Application study of kriging model in common rail diesel engine calibration

With the high development of modern diesel engines, an increasing number of new controlling parameters have been put out to calibrate, which lead to the growth of calibration loads and the decrease of the work efficiency. This paper dealt with those problems by model-based calibration method which applied the LHS-ESE algorithm to design testing sample, built an ordinary kriging surrogate model based on test data and then optimized these calibration parameters, and this method had been used in an economic optimization process of VMR425DOHC common rail diesel engine. The result of the study showes that the method made the distribution of the testing samples more reasonable. Moreover, the use of the surrogate kriging model had better prediction accuracy with the error less than 2% as well as a good match with these modeling requirements. The fuel consumption had been improved according to the optimization result.