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use Charging overhead from abrp database

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I like the effort you put in making abrp do the heavy lifting on the planning of ev road trips. One thing I find hard to guess is the average Charging overhead for a road trip as I often have no experience with the charging locations that abrp will suggest. Some locations need low overhead while others require substantial extra overhead. This can also change over time eg at different times of day or be occasionally different when a location has detours or eg some chargers take more time to get charging than others. You could even see the extra time spent at locations with good facilities as extra Charging overhead as opposed to minimal Charging overhead at places you do not want to spend any more time than strictly necessary. Can you build a database on the actual and/or average charging overhead that abrp-users take per location and use this database in trip planning?


Edited by abrpuser
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My understanding of overhead is thats it’s purely the (average) time taken between stopping driving and charging starting - usually a function mostly of how quickly the driver is able to park, get out, find the correct RFID / app, plug the cable in and then get the charger to activate. 

It’s normally about 2-3 minutes, in my experience.

The extra travel time taken between coming off the most direct route to the destination and driving to a particular charger should already be accounted for.

The main scenario I can envisage where the plan allows for only a few minutes but you ending up taking significantly more is if you get stuck in a queue waiting for a charger to become available.

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Thanks, I second any and all charging overhead experiences from other road trippers. As abrp is already planning the driving to the charging location and can see from live car data what the actual charging overhead is per location that is valuable information that will benefit all other users not familiar with the specific location. I am impressed with the 2-3 minutes that fits your Charging overhead for trip planning. I find that the abrp suggested 5 minutes is not always enough but putting in 10 minutes for all stops is probably not getting me the best possible trip planning. Abrp can build these statistics per charging location so why not put that data to work to support abrps goal of making ev trip planning as easy as possible

Edited by abrpuser
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Oh I think I see what you mean now.

If ABRP knows I am driving from A to B, and that I need to stop once to charge, it should already be including the time it takes to cover the distance from the highway to the charger.

If my understanding is correct, you shouldn’t include the time it takes to drive from the highway to the charger in the overhead. The overhead ought to be pretty similar for most charging locations (although less for Tesla Superchargers where you literally just park and plug in, and maybe a little more if you know you are going to use a charger where you can’t use an RFID card and have to fiddle with a mobile app).

As I understand it, ABRP will pick a charger that is less travel time from the highway (whilst also giving weight to other factors, such as number of stalls, network preferences etc).

What I think you are suggesting is that the time taken to cover the distance from the highway to the charger may, in reality, be longer than is estimated at certain locations.

For example, if:

- the location data of the charger is not quite accurate and the charger is in fact at the far side of a large and busy car park.

- or, the location data is accurate, but the car park where the charger is located is often busy with cars manoeuvring, pedestrians etc meaning that it take several minutes more to get to the charger than the navigation routing anticipates.

In theory, I guess it should be possible for ABRP, when used with a car with a live car connection that reads the SOC, to know when the car has actually started charging and so to calculate the average time elapsed between cars leaving the highway and starting to charge at that location. It could also differentiate between different times of day, as at some locations the overhead may be significantly different at certain times of day.

On the face of it though, it feels to me like this would be quite a lot of work to implement, and possibly for only marginal benefit - but maybe not!


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