High-power lithium-ion battery (LIB) applications, such as electric racing cars and electric vertical take-off and landing (eVTOL) aircrafts, are growing rapidly. Degradation in LIBs such as lithium plating, particle cracking, and SEI breakdown is accelerated at high C-rate at different temperatures and depth-of-discharges (DOD); however, high-power cells are designed to better withstand these operating conditions as compared to high-energy cells. Despite this, publicly available datasets of high-power batteries are limited. In this work, we present a characterization dataset of 12 high-power NMC cells which includes capacity tests, high C-rate pulse tests, and impedance tests, all of which are conducted at temperature set points of 5 °C, 25 °C, and 40 °C. Additionally, the dataset captures cell-to-cell variations, enabling the development of stochastic battery models that account for parameter uncertainty and its impact on the cell terminal voltage.
High-power lithium-ion battery characterization dataset for stochastic battery modeling / Khan, Muhammad Aadil; Thatipamula, Sai; Tresca, Luigi; Xu, Le; Trewartha, Amalie; Onori, Simona. - In: SCIENTIFIC DATA. - ISSN 2052-4463. - ELETTRONICO. - 12:1(2025). [10.1038/s41597-025-05725-y]
High-power lithium-ion battery characterization dataset for stochastic battery modeling
Tresca, Luigi;
2025
Abstract
High-power lithium-ion battery (LIB) applications, such as electric racing cars and electric vertical take-off and landing (eVTOL) aircrafts, are growing rapidly. Degradation in LIBs such as lithium plating, particle cracking, and SEI breakdown is accelerated at high C-rate at different temperatures and depth-of-discharges (DOD); however, high-power cells are designed to better withstand these operating conditions as compared to high-energy cells. Despite this, publicly available datasets of high-power batteries are limited. In this work, we present a characterization dataset of 12 high-power NMC cells which includes capacity tests, high C-rate pulse tests, and impedance tests, all of which are conducted at temperature set points of 5 °C, 25 °C, and 40 °C. Additionally, the dataset captures cell-to-cell variations, enabling the development of stochastic battery models that account for parameter uncertainty and its impact on the cell terminal voltage.Pubblicazioni consigliate
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https://hdl.handle.net/11583/3002812
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