyzed. A firing advantage degree （FAD） concept of fire unit （FU） intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.展开更多
The water quality grades of phosphate（PO4-P） and dissolved inorganic nitrogen（DIN） are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validat...The water quality grades of phosphate（PO4-P） and dissolved inorganic nitrogen（DIN） are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validation is used to determine the statistical inference method. To minimize absolute average errors and error mean squares,stratified Kriging（SK） interpolation is applied to DIN and ordinary Kriging（OK） interpolation is applied to PO4-P.Ten percent of the sites is adjusted by considering their impact on the change in deviations in DIN and PO4-P interpolation and the resultant effect on areas with different water quality grades. Thus, seven redundant historical sites are removed. Seven historical sites are distributed in areas with water quality poorer than Grade IV at the north and south branches of the Changjiang（Yangtze River） Estuary and at the coastal region north of the Hangzhou Bay. Numerous sites are installed in these regions. The contents of various elements in the waters are not remarkably changed, and the waters are mixed well. Seven sites that have been optimized and removed are set to water with quality Grades III and IV. Optimization and adjustment of unrestricted areas show that the optimized and adjusted sites are mainly distributed in regions where the water quality grade undergoes transition.Therefore, key sites for adjustment and optimization are located at the boundaries of areas with different water quality grades and seawater.展开更多
Four novel chiral honeycomb structures inspired by the biological arrangement shape are designed.The functional principle is raised to solve the large deformation of bio-inspired structures and the structural constitu...Four novel chiral honeycomb structures inspired by the biological arrangement shape are designed.The functional principle is raised to solve the large deformation of bio-inspired structures and the structural constitutive model is proposed to explain the quasi-static mechanical properties of chiral honeycomb array structures and honeycomb structures.Simulation and experiment results verify the accuracy of theoretical analysis results and the errors are all within 15%.In structural mechanical properties,Equidimensional Chiral Honeycomb Array Structure(ECHS)has excellent mechanical properties.Among ECHS,Small-sized Column Chiral Honeycomb Array Structure(SCHCS)has the best properties.The bearing capacity,specific energy absorption,and specific strength of SCHCS are more than twice as much as the others in this paper.The chiral honeycomb array structure has the best mechanical properties at a certain size.In the structural design,the optimal size model should be obtained first in combination with the optimization algorithm for the protection design.展开更多
Although emission spectral tomography （EST） combines emission spectral measurement with optical computed tomography （OCT）, it is difficult to gain transient emission data from a large number of views, therefore, h...Although emission spectral tomography （EST） combines emission spectral measurement with optical computed tomography （OCT）, it is difficult to gain transient emission data from a large number of views, therefore, high precision OCT algorithms with few views ought to be studied for EST application. To improve the reconstruction precision in the case of few views, a new computed tomography reconstruction algorithm based on multipurpose optimal criterion and simulated annealing theory （multi-criterion simulated annealing reconstruction technique, MCSART） is proposed. This algorithm can suffice criterion of least squares, criterion of most uniformity, and criterion of most smoothness synchronously. We can get global optimal solution by MCSART algorithm with simulated annealing theory. The simulating experiment result shows that this algorithm is superior to the traditional algorithms under various noises.展开更多
Accurate state of charge(SOC)estimation of lithium-ion batteries is a fundamental prerequisite for ensuring the normal and safe operation of electric vehicles,and it is also a key technology component in battery manag...Accurate state of charge(SOC)estimation of lithium-ion batteries is a fundamental prerequisite for ensuring the normal and safe operation of electric vehicles,and it is also a key technology component in battery management systems.In recent years,lithium-ion battery SOC estimation methods based on data-driven approaches have gained significant popularity.However,these methods commonly face the issue of poor model generalization and limited robustness.To address such issues,this study proposes a closed-loop SOC estimation method based on simulated annealing-optimized support vector regression(SA-SVR)combined with minimum error entropy based extended Kalman filter(MEE-EKF)algorithm.Firstly,a probability-based SA algorithm is employed to optimize the internal parameters of the SVR,thereby enhancing the precision of original SOC estimation.Secondly,utilizing the framework of the Kalman filter,the optimized SVR results are incorporated as the measurement equation and further processed through the MEE-EKF,while the ampere-hour integral physical model serves as the state equation,effectively attenuating the measurement noise,enhancing the estimation accuracy,and improving generalization ability.The proposed method is validated through battery testing experiments conducted under three typical operating conditions and one complex and random operating condition with wide temperature variations under only one condition training.The results demonstrate that the proposed method achieves a mean absolute error below 0.60%and a root mean square error below 0.73%across all operating conditions,showcasing a significant improvement in estimation accuracy compared to the benchmark algorithms.The high precision and generalization capability of the proposed method are evident,ensuring accurate SOC estimation for electric vehicles.展开更多
基金Key R&D Program of Tianjin,China(No.20YFYSGX00060).
