Optimizing Battery Heat Management in Dusty Environments

November 3rd, 2023

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Xiaohui Feng¹, Zhenzhe Li¹, Shujiao Pang¹, Ming Ren¹, Zhenmu Chen¹

¹College of Mechanical and Electrical Engineering, Wenzhou University

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Här presenterar vi den adaptiva simulerade glödgningsmetoden (ASAM) för att optimera en approximativ kvadratisk responsytmodell (QRSM) som motsvarar ett dammigt partikeltäckt batterivärmehanteringssystem och uppfylla temperatursänkningarna genom att justera luftflödeshastigheterna genom att justera luftflödeshastigheterna kombination av systeminlopp.

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Optimizing Battery Heat Management in Dusty Environments

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