An advanced control strategy for engine thermal management systems with large pure time delay. (April 2023)

• Record Type: Journal Article
• Authors: Li, Kai; Chen, Hong; Zhao, Jing; Eriksson, Lars; Gao, Jinwu
• Is Part Of: Applied thermal engineering. Volume 224(2023)
• Publication Date: 2023-04
• Subjects: Advanced engine thermal management system (AETMS) -- Disturbance estimator -- Pure time delay -- State predictor -- Energy consumption optimization; Heat engineering -- Periodicals; Heating -- Equipment and supplies -- Periodicals; Periodicals; 621.40205
• DOI: 10.1016/j.applthermaleng.2023.120084
• Languages: English
• ISSNs: 1359-4311

Abstract

Abstract: Stable and precise temperature control can effectively improve the engine's fuel consumption and emissions. An advanced engine thermal management system (AETMS) composed of electric actuators has great potential in increasing the temperature tracking control accuracy and decreasing the system energy consumption. Time-varying disturbance and pure time delay in the system make it challenging to harmoniously control multiple actuators to ensure efficient temperature tracking performance. In addition, a reasonable power distribution of the actuators is beneficial to reduce the parasitic energy consumption of the system and further improve the system efficiency. In this article, an adaptive optimization control strategy consisting of a state predictor, a disturbance estimator, an energy consumption optimization block and a state tracking controller is proposed for the temperature tracking and energy consumption optimization of AETMS. Experimental verification was performed on a range extender bench of an extended-range electric vehicle, and the results show that the system achieves high-precision temperature control and energy consumption near the theoretical optimal value under changing working conditions. The temperature steady-state error is within 0.3 o C, and the temperature adjustment time is within 100 s after the first overshoot. Highlights: Both the temperature tracking and energy consumption optimization are considered. A novel state predictor is designed to estimate the system state. A disturbance estimator is designed to estimate the system unknown disturbance. Accurate engine temperature control performance is achieved. The system energy consumption is close to the theoretical optimal value.