Date of Award
11-28-2018
Publication Type
Doctoral Thesis
Degree Name
Ph.D.
Department
Electrical and Computer Engineering
Keywords
Data-driven Optimization, Extremum Seeking Control, Field Programmable Gate Array, Internal Combustion Engine, Nonlinear System Modeling, Real-time Control
Supervisor
M. Zheng
Supervisor
X. Chen
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
The incorporation of electronic components into modern Internal Combustion, IC, engine systems have facilitated the reduction of fuel consumption and emission from IC engine operations. As more mechanical functions are being replaced by electric or electronic devices, the IC engine systems are becoming more complex in structure. Sophisticated control strategies are called in to help the engine systems meet the drivability demands and to comply with the emission regulations. Different model-based or data-driven algorithms have been applied to the optimization and control of IC engine systems. For the conventional model-based algorithms, the accuracy of the applied system models has a crucial impact on the quality of the feedback system performance. With computable analytic solutions and a good estimation of the real physical processes, the model-based control embedded systems are able to achieve good transient performances. However, the analytic solutions of some nonlinear models are difficult to obtain. Even if the solutions are available, because of the presence of unavoidable modeling uncertainties, the model-based controllers are designed conservatively.
Recommended Citation
Tan, Qingyuan, "Model-Guided Data-Driven Optimization and Control for
Internal Combustion Engine Systems" (2018). Electronic Theses and Dissertations. 7625.
https://scholar.uwindsor.ca/etd/7625