| 1. |
- Li, Kai, et al.
(author)
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A novel engine and battery coupled thermal management strategy for connected HEVs based on switched model predictive control under low temperature
- 2023
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In: Energy. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0360-5442 .- 1873-6785. ; 278
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Journal article (peer-reviewed)abstract
- Under a low-temperature environment, electric vehicles face serious environmental adaptability problems, and efficient vehicle thermal management strategies are urgently needed. This paper presents a novel engine- battery coupled thermal management strategy for connected hybrid electric vehicles (HEVs). An improved system structure for an engine-battery coupled thermal management system (engine-battery CTMS) is designed to avoid unnecessary heat loss. The control requirements of the engine-battery CTMS include minimum engine fuel consumption, minimum power battery aging damage and minimum system energy consumption, which constitutes a multi-objective optimal control problem in a finite time domain. Based on model predictive control (MPC) theory, a switched nonlinear MPC (NMPC) control strategy is proposed to solve the optimal control problem of the complex coupled multi-input multi-output system. To verify the effectiveness of the proposed strategy, three comparative experiments of the centralized NMPC-based and rule-based methods combined with the improved system structure and the unimproved system structure are designed. The results of the cosimulation experiment between MATLAB/Simulink and AMEsim under various driving cycles and different ambient temperatures show that the improved structure and switched control strategy confer great advantages in reducing the controller computation burden, engine fuel consumption, and power battery aging damage.
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| 2. |
- Li, Kai, et al.
(author)
-
An advanced control strategy for engine thermal management systems with large pure time delay
- 2023
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In: Applied Thermal Engineering. - : PERGAMON-ELSEVIER SCIENCE LTD. - 1359-4311 .- 1873-5606. ; 224
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Journal article (peer-reviewed)abstract
- Stable and precise temperature control can effectively improve the engines 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 oC, and the temperature adjustment time is within 100 s after the first overshoot.
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