Since I had already collected and tagged my combined Sense/utility data with EV charging events, I decided to try a simple experiment to see if I could build a “detector” to tell if one of my EVs (Model S and Model 3) was charging during a given hour. A few key points of context:
- Sense has been detecting the Model S fairly reliably throughout 2020, so far, but I don’t really have a fix on how reliably.
- Sense was detecting the Model 3 for a while in 2019, but kind of gave up in 2020. I haven’t really pushed for a fix, partially because it seemed every new Model 3 software release changed the charging profile.
- Both cars charge at 240V, one at up to 80A and one at up to 48A, so they have fairly distinctive patterns, except when we plug in and the battery is almost full. Occasionally the charging can get obscured by up to 15kW of heating/cooling/baseline usage.
- It’s pretty easy to detect hours where one or both cars are charging for the full hour because the Sense Total Usage number is just so big, though that doesn’t work for hours when the car is only charging for a partial hour. Plus there are a few hours that slip in because they have lots of HVAC and other activity.
- We usually charge each car at a fixed start time offset from the other one (1AM and 3:30AM), early in the morning when rates are cheapest. But not always, so we can’t rely on time to help us with “detection”.
What does EV charging look like ?
The chart below highlights points 4 and 5. There seems to be a frontier about where the yellow line is that mostly separates charging from non-charging hours, but it’s nowhere near 100% accurate for categorizing.
A close look look at Sense Model S EV Detection
How did Sense do identifying hours when my wife’s EV, the Model S, was charging ? The graph below shows EV Detection energy, the amount of energy Sense sees going to the Model S, vs. the Total Usage Sense is seeing. I have set all the hours where Sense did not see the Model S charging to -0.5kWh, just so we can separate out non-detected hours from near-zero, but real detections.
The red oval highlights hours where Sense saw the Model S as charging but it wasn’t (false positive). The green circle highlights that Sense is not mistakenly identifying ANY Model 3 charging hours as Model S charging (true negative). And the blue circle highlights hours where Sense did not detect the Model S charging even though it was (false negative). Not that two of the Model S charging hours were detected, but showed up as almost zero power, even though the Sense Usage was substantial.
If I create a quick table of occurrences, I can see the exact number of hours that fit into each category, where ‘Positive’ means Sense identified Model S charging for that hour and ‘Negative’ means it did not. The hours in blue are true-positives - Sense predicted the Model S was charging and it really was. The hours in red are true-negatives - Sense predicted the Model S was not charging and it wasn’t.
Sense got identifications right for 113 hours (true-positives), but also detected 18 extra hours (false-positives) where the Model S wasn’t charging. It recorded 3730 hours where the Model S wasn’t charging and got that correct (true-negative), while showing 10 hours as negative, even though the Model S was charging. If Sense’s EV detection was a medical diagnostic, it would have a sensitivity of 113 / (113 + 10) or 92%. And it would have a specificity of 3730/(3730 + 18) of 99.5%