Cooling Optimization Strategy for a 6s4p Lithium-Ion Battery Pack Based on Triple-Step Nonlinear Method

Hongya Zhang, Hao Chen and Haisheng Fang ()
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Hongya Zhang: School of Energy and Power Engineering, Huazhong University of Science & Technology, Wuhan 430074, China
Hao Chen: School of Energy and Power Engineering, Huazhong University of Science & Technology, Wuhan 430074, China
Haisheng Fang: School of Energy and Power Engineering, Huazhong University of Science & Technology, Wuhan 430074, China

Energies, 2022, vol. 16, issue 1, 1-31

Abstract: In a battery cooling system, by adopting a cooling optimization control strategy, the battery temperature under different external environments and load currents can be adjusted to ensure performance and safety. In this study, two modes of the thermal management system are established for the 6s4p (six serial and four parallel batteries in a stage) battery pack. A single particle model, considering battery aging, is adopted for the battery. Furthermore, a cooling optimization control strategy for the battery is proposed based on the triple-step nonlinear method, and then the optimization effect is validated under two C-rate charge–discharge cycles, NEDC cycles, and US06 cycles. Moreover, an extended PID control strategy is constructed and compared with the triple-step nonlinear method. A comparison of pump power, thermal behavior, and aging performance indicate parallel cooling is more advantageous. This verifies the validity of the triple-step nonlinear method and shows its advantages over the extended PID method. The present study provides a method to investigate the thermal behavior and aging performance of a battery pack in a BTM system, and fills in the research gaps in the cooling optimization control strategy for battery packs.

Keywords: Li-ion battery; battery thermal management; triple-step nonlinear method; extended PID method; cooling optimization (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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