基于改进响应面模型的悬架K&C特性优化
|
摘要
悬架运动学和弹性运动学特性是影响操纵稳定性的重要因素。为提高操纵稳定性,基于ADAMS/Car建立某车型前麦弗逊悬架模型,并进行K&C特性仿真分析。在ADAMS/Insight中计算硬点坐标对K&C特性的灵敏度。利用切比雪夫多项式零点插值技术改进响应面模型,并采用该模型描述悬架K&C特性变动范围与硬点坐标之间的关系,针对该模型采用双层嵌套的改进非支配排序遗传算法和粒子群算法进行多目标优化,结果表明,优化后的悬架K&C特性的变动范围均有不同程度的减小,汽车操纵稳定性得到了提高。
The kinematic and compliance characteristics of suspension( K&C characteristics) have great impact on the handling stability. To improve the handling stability,Macpherson suspension model was conducted by using ADAMS/Car,and the simulation analysis of K&C characteristics was carried out. The sensitivity of K&C characteristics with respect to hard point coordinate was finished with ADAMS/Insight. Zeros of Chebyshev polynomials interpolation method was used to improve the traditional response surface, and was applied to analyze approximation suspension K&C characteristics response. Double nested loop,containing NSGA-Ⅱ in outer loop and particle swarm optimization algorithm in inner loop,was apply for multi-objective optimization. The results show that the variation range of the suspension K&C characteristics has been optimized in a certain degree,and the vehicle handling stability is improved.
The kinematic and compliance characteristics of suspension( K&C characteristics) have great impact on the handling stability. To improve the handling stability,Macpherson suspension model was conducted by using ADAMS/Car,and the simulation analysis of K&C characteristics was carried out. The sensitivity of K&C characteristics with respect to hard point coordinate was finished with ADAMS/Insight. Zeros of Chebyshev polynomials interpolation method was used to improve the traditional response surface, and was applied to analyze approximation suspension K&C characteristics response. Double nested loop,containing NSGA-Ⅱ in outer loop and particle swarm optimization algorithm in inner loop,was apply for multi-objective optimization. The results show that the variation range of the suspension K&C characteristics has been optimized in a certain degree,and the vehicle handling stability is improved.
引文
[1]余志生.汽车理论[M].5版.北京:机械工业出版社,2009.
[2]吕振华,常放,杨道华,等.利用ADAMS对双横臂独立悬架进行仿真分析[J].汽车科技,2005(5):7-9.
[3]白小辉.基于刚柔耦合的悬架K&C特性仿真分析与性能优化[D].成都:西华大学,2016.
[4]张宝珍,阿米尔,肖思俊.基于区间不确定性的前悬架多目标可靠性优化[J].汽车工程,2015,37(6):707-713.
[5]郭孔辉.汽车操纵动力学[M].长春:吉林科学技术出版社,1991.
[6]ZHOU D,ZHAO J,LIU Y.Predictive torque control scheme for three-phase four-switch inverter-fed induction motor drives with DC-link voltages offset suppression[J].Power Electronics IEEE Transactions on,2015,30(6):3309-3318.
[7]JIN R,CHEN W,SIMPSON T W.Comparative studies of metamodelling techniques under multiple modelling criteria[J].Structural&Multidisciplinary Optimization,2001,23(1):1-13.
[8]LIU Y Y,XU S B.New Particle Swarm Optimization Base On Boundary Mutation[J].Cyberspace Security,2017,160(12):653-659.
[9]GHASEMI M,AGHAEI J,HADIPOUR M.New self-organising hierarchical PSO with jumping time-varying acceleration coefficients[J].Electronics Letters,2017,53(20):1360-1362.
[10]FRIEDRICH T,KOTZING T,KREJCA M S,et al.The compact genetic algorithm is efficient under extreme gaussian noise[J].IEEE Transactions on Evolutionary Computation,2017,21(3):477-490.
[11]APOLINAR J,RODRIGUEZ M.Three-dimensional microscope vision system based on micro laser line scanning and adaptive genetic algorithms[J].Optics Communications,2017,385:1-8.
[12]HORTON P,JABOYEDOFF M,OBLED C.Global optimization of an analog method by means of genetic algorithms[J].Monthly Weather Review,2017,145(4):1275 1294.
[13]ASADI E,RIBEIRO R,KHAMESEE M B,et al.Analysis,prototyping and experimental characterization of an adaptive hybrid-electromagnetic damper for automotive suspension systems[J].IEEE Transactions on Vehicular Technology,2017,99:1-5.
[14]何志刚,陈阳,盘朝奉.基于NSGA-Ⅱ算法的麦弗逊悬架多目标优化[J].广西大学学报(自然科学版),2016,41(6):1807-1814.
[2]吕振华,常放,杨道华,等.利用ADAMS对双横臂独立悬架进行仿真分析[J].汽车科技,2005(5):7-9.
[3]白小辉.基于刚柔耦合的悬架K&C特性仿真分析与性能优化[D].成都:西华大学,2016.
[4]张宝珍,阿米尔,肖思俊.基于区间不确定性的前悬架多目标可靠性优化[J].汽车工程,2015,37(6):707-713.
[5]郭孔辉.汽车操纵动力学[M].长春:吉林科学技术出版社,1991.
[6]ZHOU D,ZHAO J,LIU Y.Predictive torque control scheme for three-phase four-switch inverter-fed induction motor drives with DC-link voltages offset suppression[J].Power Electronics IEEE Transactions on,2015,30(6):3309-3318.
[7]JIN R,CHEN W,SIMPSON T W.Comparative studies of metamodelling techniques under multiple modelling criteria[J].Structural&Multidisciplinary Optimization,2001,23(1):1-13.
[8]LIU Y Y,XU S B.New Particle Swarm Optimization Base On Boundary Mutation[J].Cyberspace Security,2017,160(12):653-659.
[9]GHASEMI M,AGHAEI J,HADIPOUR M.New self-organising hierarchical PSO with jumping time-varying acceleration coefficients[J].Electronics Letters,2017,53(20):1360-1362.
[10]FRIEDRICH T,KOTZING T,KREJCA M S,et al.The compact genetic algorithm is efficient under extreme gaussian noise[J].IEEE Transactions on Evolutionary Computation,2017,21(3):477-490.
[11]APOLINAR J,RODRIGUEZ M.Three-dimensional microscope vision system based on micro laser line scanning and adaptive genetic algorithms[J].Optics Communications,2017,385:1-8.
[12]HORTON P,JABOYEDOFF M,OBLED C.Global optimization of an analog method by means of genetic algorithms[J].Monthly Weather Review,2017,145(4):1275 1294.
[13]ASADI E,RIBEIRO R,KHAMESEE M B,et al.Analysis,prototyping and experimental characterization of an adaptive hybrid-electromagnetic damper for automotive suspension systems[J].IEEE Transactions on Vehicular Technology,2017,99:1-5.
[14]何志刚,陈阳,盘朝奉.基于NSGA-Ⅱ算法的麦弗逊悬架多目标优化[J].广西大学学报(自然科学版),2016,41(6):1807-1814.