| Summary: | This thesis describes VRLA battery behavioural prediction models for extracting reserve time, state of
health (SOH) and reserve life knowledge. A model for simulating battery discharge behaviour is also
described. The research is focussed primarily on the standby VRLA battery such as that commonly
employed by the telecommunications industry.
Two approaches have been developed for extracting reserve time knowledge. The first utilises a
discharge voltage versus reserve charge characteristic. This characteristic robust against modest
variations in operating conditions and is reasonably robust against deterioration in battery SOH. To
cater for different battery types an adaptive approach has been developed which also allows more
accurate reserve time estimations for batteries with deteriorated SOH. It has been determined that
reserve charge and therefore reserve time can be estimated to an accuracy of within ±10% after
approximately 10% into a discharge.
The second approach utilises a unified characteristic, which enables the direct estimation of reserve
time. It has the advantage over the approach based on the voltage versus reserve charge characteristic
that it is not battery type specific. It is also more tolerant to changes in battery SOH. This comes at
the disadvantage of greater initial estimation error, although the error reduces significantly throughout
the discharge. This approach is less capable of dealing with stepped discharge rates or the discharging
of partially charged batteries compared to the model based on the voltage versus SOC characteristic.
Both approaches can also be used to obtain estimates of capacity, the primary battery SOH indicator.
In addition battery SOH knowledge can be obtained from the coup de fouet region. This region is
influenced by battery operating conditions as well as battery SOH. Various techniques for extracting
SOH knowledge from the coup de fouet region are described. By incorporating the coup de fouet SOH
estimation approach with the previous approaches, along with circumstantial knowledge obtained by
monitoring (voltage, current and temperature) base parameters, reserve operational life can be
estimated, The combination of approaches also enables the construction of a battery discharge
simulation model.
|
|---|
