Application of the newly developed KLSA model into optimizing the compression ratio of a turbocharged SI engine with cooled EGR 2018-32-0037
Owing to the stochastic nature of engine knock, determination of the knock limited spark angle (KLSA) is very difficult in engine cycle simulation. Therefore, the state-of-the-art knock modeling is mostly limited to either merely prediction of knock onset (i.e. auto-ignition of end gas) or combining a simple unburned mass fraction model representative of knock intensity. In this study, a newly developed KLSA modeling method, which takes both predictions of knock onset and intensity into account, is firstly introduced. Multiple variables such as the excess air ratio (lambda), exhaust gas recirculation (EGR) ratio, cylinder pressure and the end gas temperature are included in the knock onset model. Based on the auto-ignition theory of hot spots in the end gas, both the energy density and heat release rate in hot spots are taken into consideration in the knock intensity (KI) model. Assuming log-normal distribution of KI in consecutive cycles, the knock factor (KF) based on the likelihood ratio is employed as the criterion for definition of knocking cycles. After validation of the KLSA model with the experimental data, the geometric compression ratio of a boosted port fuel injection (PFI) spark ignition (SI) engine modified with cooled EGR is optimized by using a strategy combining the artificial neural networks (ANNs) and the genetic algorithm (GA) with the one-dimensional (1-D) engine cycle simulation. The results reveal that the newly developed model can lead to better performance in prediction of the KLSA in engine cycle simulations than the existing other models. With combined optimization of the geometric design parameter (i.e. the compression ratio) and the operative control variables such as the spark timing, intake valve closure, EGR ratio and so on, the engine thermal efficiency can be improved by 4-8% at the most frequently operated points.
Tie Li, Tao Yin, Bin Wang
Shanghai Jiao Tong Univ., Shanghai Jiao Tong University
SAE/JSAE Small Engine Technology Conference