文摘As the number of electric vehicles(EVs)continues to grow and the demand for charging infrastructure is also increasing,how to improve the charging infrastructure has become a bottleneck restricting the development of EVs.In other words,reasonably planning the location and capacity of charging stations is important for development of the EV industry and the safe and stable operation of the power system.Considering the construction and maintenance of the charging station,the distribution network loss of the charging station,and the economic loss on the user side of the EV,this paper takes the node and capacity of charging station planning as control variables and the minimum cost of system comprehensive planning as objective function,and thus proposes a location and capacity planning model for the EV charging station.Based on the problems of low efficiency and insufficient global optimization ability of the current algorithm,the simulated annealing immune particle swarm optimization algorithm(SA-IPSO)is adopted in this paper.The simulated annealing algorithm is used in the global update of the particle swarm optimization(PSO),and the immune mechanism is introduced to participate in the iterative update of the particles,so as to improve the speed and efficiency of PSO.Voronoi diagram is used to divide service area of the charging station,and a joint solution process of Voronoi diagram and SA-IPSO is proposed.By example analysis,the results show that the optimal solution corresponding to the optimisation method proposed in this paper has a low overall cost,while the average charging waiting time is only 1.8 min and the charging pile utilisation rate is 75.5%.The simulation comparison verifies that the improved algorithm improves the operational efficiency by 18.1%and basically does not fall into local convergence.
基金supported by the National Aviation Science Foundation of China(20090196002)
文摘An ant colony optimization （ACO）-simulated annealing （SA）-based algorithm is developed for the target assignment problem （TAP） in the air defense （AD） command and control （C2） system of surface to air missile （SAM） tactical unit. The accomplishment process of target assignment （TA） task is analyzed. A firing advantage degree （FAD） concept of fire unit （FU） intercepting targets is put forward and its evaluation model is established by using a linear weighted synthetic method. A TA optimization model is presented and its solving algorithms are designed respectively based on ACO and SA. A hybrid optimization strategy is presented and developed synthesizing the merits of ACO and SA. The simulation examples show that the model and algorithms can meet the solving requirement of TAP in AD combat.
基金The National Natural Science Fundation of China under contract Nos 41376190,41271404,41531179,41421001 and41601425the Open Funds of the Key Laboratory of Integrated Monitoring and Applied Technologies for Marin Harmful Algal Blooms,SOA under contract No.MATHA201120204+1 种基金the Scientific Research Project of Shanghai Marine Bureau under contract No.Hu Hai Ke2016-05the Ocean Public Welfare Scientific Research Project,State Oceanic Administration of the People's Republic of China under contract Nos 201305027 and 201505008
文摘The water quality grades of phosphate（PO4-P） and dissolved inorganic nitrogen（DIN） are integrated by spatial partitioning to fit the global and local semi-variograms of these nutrients. Leave-one-out cross validation is used to determine the statistical inference method. To minimize absolute average errors and error mean squares,stratified Kriging（SK） interpolation is applied to DIN and ordinary Kriging（OK） interpolation is applied to PO4-P.Ten percent of the sites is adjusted by considering their impact on the change in deviations in DIN and PO4-P interpolation and the resultant effect on areas with different water quality grades. Thus, seven redundant historical sites are removed. Seven historical sites are distributed in areas with water quality poorer than Grade IV at the north and south branches of the Changjiang（Yangtze River） Estuary and at the coastal region north of the Hangzhou Bay. Numerous sites are installed in these regions. The contents of various elements in the waters are not remarkably changed, and the waters are mixed well. Seven sites that have been optimized and removed are set to water with quality Grades III and IV. Optimization and adjustment of unrestricted areas show that the optimized and adjusted sites are mainly distributed in regions where the water quality grade undergoes transition.Therefore, key sites for adjustment and optimization are located at the boundaries of areas with different water quality grades and seawater.
