摘要
为了减少混合动力汽车(HEV)油耗和有害气体排放量,提出了基于交叉—变异蜂群算法的参数优化方法,通过建立车辆的动力学模型、关键部件模型,综合运用发动机、电机及动力电池的效率,制定了能量管理策略。以动力系统参数和能量控制策略参数为优化变量,建立了多目标优化模型。在蜂群算法基础上,使用交叉—变异策略加深局部搜索方法的优化深度,使用半随机半保留方法提高了全局搜索效率。结果表明:经美国城市循环工况(UDDS)工况验证,优化后油耗减少了4.85%,CO排放量降低了19.83%,碳氢化合物(CH)排放量降低了8.08%,氮氧化物(NOx)排放量降低了7.08%。这说明了交叉—变异蜂群算法在车辆参数优化中的有效性。
A parameters optimization method was proposed based on crossover-mutation bee colony algorithm to reduce fuel consumption and harmful gases emissions of hybrid electric vehicle(HEV).Energy management strategy was formulated by establishing vehicle dynamic model and key component model,comprehensively utilizing the efficiency of engine,motor and power battery.Taking the parameters of power system and energy control strategy as optimization variables,a multi-objective optimization model was established.On the basis of bee colony algorithm,crossover and mutation strategy were used to deepen local searching method,and half stochastic and half reserved method was used to improve global searching efficiency.The results show that verified by the urban dynamometer driving schedule(UDDS)condition,fuel consumption after optimization decreases by 4.85%,CO emission by 19.83%,hydrocarbon compound(CH)by 8.08%,nitrogen oxides(NOx)compound by 7.08%.This indicates the validity of crossover-mutation bee colony reckoning on parameters optimization.
作者
刘建辉
姚方方
张彦
LIU Jianhui;YAO fangfang;ZHANG Yan(College of Automotive Engineering,Huanghe Jiaotong University,Jiaozuo 454950,China;Zhengzhou Xindafang Heavy Industry Technology Co.,Ltd,Zhengzhou 450064,China)
出处
《汽车安全与节能学报》
CAS
CSCD
北大核心
2021年第2期186-192,共7页
Journal of Automotive Safety and Energy
基金
河南省科学技术攻关计划项目(112102110027)。
关键词
混合动力汽车(HEV)
能量管理策略
有害气体排放
参数优化
交叉—变异策略
蜂群算法
hybrid electric vehicle(HEV)
energy management strategy is ruled
harmful gases emissions
parameters optimization
crossover-mutation strategy
bee colony algorithm
