State-of-charge estimation to improve energy conservation and extend battery life of wireless sensor network nodes

Quintero, Vanessa; Estevez, Claudio; Orchard, Marcos E.

doi:10.1109/icufn.2017.7993766

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…The state‐space model is defined according to (1)–(3). Since the voltage is constrained, the measurement equation proposed in [3, 5] is simplified, and it is defined according to (3). In this state‐space model,

x_{1}

is associated to an unknown parameter related to the internal impedance of the battery,

x_{2}

corresponds to the SOC measurement,

i false(k false)

and

v false(k false)

refer to the current and voltage of the battery,

ω_{1} false(k false)

and

ω_{2} false(k false)

are the process noises, and

n false(k false)

is the observation noise.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, two methodologies are used to estimate the SOC based on the OCV curve. The first methodology was presented in [3, 5] and in this article is referred as

M_{1}

(although the OCV curve is constrained as explained previously). In

M_{1}

the SOC estimation is based on the Particle Filter and it uses the model described in (1)–(3) to characterise the battery behaviour.…”

Section: Methodsmentioning

confidence: 99%

“…The design of MAC protocols with dynamic operating cycles is one of the techniques implemented for the conservation of energy in WSNs. Several MAC protocols incorporate information from the battery [2,3], where two different techniques can be used to estimate the amount of energy remaining in the battery. The SOC can be defined as the amount of energy that a battery can deliver until it reaches its End-of-Discharge (EoD) time [4].…”

mentioning

confidence: 99%

“…Methodology: Currently, various models have been proposed to characterise the battery behaviour when discharging, as physical, empirical, abstract, electrochemical, electrical, and stochastic. The first step of the proposed methodology is to simplify the empirical battery model presented in [3,5]. This model uses the open circuit voltage (OCV) curve to establish the measurement equation, which is the equation that allows updating the voltage values to adjust the SOC estimation.…”

mentioning

confidence: 99%

See 3 more Smart Citations

State‐of‐charge estimation to improve decision making by MAC protocols used in WSNs

Quintero¹,

Pérez²,

Estevez³

et al. 2019

Electron. lett.

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Energy conservation is a topic of great interest in wireless sensor networks (WSNs). Various techniques have been proposed to minimise the energy consumption. One approach is to design medium access control (MAC) protocols capable of adjusting the sensor node cycle according to the available energy in the battery. The state of charge (SOC) is an indicator of the available energy stored in the battery before discharging. This work proposes a simplified battery model to estimate the SOC and compares the accuracy and computational load of the algorithm as metrics for the implementation of the MAC protocol design.

show abstract

x_{1}

is associated to an unknown parameter related to the internal impedance of the battery,

x_{2}

corresponds to the SOC measurement,

i false(k false)

and

v false(k false)

refer to the current and voltage of the battery,

ω_{1} false(k false)

and

ω_{2} false(k false)

are the process noises, and

n false(k false)

is the observation noise.…”

Section: Methodsmentioning

confidence: 99%

“…In this work, two methodologies are used to estimate the SOC based on the OCV curve. The first methodology was presented in [3, 5] and in this article is referred as

M_{1}

(although the OCV curve is constrained as explained previously). In

M_{1}

the SOC estimation is based on the Particle Filter and it uses the model described in (1)–(3) to characterise the battery behaviour.…”

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

State‐of‐charge estimation to improve decision making by MAC protocols used in WSNs

Quintero¹,

Pérez²,

Estevez³

et al. 2019

Electron. lett.

View full text Add to dashboard Cite

show abstract

“…SoC can be expressed as a percentage of some reference, i.e., the capacity when the battery was completely charged. It can be estimated applying mathematical models generated using a combination of different battery parameters [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Predicting the Batteries' State of Health in Wireless Sensor Networks Applications

Lajara

Pérez-Solano

Pelegrí-Sebastiá

2018

IEEE Trans. Ind. Electron.

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The lifetime of wireless sensor networks deployments depends strongly on the nodes battery state of health. It is important to detect promptly those motes whose batteries are affected and degraded by ageing, environmental conditions, failures, etc. There are several parameters that can provide significant information of the battery state of health, such as: the number of charge/discharge cycles, the internal resistance, voltage, drained current, temperature, etc. The combination of these parameters can be used to generate analytical models capable of predicting the battery state of health. The generation of these models needs a previous process to collect dense data traces with sampled values of the battery parameters during a large number of discharge cycles under different operating conditions. The collected data allow the development of mathematical models that can predict the battery state of health. These models are required to be simple because they must be executed in motes with low computational capabilities. The article shows the complete process of acquiring the training data, the models generation and its experimental validation using rechargeable batteries connected to Telosb motes. The obtained results provide significant insight of the battery state of health at different temperatures and charge/discharge cycles.

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On-line WSN SoC estimation using Gaussian Process Regression: An Adaptive Machine Learning Approach

Ali¹,

Ishak²,

Ahmed³

et al. 2022

Alexandria Engineering Journal

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State-of-charge estimation to improve energy conservation and extend battery life of wireless sensor network nodes

Cited by 10 publications

References 25 publications

State‐of‐charge estimation to improve decision making by MAC protocols used in WSNs

State‐of‐charge estimation to improve decision making by MAC protocols used in WSNs

Predicting the Batteries' State of Health in Wireless Sensor Networks Applications

On-line WSN SoC estimation using Gaussian Process Regression: An Adaptive Machine Learning Approach

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