The ongoing need for better fuel economy and lower exhaust pollution of vehicles has increased the employment of electric power steering(EPS)in automotives.Optimal design of EPS for a product family reduces the develo...The ongoing need for better fuel economy and lower exhaust pollution of vehicles has increased the employment of electric power steering(EPS)in automotives.Optimal design of EPS for a product family reduces the development and fabrication costs significantly.In this paper,the TOPSIS method along with the NSGA-Ⅱis employed to find an optimum family of EPS for an automotive platform.A multi-objective optimization problem is defined considering road feel,steering portability,RMS of Ackerman error,and product family penalty function(PFPF)as the conflicting objective functions.The results for the single objective optimization problems and the ones for the multi-objective optimization problem,as well as two suggested trade-off design points are presented,compared and discussed.For the two suggested points,performance at one objective function is deteriorated by about 1%,while the commonality is increased by 20%–40%,which shows the effectiveness of the proposed method in first finding the non-dominated design points and then selecting the trade-off among the obtained points.The results indicate that the obtained trade-off points have superior performance within the product family with maximum number of common parts.展开更多
在中长期水火发电调度中考虑检修计划的影响是目前中长期水火发电调度面临的难题。利用现代整数代数建模技术，建立发电计划和检修计划协调优化的多场景调度模型。在该模型中，鉴于设备检修计划的连续性，在预测场景树的基础上，将场景...在中长期水火发电调度中考虑检修计划的影响是目前中长期水火发电调度面临的难题。利用现代整数代数建模技术，建立发电计划和检修计划协调优化的多场景调度模型。在该模型中，鉴于设备检修计划的连续性，在预测场景树的基础上，将场景节点划分成不同的场景，通过节点和场景关联矩阵，实现多场景下设备检修模型的构建。同时，鉴于中长期调度计划中发电计划和检修计划对时段间隔要求的不同，分别设置电量相关节点和电力相关节点，实现中长期发电计划和检修计划的协调。上述模型是一个大规模混合整数线性规划（mixed integer linear programming，MILP）问题，采用商用MILP求解器进行求解。大规模实际水火电系统的实例分析结果表明，所提模型和方法是可行、有效的。展开更多
Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the...Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.展开更多
The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-obj...The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.展开更多
文摘The ongoing need for better fuel economy and lower exhaust pollution of vehicles has increased the employment of electric power steering(EPS)in automotives.Optimal design of EPS for a product family reduces the development and fabrication costs significantly.In this paper,the TOPSIS method along with the NSGA-Ⅱis employed to find an optimum family of EPS for an automotive platform.A multi-objective optimization problem is defined considering road feel,steering portability,RMS of Ackerman error,and product family penalty function(PFPF)as the conflicting objective functions.The results for the single objective optimization problems and the ones for the multi-objective optimization problem,as well as two suggested trade-off design points are presented,compared and discussed.For the two suggested points,performance at one objective function is deteriorated by about 1%,while the commonality is increased by 20%–40%,which shows the effectiveness of the proposed method in first finding the non-dominated design points and then selecting the trade-off among the obtained points.The results indicate that the obtained trade-off points have superior performance within the product family with maximum number of common parts.
文摘在中长期水火发电调度中考虑检修计划的影响是目前中长期水火发电调度面临的难题。利用现代整数代数建模技术，建立发电计划和检修计划协调优化的多场景调度模型。在该模型中，鉴于设备检修计划的连续性，在预测场景树的基础上，将场景节点划分成不同的场景，通过节点和场景关联矩阵，实现多场景下设备检修模型的构建。同时，鉴于中长期调度计划中发电计划和检修计划对时段间隔要求的不同，分别设置电量相关节点和电力相关节点，实现中长期发电计划和检修计划的协调。上述模型是一个大规模混合整数线性规划（mixed integer linear programming，MILP）问题，采用商用MILP求解器进行求解。大规模实际水火电系统的实例分析结果表明，所提模型和方法是可行、有效的。
基金Projects(51908388,51508315,51905320)supported by the National Natural Science Foundation of ChinaProject(2019 JZZY 010911)supported by the Key R&D Program of Shandong Province,China+1 种基金Project supported by the Shandong University of Technology&Zibo City Integration Develo pment Project,ChinaProject(ZR 2021 MG 012)supported by Shandong Provincial Natural Science Foundation,China。
文摘Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.
基金Projects(51005115, 51005248) supported by the National Natural Science Foundation of ChinaProject(SKLMT-KFKT-201105)supported by the Visiting Scholar Foundation of State Key Laboratory of Mechanical Transmission in Chongqing University, ChinaProject(QC201101) supported by Visiting Scholar Foundation of the Automobile Engineering Key Laboratory of Jiangsu Province, China
文摘The vehicle model of the recirculating ball-type electric power steering (EPS) system for the pure electric bus was built. According to the features of constrained optimization for multi-variable function, a multi-objective genetic algorithm (GA) was designed. Based on the model of system, the quantitative formula of the road feel, sensitivity, and operation stability of the steering were induced. Considering the road feel and sensitivity of steering as optimization objectives, and the operation stability of steering as constraint, the multi-objective GA was proposed and the system parameters were optimized. The simulation results show that the system optimized by multi-objective genetic algorithm has better road feel, steering sensibility and steering stability. The energy of steering road feel after optimization is 1.44 times larger than the one before optimization, and the energy of portability after optimization is 0.4 times larger than the one before optimization. The ground test was conducted in order to verify the feasibility of simulation results, and it is shown that the pure electric bus equipped with the recirculating ball-type EPS system can provide better road feel and better steering portability for the drivers, thus the optimization methods can provide a theoretical basis for the design and optimization of the recirculating ball-type EPS system.
