A low temperature preheating strategy with optimized fuzzy controller for lithium-ion batteries. (1st August 2022)

• Record Type: Journal Article
• Authors: Huang, Zhiwu; Gao, Zhiwei; Liu, Yongjie; Guan, Kaifu; Lu, Yao; Zhou, Feng; Jiang, Fu; Peng, Jun
• Is Part Of: Journal of energy storage. Volume 52:Part A(2022)
• Publication Date: 2022-08-01
• Subjects: Electric vehicles -- Lithium-ion batteries -- Optimal pulse preheating strategy -- Fuzzy logic control -- Genetic algorithm; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2022.104709
• Languages: English
• ISSNs: 2352-152X

Abstract

Abstract: Electric vehicles (EVs) suffer from significant performance loss under low temperatures due to the limited operating temperature ranges of lithium-ion batteries. Warming up the cells before the operation is recommended by manufacturers to recover effective drive for EVs rapidly. In this paper, an optimized internal pulse preheating strategy is proposed to realize the cold start of vehicles without other ground power sources. First, an electro-thermal model of batteries is established, which can dynamically update based on the current state of charge and temperature of cells. Then the internal preheating pulse currents are obtained by using fuzzy logic control with a fixed frequency. The bidirectional pulse amplitudes are decided by the real-time state of charge and temperature in the rule-based framework. Furthermore, an offline genetic algorithm is used to optimize the fuzzy rules with the updated impedance parameters to reduce energy consumption and preheating time. Experiments are conducted with different battery initial states of charge to evaluate the superiority of the proposed strategy. Results show that the battery can achieve a temperature rise from −10 °C to 10 °C in 603 s though the state of charge is at a low level, with the temperature rise above 2 °C/min. Besides, compared with current preheating strategies, the proposed strategy can at least shorten the preheating time by 15% and save the energy loss by 10%. Highlights: An efficient and fast internal heating method is devised for lithium-ion batteries. Battery model parameters recognition accuracy in low-temperature environments is improved. A fuzzy control-based battery pulse current heating approach is developed. Multiple sets of fuzzy control parameters are optimized based on the genetic algorithm. Validation results denote the improved heating speed and energy economy.