Wang, Tuo (Beijing Institute of Technology), Huang, Ying (Beijing Institute of Technology), Zhang, Zhenyu (Beijing Institute of Technology), Wang, Xu (Beijing Institute of Technology)

Triple Wiebe Combustion Model Parameters Identification Using Combined Genetic and Levenberg-Marquardt Algorithm

Scheduled for presentation during the Regular session "Engine control system" (MoBT1), Monday, August 23, 2021, 16:50−17:10, Room T1

6th IFAC Conference on Engine and Powertrain Control, Simulation and Modeling, August 23-25, 2021, Tokyo, Japan

This information is tentative and subject to change. Compiled on May 4, 2024

Abstract

Combustion models are the core of diesel engine performance simulation, and zero-dimensional combustion models are widely used in the field of model-based diesel engine control because of the advantage of fast computing speed. The computational accuracy of the zero-dimensional combustion model is mainly determined by the model parameters, so it is necessary to study the process of combustion model parameter identification. This paper demonstrates the process of heat release parameterization based on the Triple Wiebe combustion model, which consists of four main parts: heat release rate acquisition, model parameter selection, parameter identification, and result calibration. To enable fast and accurate parameter identification, a Combined Genetic and Levenberg-Marquardt algorithm is proposed, which has both the global search capability of the genetic algorithm and the fitting speed of the Levenberg-Marquardt algorithm. The new algorithm was tested on the basis of engine transient experimental data, and the results showed that it could achieve the required accuracy within a less number of iterations.