Simulation At Work Process And Performance Optimization For Diesel Engine Based On Genetic Algorithim

Now, energy conservation and emission reduction has become the main target of the majorautomobile manufacturers in the world. Research and development of high efficiency, low fuelconsumption, low pollution and low noise of the engine, improving the level of the energy efficiencyand emission reduction of the engine, has become extremely urgent task for national automobileindustry. With the development of computer technology, computer simulation technology has beenmore and more used in engine research and development. After analyzing the existing simulation ofthe engine, the fresh thought of performance optimization for diesel engine based on geneticalgorithim has been put forward in this dissertation. The main contents of this paper are delivered asfollowings.①In this paper, a simulation model of the whole working process of the diesel engine wasestablished by using one-dimensional engine simulation software of AVL BOOST. The speedcharacteristics of a diesel engine was simulated in the throttle full opening by using the establishedsimulation model, and the simulation results and bench test results were compared. The results showthat the error of the simulation results between experimental results is less than5%, the simulationmodel can accurately reflect the operating characteristics of the diesel engine, to verify the accuracyand the reliability of the simulation model.②Using the established simulation model to research theinfluence of the intake advancedangle, intake lag angle, exhaust advanced angle, exhaust lag angle, compression ratio, fuel injectionadvance angle, intake pipe length, intake pipe diameter, exhaust pipe length and exhaust pipediameter on the engine performance. Choose three typical working conditions,3500r/min (ratedspeed),2000r/min (maximum torque speed) and1000r/min (low speed),change one parameter valuerespectively to simulation in the other parameters uncharged, analyze the influence rules of differentparameters on the engine performance, and put forward the corresponding optimal range andoptimization direction of each parameter.③On this basis, learn theory knowledge of genetic algorithms and multi-objective geneticalgorithm,with the engine power, fuel economy and emission performance as the optimizationobjective, and the above parameters as the design variables. Using the multi-objective geneticalgorithm to optimize the analysis for different working condition. An optimal solution was obtainedby comparing the optimized solution with the front results under different conditions. In the dieselengine test bench, simulation and analysis was done by changing the relevant parameters accordingto the optimal optimization scheme. After optimizing the test results compared with the test results obtained before optimization, the analysis shows that power and emissions performance of dieselengine has been significantly improved fuel economy also improved.