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A method for modeling the battery state of charge in wireless sensor networks

Authors :
Jose Pelegri-Sebastia
R. Lajara
Juan J. Pérez-Solano
Source :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Publication Year :
2015
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), 2015.

Abstract

In this paper we propose a method for obtaining an analytic model of the battery State-of-Charge (SoC) in wireless sensor nodes. The objective is to find simple models that can be used to estimate accurately the real battery state and consequently the node lifetime. Running the model in the network nodes, we can provide the motes with the required information to implement applications that can be considered as battery-aware. The proposed methodology reduces the computational complexity of the model avoiding complicated electrochemical simulations and treating the battery as an unknown system with an output that can be predicted using simple mathematical models. At a first stage, during a setup period, the method starts with the measurement of several battery parameters under different environmental and operational conditions. After that, the method uses the previous collected data for building mathematical models, considering the linear regression or the multilayer perceptron as the most appropriated. Finally, the models are validated experimentally with new measures. Results show the suitability of the method that produces accurate and simple models, capable of being implemented even in low-cost and very constrained real motes<br />This work was supported by the I+D+i Program, Generalitat Valenciana, through the Research and Development under Project GV05/043 and in part by the Vicerrectorado of Investigation, Development and Innovation, Universidad Politecnica de Valencia, under Grant PAID-06-06-002-61.

Details

Language :
English
Database :
OpenAIRE
Journal :
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia, instname
Accession number :
edsair.doi.dedup.....3eb34bab64270eb70c5c184be513237f