| As the rapid development of science and technology, all countries have raised the standard of energy saving and environment protection, which makes high pressure common rail system the perfect technology for satisfying all these. In China, number of vehicles using high pressure common rail engines is increasing remarkably, while it comes up with problem of diagnosis of the system. However, China has no command of diagnosis technology of high pressure common rail engines, therefore, designated reparation stations are needed and the price of these stations is very high, which affects the development and implementation of this new technology. It has became a threshold in Chinese automobile industry. It is urgent to develop a self-designed diagnosis of high pressure common rail engine system.In the design of diagnosis of high pressure common rail engine system, the control and intelligent diagnosis of high pressure needs to be tackled.Based on the existing control algorithms, this paper presents three pressure control algorithms, namely, pressure control algorithm based on PID, pressure control algorithm based on Kalman filter and PID, pressure control algorithm based on BP neural networks. Experimental results show that these three algorithms can control the pressure of the high pressure common rail system, to obtain higher precise of the pressure. It is proved that they can all satisfy the application of diagnosis of high pressure common rail engine system.In the diagnosis, this paper presents two algorithms for intelligent diagnosis of high pressure common rail engine system based on thresholds and based on BP neural networks. Because of the great nonlinear projection ability, it is fit for complicated diagnosis. Experimental results show that this algorithm can better diagnosis the high pressure in common rail system, sensors and low-pressure. The preciseness can be higher than 99.89%, which is satisfied in diagnosis of high pressure common rail engine system. |
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