Battery Ageing, Nb. of cycles |
  
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Battery Ageing, Nb. of cycles |
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The battery ageing is made of 2 contributions:
Static ageing
This is the "fatal" ageing, arising whatever the battery is in use or not.
With Lead-acid batteries, this is mainly related to the sulfatation of the electrodes, and the stratification of the electrolyte (except Gel technologies). It depends on many factors: maintenance, temperature (above 25°C, reduced by a factor of 2 for each 10°C increase), deep discharges.
We don't have much information about the static degradation of Li-Ion batteries.
Operating ageing
The second component is related to the use of the battery.
Ideally a battery will be able to store a given quantity of energy during its life. This is expressed by the manufacturers as number of cycles, for some given DOD (depth of discharge). As an example, a battery will be able to provide 6000 cycles at 20% DOD, or 3000 cycles at 40% DOD, or 2000 cycles at 60% DOD, etc. I.e. an equivalent of 1200 "Full discharge" cycles.
With this hypothesis, the number of cycles is proportional to Total full cycles / DOD, i.e. an hyperbolic function of DOD.
In the reality the deeper the DOD, the higher the wearing degradation. This means that the real NbCycles is lower than the hyperbolic model.
Database profile and Hyperbolic model Show model + degradation acc. to DOD
Tool and model
The points of the profile are given on the datasheets. You can drag the values by the left mouse button, or edit them by the right button.
This graph shows the Hyperbolic model without additional degradation.
Now you can also show the model, including a specified linear degradation as function of the average DOD: on this example, when you have 10% more DOD, the additional degradation is 10% * 40%(of full SOC).
Pressing the "Keep" button, it is possible to replace the specified profile by the profile constructed on the model.
During the simulation, for each time step:
oThe static ageing state is decremented as a function of the battery actual temperature as defined by the user for the simulation. This is stored in the simulation variable SOWStat (SOW stands for "State Of Wear").
oThe dynamic ageing state is accurately evaluated as function of the discharging current and the depth of discharge for this hour and the curve above. It is stored in the variable SOWCycl.
The final SOW state is the minimum of both states.
Both initial wearing states may be specified at the beginning of the simulation, allowing to chain the real state over several simulation years.
The SOW evolution value along the year determines the Battery lifetime, which may be used in the economic evaluation for the replacement costs.
If, during the simulation, one of these SOW states attains zero, the battery is supposed to be replaced and both SOW are reset to 100%.
You can see the General Model description for further details.