Risk measures for particle-filtering-based state-of-charge prognosis in lithium-ion batteries
| Autor: | Bin Zhang, Marcos E. Orchard, Pablo Hevia-Koch, Liang Tang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: |
Battery (electricity)
Engineering business.industry Risk measure Measure (physics) chemistry.chemical_element Reliability engineering State of charge chemistry Control and Systems Engineering Electronic engineering Lithium Electrical and Electronic Engineering business Particle filter Risk management |
| Zdroj: | IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS Artículos CONICYT CONICYT Chile instacron:CONICYT |
| Popis: | This paper presents a class of risk measures to be used as damage indicators within particle filtering (PF)-based real-time prognosis algorithms, with application to the case of state-of-charge prediction in lithium-ion batteries. The proposed risk measure not only incorporates the risk of battery failure but also is a measure for the confidence on the prognosis algorithm itself. In addition, a novel simplified PF-based prognostic method is proposed to estimate the battery discharge time, while providing a computationally inexpensive solution. Computing times for both the novel prognosis routine and the associated risk measure are fast enough to allow their implementation in real-time applications, such as decision-making systems or path-planning algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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