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Modelling the recovery effect in batteries and supercapacitors for wearable sensors: discovering the existence of hidden time constants

Arora, H. (2018) Modelling the recovery effect in batteries and supercapacitors for wearable sensors: discovering the existence of hidden time constants. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00077542

Abstract/Summary

Wearable devices, including health care monitors and aids, are very popular and extremely pervasive. They allow a user to sense physiological parameters and movement, can process sensed data to derive contextualised information, and also communicate with the wider world to allow remote health monitoring and enable health interventions. The inevitable march of technological invention pushes wearables to have more functionality, process more and sense more. As such, the demands on their power source increases. However, users demand small and lightweight wearable devices which place physical constraints on the power source, thus limiting the available power. To address these two conflicting positions, it seems sensible to consider ways to manage the wearable power source intelligently. It becomes absolutely vital to effectively utilise all the available power for device longevity between charges. Rechargeable batteries are popular in wearable devices. While rechargeable batteries have good energy density, their charge rate can be limited and they can be relatively heavy. Supercapacitors are likely to also be adopted as power sources for wearable sensors; in particular where the sensor mechanism relies on energy harvesting. A specific advantage of supercapacitors over batteries is their maintained performance over large numbers of discharge cycles and they are relatively light weight. It is known in the literature that the electrochemical recovery effect can enable the extraction of more power from the battery when implementing idle times in between discharge cycles, and it has been used to develop various power management techniques. However, there is no evidence concerning the actual increase in available power that can be obtained by exploiting the recovery effect. Also, this property cannot be generalised across all battery chemistries since it is an innate phenomenon, relying on the anode/cathode material. Indeed recent developments suggest that recovery effect does not exist at all. This thesis examines the recovery effect in batteries and presents controlled experiments and results, to verify the presence, and level, of the recovery effect in commonly used battery chemistries that are typically found in wearable sensors and healthcare devices. While the literature analysed the recovery effect using active current and zero discharge current, this work has identified that wearable devices still have a small current drawn from the power source when in idle mode, therefore a novel active and idle discharge circuit was designed to model the recovery effect in the typical operation of wearable devices. The results have revealed that the recovery effect significantly does exist in certain batteries, and a novel contribution from this research has been the identification that the recovery response can be modelled using two different time constants. The time constants reflect the difference in charge carrier movement from the available charge well and the bounded charge well leading to the proposal from this work to model the recovery effect using a two-tank model. This novel finding has important implications for the development of power management techniques that utilise the recovery effect, with application in a large range of battery operated devices. Furthermore, this thesis also has examined the recovery effect in supercapacitors and has for the first time demonstrated that the recovery effect also exists in supercapacitors.

Item Type:Thesis (PhD)
Thesis Supervisor:Sherratt, R. S. and Harwin, W.
Thesis/Report Department:School of Biological Sciences
Identification Number/DOI:https://doi.org/10.48683/1926.00077542
Divisions:Life Sciences > School of Biological Sciences
ID Code:77542
Additional Information:Content of appendices #1 & #3 redacted due to copyright

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