Design considerations for solar energy harvesting wireless embedded systems
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Micro power meter for energy monitoring of wireless sensor networks at scale
Proceedings of the 6th international conference on Information processing in sensor networks
Software-based on-line energy estimation for sensor nodes
Proceedings of the 4th workshop on Embedded networked sensors
Design, Modeling, and Capacity Planning for Micro-solar Power Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Battery Lifetime Prediction Model for a WSN Platform
SENSORCOMM '10 Proceedings of the 2010 Fourth International Conference on Sensor Technologies and Applications
GPS-Equipped wireless sensor network node for high-accuracy positioning applications
EWSN'12 Proceedings of the 9th European conference on Wireless Sensor Networks
ScanTraffic: smart camera network for traffic information collection
EWSN'12 Proceedings of the 9th European conference on Wireless Sensor Networks
Power management for long-term sensing applications with energy harvesting
Proceedings of the 1st International Workshop on Energy Neutral Sensing Systems
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Batteries play an integral role in Wireless Sensor Networks as they provide the energy necessary to operate the individual sensor nodes. In order to extend the network's lifetime, and theoretically permit continuous operation even for systems with high-energy consumption, environmental energy harvesting has attracted much interest. It has been shown that the motes' utility can be improved significantly if run-time knowledge of remaining battery capacity is available. In this work, a light-weight and cost effective approach to approximating the battery state-of-charge (SOC) based on voltage measurements is presented. Despite commonly perceived as inferior to other approaches, a performance evaluation shows that SOC approximations with over 95% accuracy are possible. It is further shown that battery inefficiencies due to e.g., temperature and aging are taken into consideration despite not explicitly modeling these effects. The approach only requires system input voltage measurements, but benefits from optional current and temperature measurements.