The optimization of the biodiesel blending ratio is based on the best engine performance. Engine performance is mainly related to power, economy, emission performance, etc. Some of these performance indicators are contrary to each other, such as complete combustion of the engine, general fuel economy, However, often NOx emissions are high, and smoke reduction often leads to increased NOx emissions, and so on. In addition, the range of choice for the blending of biodiesel is larger, ranging from 10% to 95%. Therefore, if the conventional machine test method with load characteristics and speed characteristics is used, the workload is bound to be large, and it is difficult to completely cover the range of the blending ratio. . Modern experimental design methods, such as orthogonal design test methods, solve the problems that involve multiple factors in the test. However, when the scope of the test is large, and the test factor has more inspection grades (in the test design, the grade is called level), the orthogonal test and other popular test methods are used for the test, and the test volume is still large. The uniform design method proposed by Wang Yuan and Fang Kaitai considers how to evenly spread the design points within the scope of the test, so that the most useful information can be obtained with fewer test points, and the problems of multi-factor and multi-level tests can be solved well. In this study, a uniform design method was used to design a biodiesel blending and burning ratio test scheme.
The variables that can be controlled in this experiment include biodiesel blending ratio, engine speed, and load. In order to improve the testing accuracy, 18 blended-burning recipes were selected for study. The engine speed and load were respectively selected from 9 levels and 6 levels. The indicator then selects the fuel consumption rate and power to represent the economic characteristics and power characteristics of the engine, respectively. NOx, smoke, and CO represent the emission characteristics of the engine. Due to the low HC emission under the experimental conditions, it is not considered. The use of DPS software to generate an optimized engine burn-up ratio uniform design schedule table, see. The corresponding test result data is also shown in the middle.
Regression analysis of fuel consumption rate Calculation of fuel consumption rate Regression equation and significance test After taking the logarithm of the fuel consumption rate data, select the independent variable under the confidence level of 005 for regression analysis processing: Y1=exp(58125+04123X1+02045X2) -06537X3+09643X23-07593X2X3), (2) Significant test of the regression equation. The regression coefficient of the regression equation is 09302. The remaining standard deviation is 01717, and the p-test value is 00001. The significance test of the regression equation shows that the equation is effective. well.
Analysis of the effect of blend ratio of biodiesel on fuel consumption When the ratio of diesel blended fuel is taken as 10%, the fuel consumption rate “be†is the top surface of the crankshaft, as shown. Different biodiesel blending ratios correspond to different curved top cylinders, the same below.
The effect of speed and load on the fuel consumption rate is known. Under the 10% biodiesel blending ratio, the engine fuel consumption rate decreases first and then increases with the increase of the load, and increases with the increase of the engine speed. The trend of consumption rate shows that the regression equation is credible. Two-fold integration of the load and speed results in Vbe, and the trend is as shown.
The relationship between the blend ratio and Vbe is known, the engine fuel consumption rate increases with the increase of the ratio of biodiesel blending, which is due to the low calorific value of biodiesel fuel, which indicates the decrease of thermal efficiency, and the viscosity of biodiesel is relatively large. The chemical performance is poor. With the increase of the blending ratio, the mixture in a certain area is too rich and the combustion is not enough. As a result, the fuel consumption rate increases with the increase of the blending ratio of biodiesel.
Power Regression Analysis Calculation Power Regression Equation Significance Test After taking the logarithm of the power data logarithm again, select the independent variable at a confidence level of 005 for regression analysis: Y2=exp(-28807+29150X2+37949X3-01774X21-07409X2- 16436X23), (3) The regression equation was tested for significance. The regression coefficient of the regression equation was 09936, the residual standard deviation was 0126, and the p-test value was 00001. The significance test of the regression equation showed that the equation fitting effect was very good.
Analysis of the effect of the blending ratio of biodiesel on burning At the blending ratio of 10% biodiesel, the top of the column with power Pe is shown in the figure. It can be seen that at a blending ratio of 10% biodiesel, the engine power increases with the increase of load and speed, which is in line with the trend of diesel engine power, indicating that the regression equation is credible.
Speed, load impact on power The two-fold integration of the engine speed and load results in VPe. The trend is as follows. The relationship between the blending ratio and VPe indicates that the engine power decreases with the increase of the blending ratio of biodiesel, and the blending ratio changes slowly. This is because the low calorific value of the biodiesel fuel indicates that the thermal efficiency is reduced and the engine power is increased. The biodiesel blending ratio decreases.
Analysis of the effect of blending ratio of biodiesel on the smoke content At the ratio of 10% biodiesel blended, the top of the cylinder with smoke as the top is shown. Smoke is generated in the high temperature and pressure conditions, due to local high temperature, oxygen deficiency, cracking and dehydrogenation to produce solid particles with carbon as the main component. It can be seen that smoke increases with the increase of speed and load, which is in accordance with the smoke generation mechanism of diesel engines, indicating that the smoke regression equation is credible. Due to the non-uniformity of the diesel engine mixture, despite the overall oxygen-rich combustion, partial oxygen deficiency still leads to the generation of smoke, and the oxygen enrichment of the fuel can significantly reduce black smoke emissions.
Analysis of the effect of blending ratio of biodiesel to diesel on CO At the ratio of 10% biodiesel blended, the top cylinder with CO as the top surface is shown as 0. CO is the main intermediate product produced by hydrocarbon fuel in the combustion process. The main influencing factor is the oxygen concentration and temperature in the combustion process. The CO emission decreases first and then increases with the decrease of the excess air coefficient. From 0, the change trend of the CO regression equation is in line with the CO production mechanism of the diesel engine, which shows that the regression equation is credible.
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