Model-Guided Extremum Seeking for Diesel Engine Fuel Injection Optimization

作者：Tan Qingyuan; Divekar Prasad; Tan Ying; Chen Xiang^*; Zheng Ming

来源：IEEE/ASME Transactions on Mechatronics, 2018, 23(2): 936-946.

DOI：10.1109/TMECH.2018.2793879

• Data-driven
• diesel engine
• extremum seeking (ES)
• fuel injection
• model-guided optimization
• multiple operating points

Extremum seeking (ES) is a model-free optimization method that has been successfully applied to the automotive engine calibration. However, the slow convergence speed of ES algorithms presents a concern for the online application of this approach to engine optimization where time constraint is critical. In this paper, a model-guided ES architecture is proposed and is showcased with fuel injection optimization for a diesel engine at different operating points. In particular, by integrating a computable engine model into the ES scheme and monitoring the operation point online, the optimal combustion phase under the current operating point can be estimated and this estimation serves as the initialization of the online optimization, resulting in significantly shortened convergence time of ES. The effectiveness of the model-guided ES scheme is validated in the fuel injection optimization design, where the injection timing is controlled to achieve the best compromise between the diesel engine thermal efficiency and the in-cylinder peak pressure rise rate, with both experiments and simulation results presented.

• 出版日期2018-4