Development of the predictive based control of an autonomous engine cooling system for variable engine operating conditions in SI engines: design, modeling and real-time application. (July 2020)

• Record Type: Journal Article
• Authors: Kaleli, Alirıza
• Is Part Of: Control engineering practice. Volume 100(2020)
• Publication Date: 2020-07
• Subjects: Autonomous engine cooling system -- Prediction error model -- Model predictive control -- Thermal management system; Automatic control -- Periodicals; 629.89
• DOI: 10.1016/j.conengprac.2020.104424
• Languages: English
• ISSNs: 0967-0661

Abstract

Abstract: This study includes the design of an autonomous cooling system and implementation of the system on gasoline-fueled internal combustion engine by using model predictive control (MPC) technique. The system designed with MPC provides superior performance in terms of engine thermal management compared to the conventional cooling system. This controller structure is selected because it can be easily adaptable to the multivariable control system and is relatively easy to adjust. In the first part of the study, a multi input multi output (MIMO) model for a gasoline engine cooling system is developed under different operating conditions by using system identification techniques. Then, the performance of the proposed predictive based engine cooling system is tested for both steady and transient engine operating conditions. The experimental results showed that the designed autonomous thermal management system outperforms compared to the conventional cooling system in terms of reducing fuel consumption, shortening of the engine warm-up time and improvement of the exhaust emission characteristics. Highlights: An autonomous engine cooling system is designed by using model based MPC algorithm. The model is obtained by using subspace system identification techniques. The PEM model is based on data from 1.6L SI engine for different operating regions. The designed system has decreased warm-up time, fuel consumption, exhaust emissions. Real time dyno test is performed on steady-state and transient operating conditions.