摘要
通过建立各缸空燃比不均匀的产生及传递模型,提出了一种利用改进遗传算法进行参数辨识的方法。新方法只需一个宽域氧传感器(universal exhaust gas oxygen sensor,UEGO)便能完成参数辨识,大幅度简化试验过程的同时能显著降低试验成本。结合卡尔曼滤波算法建立的各缸空燃比观测器,构建了平衡各缸空燃比的反馈控制系统。GT-Power与Simulink联合仿真结果表明:新方法能将各缸空燃比差异从原来的±10%减至±1%以内。
A genetic algorithm identification method and model to produce and transfer cylinder-to- cylinder AFR variation was proposed,thus in stead of many UEGO only one was needed , so the experiment become much simplified and the cost could be significantly reduced. Then a feedback AFR balance control system was set up using individual cylinder AFR observer based on Kalman filtering algorithm. The integrated simulation of GT-Power and Simulink shows that the AFR variation cylinder-to-cylinder can be reduced from ±10% to±1% by using this method.
出处
《内燃机工程》
EI
CAS
CSCD
北大核心
2013年第6期13-18,共6页
Chinese Internal Combustion Engine Engineering
基金
国家"八六三"高技术研究发展计划资助项目(2008AA11A114)
天津大学内燃机燃烧学国家重点试验室自主课题资助项目
关键词
内燃机
各缸空燃比不均匀
多缸汽油机
遗传算法
参数辨识
卡尔曼滤波
IC engine
individual cylinder AFR unbalance
multi-cylinder gasolineengine
genetic algorithm
parameter identification
Kalman filtering