Tools
Tools
Shi, Y, Yu, DL, Tian, Y and Shi, Y (2015) Modified Volterra model-based non-linear model predictive control of IC engines with real-time simulations. Transactions of the Institute of Measurement and Control, 39 (2). pp. 208-223. ISSN 0142-3312
|
Text
Modified Volterra model-based non-linear model predictive control of IC engines with real-time simulations.pdf - Accepted Version Download (2MB) | Preview |
Abstract
Modelling of non-linear dynamics of an air manifold and fuel injection in an internal combustion (IC) engine is investigated in this paper using the Volterra series model. Volterra model-based non-linear model predictive control (NMPC) is then developed to regulate the air–fuel ratio (AFR) at the stoichiometric value. Due to the significant difference between the time constants of the air manifold dynamics and fuel injection dynamics, the traditional Volterra model is unable to achieve a proper compromise between model accuracy and complexity. A novel method is therefore developed in this paper by using different sampling periods, to reduce the input terms significantly while maintaining the accuracy of the model. The developed NMPC system is applied to a widely used IC engine benchmark, the mean value engine model. The performance of the controlled engine under real-time simulation in the environment of dSPACE was evaluated. The simulation results show a significant improvement of the controlled performance compared with a feed-forward plus PI feedback control.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Science & Technology; Technology; Automation & Control Systems; Instruments & Instrumentation; Air-fuel ratio control; IC engines; Volterra model; non-linear model predictive control; real-time simulations; OBSERVER; ALGORITHM; NETWORKS |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics |
| Divisions: | Engineering |
| Publisher: | Sage |
| Related URLs: | |
| Date Deposited: | 05 Nov 2018 11:56 |
| Last Modified: | 04 Sep 2021 02:16 |
| DOI or ID number: | 10.1177/0142331215604893 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/9610 |
 |
View Item |