Abstract
The homogeneous charge compression ignition (HCCI) combustion engine principle lacks direct ignition timing control, instead the auto-ignition depends on the operating condition. Since auto-ignition of a homogeneous mixture is very sensitive to operating conditions, fast combustion phasing control is necessary for reliable operation. For this paper, a six-cylinder heavy-duty HCCI engine was controlled on a cycle-to-cycle basis in real time. Sensors, actuators and control structures for control of the HCCI combustion were compared. Among several actuators for HCCI engine control suggested, two actuators were compared - i.e., dual-fuel actuation and variable valve actuation (VVA). As for control principles, model predictive control (MPC) has several desirable features and today MPC can be applied to relatively fast systems, such as VVA and dual-fuel actuation. For sensor feedback control of the HCCI engine, cylinder pressure and ion current - i.e., the electronic conductive properties in the reaction zone - were compared. Combustion phasing control based on ion current was compared to control based on cylinder pressure. For the purpose of control synthesis requiring dynamic models, system identification provided models of the HCCI combustion, the models being validated by stochastic model validation. With such models providing a basis for model-based control, MPC control results were compared to PID and LQG control results. While satisfying the constraints on cylinder pressure, both control of the combustion phasing and control of load torque was achieved with simultaneous minimization of the fuel consumption and emissions.
Original language | English (US) |
---|---|
Pages (from-to) | 422-448 |
Number of pages | 27 |
Journal | International Journal of Control |
Volume | 79 |
Issue number | 5 |
DOIs | |
State | Published - May 1 2006 |
Externally published | Yes |
Bibliographical note
Funding Information:We are grateful to Xyoli Pérez-Campos (Associate Editor) and two anonymous reviewers for their critical comments on the manuscript that helped improve it. Thanks to M. M. González-Ramos for the critical reading of the manuscript and various useful remarks. The MSc Carmen M. Gómez-Arredondo received a scholarship from CONACYT and support by the Programa Integral de Fortalecimiento Institucional de la Secretaría de Educación Pública. Rocío L. Sosa-Ramírez helped with Figure 1. SSN data was obtained by the Servicio Sismológico Nacional (México) and acquisition and distribution was thanks to its personnel.
Funding Information:
We are grateful to Xyoli P?rez-Campos (Associate Editor) and two anonymous reviewers for their critical comments on the manuscript that helped improve it. Thanks to M. M. Gonz?lez-Ramos for the critical reading of the manuscript and various useful remarks. The MSc Carmen M. G?mez-Arredondo received a scholarship from CONACYT and support by the Programa Integral de Fortalecimiento Institucional de la Secretar?a de Educaci?n P?blica. Roc?o L. Sosa-Ram?rez helped with Figure 1. SSN data was obtained by the Servicio Sismol?gico Nacional (M?xico) and acquisition and distribution was thanks to its personnel.
ASJC Scopus subject areas
- Control and Systems Engineering
- Computer Science Applications