Real-time combustion parameter estimation algorithm for light-duty diesel engines using in-cylinder pressure measurement

Abstract

This paper proposes a real-time estimation algorithm of combustion parameters for the location of 50% of mass fraction burnt (MFB50), and indicated mean effective pressure (IMEP). The proposed estimation algorithm uses the difference pressure only instead of the in-cylinder pressure for calculation of the combustion parameters. Since the difference pressure is the pressure that is generated only by the combustion, it occurs between the start of combustion (SOC) and the end of combustion (EOC); this allows the proposed algorithm to estimate the combustion parameters with fewer cylinder pressure data samples and low computational load compared with the conventional method. The proposed algorithm estimates the IMEP with a result acquired during the MFB50 calculation and that can significantly reduce the computational load required to calculate the combustion parameters. Consequently, the proposed estimation algorithm requires only 51% of the execution time to calculate the combustion parameters compared to the conventional method. The proposed estimation algorithm is validated with an engine experiment under 131 operating conditions that showed high linear correlation with the original combustion parameters. In-cylinder pressure based combustion control using the estimated combustion parameters is introduced as a case study and the proposed estimation algorithm validated its significant potential for real-time applications. (C) 2013 Elsevier Ltd. All rights reserved.This work was financially supported by the Ministry of Education, Science and Technology through the BrainKorea 21 Program (201000000000173), the Ministry of Knowledge Economy (MKE) and the Korea Institute for Advancement in Technology (KIAT) through the Workforce Development Program in Strategic Technology, the Energy Resource R&D program (2006ETR11P091C) under the Ministry of Knowledge Economy (MKE), the National Research Foundation of Korea (NRF) grant funded by the Korea government (MEST) (No. 2011-0017495), the Industrial Strategy Technology Development Program of Ministry of Knowledge Economy (MKE) (No. 10039673), and the Industrial Strategy Technology Development Program of Ministry of Knowledge Economy (MKE) (No. 10042633)