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 cyberphysical 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 quantitiesfor example, state of charge, voltage and lifetimeof 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. K E Y W O R D Swireless sensor network, battery modelling, energy harvesting, thermal effect