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An analytical model to estimate the state of charge and lifetime for batteries with energy harvesting capabilities
Author(s) -
Rodrigues Leonardo M.,
Bitencourt Nathália L.,
Rech Luciana,
Montez Carlos,
Moraes Ricardo
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.5269
Subject(s) - energy harvesting , battery (electricity) , context (archaeology) , state of charge , energy (signal processing) , computer science , power (physics) , voltage , energy storage , electrical engineering , engineering , reliability engineering , physics , quantum mechanics , paleontology , statistics , mathematics , biology
Summary Energy limitation is one of the major bottlenecks during the operation of many emerging applications, such as electric vehicles, water and gas meters and a number of sensors used in the context of the Internet of Things and cyber‐physical systems. Energy harvesting techniques have arisen as a promising solution to minimize the energy issues found in these types of application domains. In energy harvesting systems, a critical challenge is the need to use battery models capable of accurately estimating both the input and output power of batteries. This article proposes a temperature‐dependent analytical battery model capable of estimating some output quantities — for example, state of charge, voltage and lifetime — of batteries that use energy harvesting technologies. This model was validated by comparing its analytical results with a dataset called the Randomized Battery Usage Data Set, which is available at the data repository of the National Aeronautics and Space Administration (NASA) website. It is also presented a proof‐of‐concept application, demonstrating that the use of these technologies can serve as an effective means to extend the operating time of batteries, resulting in significant benefits for a number of applications.