Quantitative Analysis on Cycle Fuel Injection Quantity Fluctuation of Diesel Engine Electronic In-line Pump System

<div class="section abstract"><div class="htmlview paragraph">A new fuel injection equipment, the Electronic In-line Pump (EIP) system has been developed in this paper, in order to meet The China's PHASE III and IV emission legislations. The EIP is a product which is assembled together by mechanical hydraulic and electrical magnetic system, and it includes electronic magnetic pump and electronic magnetic injector. The fluctuation in cycle fuel injection quantity (CFIQ) influences not only on the coherence of the product performance, but also on the quality qualification rate of the product. A numerical model of the EIP system was built in the AMESim environment for the purpose of creating a design tool for engine application and system optimization. The model was used to predict key injection characteristics, i.e. injection pressure, injection rate, injection duration at different operating conditions, etc. To validate these predictions, experimental tests were conducted at the same model conditions. The results are quite encouraging, and in agreement with model predictions. The influence of the parameters such as fluctuation of supply fuel pressure, cam velocity, plunger matching clearance, peak control current, anchor residual clearance, valve matching clearance, valve lift, injector opening pressure, nozzle flow coefficient, injector needle lift, etc on cycle fuel injection quantity fluctuation (CFIQF) has been analyzed in detail by the AMESim simulation model. The quantitative percentage index of the influence of different parameters on CFIQF, namely, the influence percentage of injector characteristic parameters are from 44% to 34%, valve characteristic parameters are from 20% to 35%, plunger characteristic parameters are from 32% to 19%, and low pressure supply fuel characteristic parameters are form 4% to 12% with the cam rotate speed from 500r/min to 1300r/min. Based on the design of experiment (DOE) method, take the interaction into consideration, system model has been built in the Modeling and design environment (MODDE), the correlations of CFIQ and different factors have been analyzed and the correlation coefficients of CFIQ and different factors are obtained. The result shows that correlation not only exists between the single factor of parameter and CFIQ, also exists between interaction factor of parameter and CFIQ.</div></div>