摘要
针对AMT汽车系统运行过程中,驾驶员手动换档时,车体的动力传动系统各部件协调性较差、驾驶员频繁换档导致安全系数低的问题,它设计了基于神经网络的智能控制系统研究,构建了档位决策模型、离合器接合速度控制模型,其研究试验是在赣州市齿轮箱厂的变速器试验台上进行的,通过对离合器机构进行快速分离和快—慢—快速度控制进行跟踪,离合器快速分离时间为0.4s,能很好跟踪目标位移,机构动作灵敏,完全能够满足离合器控制的需要;对换档机构进行静态连续换档试验,测试数据显示神经网络的加入使得电机对控制信号的响应速度快,即验证了本研究的可行性。
According to the driver＇s manual shift, each component of power transmission system of car body coordination is being poor and the frequent shift leadding to low safety in the process of AMT running of car, it designs the neural network intelligent control technology, then constructs the speed control model of the engaged gear position decision model and clutch engagement speed control model. The experi mental study is carried out in a transmission experiment platform of Ganzhou gear box factory. By means of clutch mechanism＇s fast separa tion and fast slow fast speed tracking control, Clutch fast separation time are 0.4 seconds, so it can be very useful to track target displace ment and the mechanism of action is sensitive and it is fully able to meet the need for clutch control; By means of the shifting mechanism＇s statical and continuous modified profile test, the results prove that the Neural Network is added to make the response speed of the control sig nal fast, and conform the feasibility of the study.
出处
《计算机测量与控制》
北大核心
2013年第11期2966-2968,共3页
Computer Measurement &Control
基金
江西省教育厅基金项目(GJJ11483)
