In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Mo...In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.展开更多
The optimal rendezvous trajectory designs in many current research efforts do not incorporate the practical uncertainties into the closed loop of the design.A robust optimization design method for a nonlinear rendezvo...The optimal rendezvous trajectory designs in many current research efforts do not incorporate the practical uncertainties into the closed loop of the design.A robust optimization design method for a nonlinear rendezvous trajectory with uncertainty is proposed in this paper.One performance index related to the variances of the terminal state error is termed the robustness performance index,and a two-objective optimization model(including the minimum characteristic velocity and the minimum robustness performance index)is formulated on the basis of the Lambert algorithm.A multi-objective,non-dominated sorting genetic algorithm is employed to obtain the Pareto optimal solution set.It is shown that the proposed approach can be used to quickly obtain several inherent principles of the rendezvous trajectory by taking practical errors into account.Furthermore,this approach can identify the most preferable design space in which a specific solution for the actual application of the rendezvous control should be chosen.展开更多
The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expre...The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expressions of steering road feel,steering portability and steering stability are proposed.Through integrating the Monte Carlo descriptive sampling,elitist non-dominated sorting genetic algorithm(NSGA-II) and Taguchi robust design method,the system parameters are optimized with steering road feel and steering portability as optimization targets,and steering stability and steering portability as constraints.The simulation results show that the system optimized based on quality engineering can improve the steering road feel,guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.展开更多
文摘In order to reduce both the weight of vehicles and the damage of occupants in a crash event simultaneously, it is necessary to perform a multi-objective optimal design of the automotive energy absorbing components. Modified non-dominated sorting genetic algorithm II(NSGA II) was used for multi-objective optimization of automotive S-rail considering absorbed energy(E), peak crushing force(Fmax) and mass of the structure(W) as three conflicting objective functions. In the multi-objective optimization problem(MOP), E and Fmax are defined by polynomial models extracted using the software GEvo M based on train and test data obtained from numerical simulation of quasi-static crushing of the S-rail using ABAQUS. Finally, the nearest to ideal point(NIP)method and technique for ordering preferences by similarity to ideal solution(TOPSIS) method are used to find the some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. Results represent that the optimum design point obtained from TOPSIS method exhibits better trade-off in comparison with that of optimum design point obtained from NIP method.
基金supported by the National Natural Science Foundation of China(Grant No.11222215)the National Basic Research Program of China(Grant No.2013CB733100)the Science Project of the National University of Defense Technology(Grant No.CJ12-01-02)
文摘The optimal rendezvous trajectory designs in many current research efforts do not incorporate the practical uncertainties into the closed loop of the design.A robust optimization design method for a nonlinear rendezvous trajectory with uncertainty is proposed in this paper.One performance index related to the variances of the terminal state error is termed the robustness performance index,and a two-objective optimization model(including the minimum characteristic velocity and the minimum robustness performance index)is formulated on the basis of the Lambert algorithm.A multi-objective,non-dominated sorting genetic algorithm is employed to obtain the Pareto optimal solution set.It is shown that the proposed approach can be used to quickly obtain several inherent principles of the rendezvous trajectory by taking practical errors into account.Furthermore,this approach can identify the most preferable design space in which a specific solution for the actual application of the rendezvous control should be chosen.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51005115 and 51005248)the Science Fund of State Key Laboratory of Automotive Safety and Energy (Grant No. KF11201)
文摘The model of the differential steering system(DSS) of electric vehicle with motorized wheels and the three-degree-of-freedom dynamic model of vehicle are built.Based on these models,the concepts and quantitative expressions of steering road feel,steering portability and steering stability are proposed.Through integrating the Monte Carlo descriptive sampling,elitist non-dominated sorting genetic algorithm(NSGA-II) and Taguchi robust design method,the system parameters are optimized with steering road feel and steering portability as optimization targets,and steering stability and steering portability as constraints.The simulation results show that the system optimized based on quality engineering can improve the steering road feel,guarantee steering stability and steering portability and thus provide a theoretical basis for the design and optimization of the electric vehicle with motorized wheels system.
