Search results
26 sie 2022 · It combines the advantages of machine learning methods, by inferring model structure and parameters from aging data without requiring domain knowledge, and semi-empirical approaches, by providing potentially interpretable mathematical functions, comparable to state-of-the-art cell aging models.
1 lis 2020 · In this study, an accelerated aging experimental system that is capable of collecting aging data and enables condition monitoring in real-time is designed, and a RUL estimation on IGBT using LSTM is introduced in detail.
Accelerated aging test (AAT) is required to efficiently evaluate the operating life of lithium-ion batteries (LiB). It can partially substitute traditional aging test which typically lasts for thousands of LiB charge/discharge cycles.
12 paź 2024 · A clinically useful characterization of the cognitive aging process requires the development of valid and robust behavioral tests, with an emphasis on explaining and understanding typical...
1 gru 2022 · An integrated framework of ageing mechanisms and data-driven methods (IFAMDM) is introduced for lithium-ion battery accelerated ageing diagnosis. Highly adaptable features reflecting the...
1 cze 2024 · In this paper, in order to make the aging prediction model both highly precise and stable when facing various usage scenarios, we propose a multidimensional software aging prediction method based on ensemble learning (MSAP).
Accelerated aging is testing that uses aggravated conditions of heat, humidity, oxygen, sunlight, vibration, etc. to speed up the normal aging processes of items. It is used to help determine the long-term effects of expected levels of stress within a shorter time, usually in a laboratory by controlled standard test methods.
