Automatic Combustion Phase Calibration With Extremum Seeking Approach

Abstract

One of the most effective factors influencing performance, efficiency, and pollutant emis sions o f internal combustion engines is the combustion phasing: in gasoline engines elec tronic control units (ECUs) manage the spark advance (SA) in order to set the optimal combustion phase. Combustion control is assuming a crucial role in reducing engine tail pipe emissions and maximizing performance. The number of actuations influencing the combustion is increasing, and as a consequence, the calibration of control parameters is becoming challenging. One of the most effective factors influencing performance and effi ciency is the combustion phasing: for gasoline engines, control variables such as SA, airto-fuel ratio (AFR), variable valve timing (W T), and exhaust gas recirculation (EGR) are mostly used to set the combustion phasing. The optimal control setting can be chosen according to a target function (cost or merit function), taking into account peiformance indicators, such as indicated mean effective pressure (IMEP), brake-specific fuel con sumption (BSFC), pollutant emissions, or other indexes inherent to reliability issues, such as exhaust gas temperature or knock intensity. Many different approaches can be used to reach the best calibration settings: design of experiment (DOE) is a common option when many parameters influence the results, but other methodologies are in use: some o f them are based on the knowledge of the controlled system behavior by means of models that are identified during the calibration process. The paper proposes the use o f a different concept, based on the extremum seeking approach. The main idea consists in changing the values of each control parameter at the same time, identifying its effect on the monitored target function, and allowing to shift automatically the control setting towards the optimum solution throughout the calibration procedure. An original tech nique for the recognition of control parameters variations effect on the target function is introduced, based on spectral analysis. The methodology has been applied to data refer ring to different engines and operating conditions, using IMEP, exhaust temperature, and knock intensity for the definition of the target function and using SA and AFR as control variables. The approach proved to be efficient in reaching the optimum control setting, showing that the optimal setting can be achieved rapidly and consistently.

Adaptive in-cylinder pressure model for spark ignition engine control

“…A widely used method to evaluate combustion efficiency is through the indicated mean effective pressure (IMEP), which is calculated from the in-cylinder pressure trace. Many studies have applied extremum seeking (ES) methods for combustion optimization, thus the optimal SA is calibrated in real-time [4]. Other works employ on-board learning algorithms for real-time combustion control, in [5] a scheme with two layers is proposed, in which the target of the crank angle position where 50% of the heat is released (CA50) is achieved by controlling the SA through a combination of feed forward / feed back controller and a look-up table on-line calibrated.…”

Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps

“…Static optimization of the control inputs of an engine is the first step towards the calibration of an engine control unit. This optimization can be carried out directly on the real engine [3] or by utilizing models to represent the engine [4,5]. The number of actuations influencing the engine performance is increasing, and, as a consequence, the effort in the calibration of control parameters can be very costly and demanding.…”