Song, K., Xie, H., Jiang, W., Chen, Q. et al., "On-Line Optimization of Direct-Injection-Timing for SI-CAI Hybrid Combustion in a PFI-DI Gasoline Engine," SAE Technical Paper 2016-01-0757, 2016, doi:10.4271/2016-01-0757.
The spark ignition-controlled auto-ignition (SI-CAI) hybrid combustion is promising in achieving smooth transition between SI and CAI combustion but, it is limited by the combustion cyclic-variation at late combustion phasing to avoid too high pressure rise rate (PRR). In this paper, to stabilize the combustion and reduce PRR, the in-cylinder fuel-stratification strategy is investigated in a gasoline engine, equipped with port fuel injection combined with single pulse direct injection (PFI-DI). Experimental results confirm the benefits of employing PFI-DI in comparison with PFI and single-pulse DI strategy. The influence of DI timing (Start of injection, SOI) on the combustion process is found to be quite complicated, in terms of combustion phasing, combustion stability, PRR and thermal efficiency. It makes the optimal-SOI calibration time-intensive, since complex trade-off between PRR and thermal efficiency is needed.Therefore, a novel SOI on-line optimization controller (Smart-SOI) is proposed, consisting of a cost function and its extremum seeker. The cost function has PRR and thermal efficiency as inputs, and established a parabolic relation from SOI to the function output. By searching for the extremum of this parabola via the extremum seeking algorithm, the optimal-SOI is successfully calibrated on-line. Experimental validation results show that SOI can converge towards its optimal position in terms of thermal efficiency and PRR via Smart-SOI at different operating conditions, in terms of spark timing and loads. It takes 200 to 1600 cycles at 1500 engine speed for Smart-SOI to correct an offset of 68°CA in optimal SOI at most in the test cases. The Smart-SOI is valuable in the fuel-stratified SI-CAI hybrid combustion control, because it can adapt to combustion boundary condition variations, reduce the off-line calibration burden of SOI and is easy to implement.