基金This work is supported by National Key R&D program of of China(No.2022YFB4600500)the National Natural Science Foundation of China(No.51975246)+2 种基金the Science and Technology Development Program of Jilin Province,China(No.20220101192JC)Capital construction fund plan within the budget of Jilin Province(No.2023C041-4)Chongqing Natural Science Foundation(No.CSSTB2022NSCQ-MSX0225).
文摘Four novel chiral honeycomb structures inspired by the biological arrangement shape are designed.The functional principle is raised to solve the large deformation of bio-inspired structures and the structural constitutive model is proposed to explain the quasi-static mechanical properties of chiral honeycomb array structures and honeycomb structures.Simulation and experiment results verify the accuracy of theoretical analysis results and the errors are all within 15%.In structural mechanical properties,Equidimensional Chiral Honeycomb Array Structure(ECHS)has excellent mechanical properties.Among ECHS,Small-sized Column Chiral Honeycomb Array Structure(SCHCS)has the best properties.The bearing capacity,specific energy absorption,and specific strength of SCHCS are more than twice as much as the others in this paper.The chiral honeycomb array structure has the best mechanical properties at a certain size.In the structural design,the optimal size model should be obtained first in combination with the optimization algorithm for the protection design.
基金This work was supported by the Chinese Natural Science Foundation of China(No.60577016)the Foundation(No. 0512034)of Jiangxi Natural Science+1 种基金the Science and Technology Program(No. 2006-164)of Jiangxi Provincial Department of Educationthe Program(No.2005-314)of Key Laboratory of Nondestructive Testing Technology,Ministry of Education.
文摘Although emission spectral tomography （EST） combines emission spectral measurement with optical computed tomography （OCT）, it is difficult to gain transient emission data from a large number of views, therefore, high precision OCT algorithms with few views ought to be studied for EST application. To improve the reconstruction precision in the case of few views, a new computed tomography reconstruction algorithm based on multipurpose optimal criterion and simulated annealing theory （multi-criterion simulated annealing reconstruction technique, MCSART） is proposed. This algorithm can suffice criterion of least squares, criterion of most uniformity, and criterion of most smoothness synchronously. We can get global optimal solution by MCSART algorithm with simulated annealing theory. The simulating experiment result shows that this algorithm is superior to the traditional algorithms under various noises.
基金Key Research and Development Program of Shaanxi Province(2023-GHYB-05 and 2023-YBSF-104).
文摘Accurate state of charge(SOC)estimation of lithium-ion batteries is a fundamental prerequisite for ensuring the normal and safe operation of electric vehicles,and it is also a key technology component in battery management systems.In recent years,lithium-ion battery SOC estimation methods based on data-driven approaches have gained significant popularity.However,these methods commonly face the issue of poor model generalization and limited robustness.To address such issues,this study proposes a closed-loop SOC estimation method based on simulated annealing-optimized support vector regression(SA-SVR)combined with minimum error entropy based extended Kalman filter(MEE-EKF)algorithm.Firstly,a probability-based SA algorithm is employed to optimize the internal parameters of the SVR,thereby enhancing the precision of original SOC estimation.Secondly,utilizing the framework of the Kalman filter,the optimized SVR results are incorporated as the measurement equation and further processed through the MEE-EKF,while the ampere-hour integral physical model serves as the state equation,effectively attenuating the measurement noise,enhancing the estimation accuracy,and improving generalization ability.The proposed method is validated through battery testing experiments conducted under three typical operating conditions and one complex and random operating condition with wide temperature variations under only one condition training.The results demonstrate that the proposed method achieves a mean absolute error below 0.60%and a root mean square error below 0.73%across all operating conditions,showcasing a significant improvement in estimation accuracy compared to the benchmark algorithms.The high precision and generalization capability of the proposed method are evident,ensuring accurate SOC estimation for electric vehicles.
