Hello I am Alberto Soto with siemens PLM Software. Today I will present the battery
data sheet import tool a standard feature ofLMS Imagine.Lab Amesim. When
sizing a battery for a specific application we usually don't have access
to costly measurement data, an alternative is to use the supplier
provided data sheet in order to generate a quasistatic model. This can easily be
done by using the battery data sheet import tool.
I start by loading the battery data sheet import tool
methodology demo. Here we will find a battery model connected to a virtual
test bench.
We will compare the results to measurement data from an actual test
bench. To launch the tool we click on the battery model and launch the battery
data sheet import tool. Here we can define a project name, battery nominal capacity
and the characterization type.
You can do this either by loading discharge curves, discharge curves in
front of temperature or OCV and discharge curves.
For now we will keep it simple and just load several discharge curves.
We start by choosing the image we want to load.
We have to define a scaling for that image.
So we zoom in on the image, select a first point to define the X-axis, we select
two points along that axes, for example 0 and 40 and then again two points
along the y-axis 2.6 and 4. Now, our image has been scaled. Then we select the
colour we want to adquire and click the button, now we must define what type
of curve we want to import.
First we commenced to defind the first type in this case "discharge", the name of
the curve in the this case I call it, first
the axis type in this case capacities already correct, the C-rate which as we
can see in the legend is 0.33 and the temperature in this case 23-degree.
Our curve is automatically required but as we can see here some legend points have
also been taken.
Remove those points and then in order to have a clean curve we do a
re-interpolation, that way we have evenly spaced break point. Now we do the same thing
for the next curve at 1.0C again we give it a name,
set the C-rate and temperature. Again we remove unnecessary points and we
interpolate. Finally we do it for the third curve so we call it
third, set to C-rate, temperature, this case the legend was not capture,d so we
simply reinterpolate. Now, that we have our three curves we can add them to the
model calibration data list.
We simply drag and drop them into the list as we can see the list has now
turned green,
this means we are ready to proceed. Also the model calibration tab has now become
enabled and so we can launch identification.
We see that are three curves are shown here, the calculated OCV shown here
and the resistance value is shown here. If we are content with our results we
can move on to statistics tab, here we can evaluate how our model is working.
We are comparing the crosses which represents the acquired curves with the
lines which represent the simulated result. As we can see it matches pretty
well. Other than visually you can also compare average and maximum values, or we
can visualize the error. Either absolute error or simply the error.
We can also visualize the error samples that is to say where our error is mostly
located. As we can see here the center is around zero which is pretty good.
Click OK and the primers are now been sent to our battery model.
The only thing left is to run a simulation.
We launched our simulation and so now we will compare measurement data to our
simulation results.
As you can see here the input to the system is a current profile. A current
profile is made of electric vehicle and hybrid electric vehicle cycles. So we can
compare the input voltage or validation. We see the results are pretty good if we
zoom in to an electric vehicle cycle we see that the overall results are good
and that we match the question static characteristics pretty well.
Same thing for the hybrid electric vehicle.
And last but not least we can also compare temperature and even though we
have a very simple thermal model we see the results much pretty well. That is all
for now thank you for watching and please visit our website.