A novel multistage constant compressor speed control strategy of electric vehicle air conditioning system based on genetic algorithm. (15th February 2022)

• Record Type: Journal Article
• Authors: Huang, Xianghui; Li, Kuining; Xie, Yi; Liu, Bin; Liu, Jiangyan; Liu, Zhaoming; Mou, Lunjie
• Is Part Of: Energy. Volume 241(2022)
• Publication Date: 2022-02-15
• Subjects: Electric vehicles -- air conditioning system -- Control strategy -- Genetic algorithm -- Energy saving -- Multistage constant compressor speed; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.122903
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This study establishes a passenger cabin-coupled air conditioning model that the heat exchangers adopted in the air conditioning model, are calibrated by testing, during which the parameters for establishing the passenger cabin model are measured. The cabin temperature simulation results of the air conditioning model proposed in this paper fit well with the test results, with a maximum difference of 3 °C. A genetic algorithm (GA) optimization-based multistage constant-compressor speed (MCCS) air conditioning system control strategy is proposed. This control strategy sets the cabin temperature as the input control factor and the compressor speed as the output factor, and different cabin temperature ranges correspond to the MCCSs, which are optimized by the GA. The presented strategy is contrasted with the most commonly used on/off controllers and the proportional integral derivative (PID) controller, and an engineering-applied (EA) air conditioning control strategy. The proposed controller can maintain passenger cabin thermal comfort and save energy simultaneously, and it can be easily applied in engineering. Based on the simulation results, the MCCS controller can save 17.5, 7.5, and 5.8% more energy consumption than the on/off, PID, and EA controllers. Moreover, it can improve the coefficient of performance of the air conditioning system by 5.3 and 3.9% more than the PID and EA controllers. Therefore, the proposed MCCS controller can increase the operation efficiency of electric vehicles AC system. Graphical abstract: Image 1 Highlights: A genetic algorithm optimization based adaptive multistage constant compressor speed controller for AC system is built. Thermal model of the AC system coupled with passenger cabin is validated by experimental test. The proposed controller is compared with an engineering applied controller and it is easy to apply in engineering. The proposed controller can keep the passenger cabin thermal comfort and save energy simultaneously.