VRLA battery state-of-charge estimation in telecommunication power systems

Anbuky, A.H.; Pascoe, P.E.

doi:10.1109/41.847897

Cited by 83 publications

(28 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Deactivate charge Activate discharge (see Figure 10) battery behaviour [1][2][3][4][15][16][17][18][19]. Through the use of the system, several models have been developed [17][18][19] and a greater understanding of battery behaviour has been achieved, especially within the poorly understood coup de fouet region [1][2][3][4]15,16,19].…”

Section: Resultsmentioning

confidence: 99%

Automated battery test system

Pascoe¹,

Anbuky²

2003

Measurement

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Automated battery test system

Pascoe¹,

Anbuky²

2003

Measurement

View full text Add to dashboard Cite

“…The aforementioned methods are not suitable for online and continuous monitoring, as required in hybrid renewable energy systems, because they require a long stabilisation period [52]. For lead acid batteries, B SOC is linearly proportional to its discharge voltage [49,53]. Therefore, in this work, the battery's terminal voltage is used as an approximation of the B SOC .…”

Section: Lead Acid Battery Bank and Modelmentioning

confidence: 98%

Predictive power management strategies for stand-alone hydrogen systems: Lab-scale validation

Brka

Kothapalli

Al-Abdeli

2015

International Journal of Hydrogen Energy

View full text Add to dashboard Cite

“…Several battery life estimation algorithms have been proposed based on electro-chemical models (including Peukert's equation), equivalent circuit models, hydrodynamic models, finite element models, tabulated data models, and even neural networks; see for example [20]. Our goal is neither to propose a new battery depletion model nor develop a new battery life estimation algorithm.…”

Section: Energy Consumption Modelmentioning

confidence: 99%

Pitfalls in energy consumption evaluation studies

Pentikousis

2009

2009 6th International Symposium on Wireless Communication Systems

View full text Add to dashboard Cite

Abstract-Energy consumption is fast emerging as a central item of research for the Future Internet (FI).In an environment where the majority of users access next generation networks using battery-powered devices, energy efficiency is of equal importance to other well-established metrics of overall system and protocol performance. Nevertheless, we still lack benchmarks of what constitutes energy efficient operation in mobile computing and networking. In particular, models that accurately quantify transport protocol energy consumption are in short supply. This paper introduces a blueprint for a configurable and extensible energy consumption model which takes battery depletion and recovery characteristics into consideration. We show that the non-linear nature of battery depletion cannot be ignored in energy consumption evaluation studies. Battery recovery effects should be accounted for as well. We explore the potential gains in different TCP variants using our model and illustrate that data-counting and time-counting are not sufficient methods for assessing the energy efficiency of transport protocols operating on devices with fixed-energy sources.

show abstract

VRLA battery state-of-charge estimation in telecommunication power systems

Cited by 83 publications

References 4 publications

Automated battery test system

Automated battery test system

Predictive power management strategies for stand-alone hydrogen systems: Lab-scale validation

Pitfalls in energy consumption evaluation studies

Contact Info

Product

Resources

About