Research On High-pressure Common Rail Injection System Of Diesel Engine

Energy problem and environmental crisis is getting increasingly serious, thatforced the development of diesel engine to turn to the destination of low pollution,low fuel consumption and high power. The development of the microprocessor andelectronic control technology, make the electronic control technology for dieselengine has been applied. Diesel engine with electronic control system can real-timemonitor the work conditions to calculate the actual needs of the oil, the pressure, andthe right injection time, that improve the combustion performance of the dieselengine, make it has better power, economy and emissions. High Pressure CommonRail electronic control diesel engine as one of the three major breakthroughs ininternal combustion engine industry at the end of the last century, which couldachieve the ideal fuel injection law, is considered one of the most cost-effectiveways to solve the energy and environmental pressure, and received widespreadattention.This paper first introduces the development of the electronic controltechnologies in diesel engine, and electronic control technologies and diesel engineelectronic control system were outlined. Then introduced on the composition andworking principle of the High Pressure Common Rail fuel injection system in dieselengine, whose development status and prospects is also introduced. Then focus onthe electronic control unit of the High Pressure Common Rail fuel injectionsystem–ECU, research and analysis its work conditions, logical structure andsoftware architecture.This paper also research and analysis the system control theory and controlstrategy, based on the control theory, analyzed and summarized control strategy ofthe fuel injection quantity, injection pressure, injection timing, injection rate andmulti-injection coordination control.Finally, research on the closed-loop algorithm of common rail pressure, raisedthe fuzzy RBF neural network PID algorithm, designed the fuzzy RBF neuralnetwork PID controller, performed simulation experiments in MATLAB/SUMULINK Simulation platform, analysis of the steady-state performance, dynamicperformance and the inhibition of the disturbance performance and otherperformance indicators of the fuzzy RBF neural network PID controller, and to do acomparative analysis with fuzzy adaptive PID algorithm. The results show that the steady-state performance, dynamic performance and disturbance rejectionperformance of the fuzzy RBF neural network PID algorithm is better than the onesof the fuzzy adaptive PID algorithm, it adapts better to the requirements of thechange in the high-pressure common rail system operating conditions.