Abstract
Over the years, lithium–ion batteries have developed as a key enabling technology for the green transition. Although many of these batteries’ characteristics, such as energy density, power capability, and cost, have gradually improved, uncertainties remain concerning their performance over their lifetimes. Thus, to ensure reliable and efficient battery operation, the battery's available performance, known as its state of health (SOH), must be known at every moment. This chapter introduces the most common battery SOH estimation methods, from direct measurements to deep neural networks, discussing their key performance metrics, advantages, and drawbacks.
Originalsprog | Engelsk |
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Titel | Control of Power Electronic Converters and Systems : Volume 4 |
Redaktører | Frede Blaabjerg |
Antal sider | 48 |
Vol/bind | 4 |
Forlag | Elsevier |
Publikationsdato | 1 jan. 2024 |
Udgave | 1 |
Sider | 383-430 |
Kapitel | 13 |
ISBN (Trykt) | 9780323856232 |
ISBN (Elektronisk) | 9780323856225 |
DOI | |
Status | Udgivet - 1 jan. 2024 |