I'm getting close to wrapping up a ~3,000 mile week and a half road trip under 8.1 / 17.24.30.
The energy remaining at destination is a wonderful feature and a game changer, and more feedback from it would help more.
In particular, I'd like to see how the instant or short term consumption matches with the predicted plan.
Right now, you have to wait until the percentage at arrival changes up or down to know if you need to change your behavior to reach the destination.
Small elevation changes can throw the acreage condition per mile off by a hundred watt hours per mile without being noticeable, so understanding what went into the estimate instead of just looking for a trip long average is important.
One simple way this could be implemented is with a second dotted/dashed line on the center console and driver energy screens (presumably in a different color) Welch shows the predicted average consumption for the last 5/15/30 miles.
(If the data they have is granular enough, they could put up a second curve matching the real usage curve instead, which might be better, but would involve a whole lot more data and actually might be harder to compare at a glance.)
Thoughts?
The energy remaining at destination is a wonderful feature and a game changer, and more feedback from it would help more.
In particular, I'd like to see how the instant or short term consumption matches with the predicted plan.
Right now, you have to wait until the percentage at arrival changes up or down to know if you need to change your behavior to reach the destination.
Small elevation changes can throw the acreage condition per mile off by a hundred watt hours per mile without being noticeable, so understanding what went into the estimate instead of just looking for a trip long average is important.
One simple way this could be implemented is with a second dotted/dashed line on the center console and driver energy screens (presumably in a different color) Welch shows the predicted average consumption for the last 5/15/30 miles.
(If the data they have is granular enough, they could put up a second curve matching the real usage curve instead, which might be better, but would involve a whole lot more data and actually might be harder to compare at a glance.)
Thoughts?