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- W3082652912 abstract "Use of Li-Ion batteries is increasing exponentially. The Battery Management Systems (BMSs) are used to achieve a longer battery life and to maximize its usefulness. Contemporary BMSs are complex, creating a greater overhead consumption on the battery. The purpose of this work is to improve the power efficiency of the modern BMSs. To this end the processes of level-crossing sensing and processing are used. The emphasis is on developing a reliable, efficient, and real-time technique for estimating battery cells’ state of health (SoH). Using an original event-driven approach, the SoH is approximated. Comparison of the designed system is performed with traditional equivalents. Results show an outperformance of 4.7-fold in terms of compression gain and computational efficiency while maintaining sufficient precision of the SoH estimation." @default.
- W3082652912 created "2020-09-08" @default.
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- W3082652912 date "2020-07-01" @default.
- W3082652912 modified "2023-10-14" @default.
- W3082652912 title "Level-Crossing Sampling for Li-Ion Batteries Effective State of Health Estimation" @default.
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- W3082652912 doi "https://doi.org/10.1109/ichqp46026.2020.9177915" @default.
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