Article,
Model prediction for ranking lead-acid batteries according to expected lifetime in renewable energy systems and autonomous power-supply systems
Journal of Power Sources, (2007)
Abstract
Predicting the lifetime of lead-acid batteries in applications with
irregular operating conditions such as partial state-of-charge cycling,
varying depth-of-discharge and different times between full charging
is known as a difficult task. Experimental investigations in the
laboratory are difficult because each application has its own specific
operation profile. Therefore, an experimental investigation is necessary
for each application and, moreover, for each operation strategy.
This paper presents a lifetime model that allows comparison of the
impact of different operating conditions, different system sizing
and different battery technologies on battery lifetime. It is a tool
for system designers and system operators to select appropriate batteries,
to do a proper system design (sizing of the battery, power generators
and loads), and to implement an optimized operation strategy (end-of-charge
voltage, frequency of full charging, gassing periods, maximum depth-of-discharge).
The model is a weighted Ah throughput approach based on the assumption
that operating conditions are typically more severe than those used
in standard tests of cycling and float lifetime. The wear depends
on the depth-of-discharge, the current rate, the existing acid stratification,
and the time since the last full charging. The actual Ah throughput
is continuously multiplied by a weight factor that represents the
actual operating conditions. Even though the modelling approach is
mainly heuristic, all of the effects that are taken into account
are based on a detailed analysis and understanding of ageing processes
in lead-acid batteries. The ânormalâ user can adapt the model
to different battery types simply from the data sheet information
on cycle lifetime and float lifetime.
