Another new TQ motor: hpr40

[stompandgo]

Some of us also have real world, on-road metrics and data from our rides and races to go by. There's also the unmeasurable RPE (Relative Perceived Exertion) data that is accurate only for that rider.

The developer contacted me and explained his methodology and the systematic approach needed to get an accurate outcome. I was pleased that he does not claim it to be gospel, only an estimate. I will go through the motions and follow his instructions for my last long ride, so that we can see how close he came to predicting the eventual usage. The one variable that I use on almost every ride is the effect of shutting Off. I may turn off assist for large percentages of the ride, and there's no realistic way to predict how much Off time there would be because it is so dependent on RPE, terrain, road conditions, atmospheric conditions, etc.

I am very intrigued by this model, however. I have a ride I plan to do soon that, even with the range extender and significant time in Off, may run out of assist. I'd like to see what it comes up with.

 

[Jeremy McCreary]

Some of us also have real world, on-road metrics and data from our rides and races to go by.

Would love to have that kind of experience to draw on — no doubt another very useful lens on your riding. I say, the more lenses, the better.

The developer contacted me and explained his methodology and the systematic approach needed to get an accurate outcome. I was pleased that he does not claim it to be gospel, only an estimate. I will go through the motions and follow his instructions for my last long ride, so that we can see how close he came to predicting the eventual usage. The one variable that I use on almost every ride is the effect of shutting Off. I may turn off assist for large percentages of the ride, and there's no realistic way to predict how much Off time there would be because it is so dependent on RPE, terrain, road conditions, atmospheric conditions, etc.

I rarely stick to a planned route, much less a script on how to ride it. Hard to deal with that in any conceivable pre-ride range prediction scheme.

But if you find the app reasonably accurate when you actually ride a route the way you told it you would, you could use a prediction as a reference case for range management en route.

"I have the battery to ride this route this way with roughly this much left over." Your thinking about range could then delta off that case as the ride evolves.

For example, if the app predicts 20% battery left for a particular route and riding script, you should probably either (a) avoid battery-hungry deviations, or (b) compensate with some battery-saving deviations elsewhere.

The predictions might also help you decide when it's safe to leave that heavy range extender at home — with the understanding, of course, that the RE comes along in borderline cases.

 

[stompandgo]

Would love to have that kind of experience to draw on — no doubt another very useful lens on your riding. I say, the more lenses, the better.



I rarely stick to a planned route, much less a script on how to ride it. Hard to deal with that in any conceivable pre-ride range prediction scheme.

But if you find the app reasonably accurate when you actually ride a route the way you told it you would, you could use a prediction as a reference case for range management en route.

"I have the battery to ride this route this way with roughly this much left over." Your thinking about range could then delta off that case as the ride evolves.

That's exactly what I plan to use it for. I have a ride I've wanted to do since I moved here that I don't think is possible under assist from start to finish even with the range extender. The segment prediction part is hard, as the terrain is mostly rolling. It's not like I'm riding in the country with climb 1, climb 2, climb 3, etc. on the ride route. But I will try. What I hope to get out of it is some metric that represents the power deficit, i.e. you will have -100Wh, or you need 120% of your capacity, something that will help me gauge the off time. The Garmin "Smart Range" algorithm isn't bad, but I would not plan a ride on the road with it.

For example, if the app predicts 20% battery left for a particular route and riding script, you should probably either (a) avoid battery-hungry deviations, or (b) compensate with some battery-saving deviations elsewhere.

The predictions might also help you decide when it's safe to leave that heavy range extender at home — with the understanding, of course, that the RE comes along in borderline cases.

Fortunately the TQ range extender is only a bit over 2 pounds, on a 32 pound bike. It's added weight is negligible. But I get what you are saying.

 

[apctjb]

I have a ride I've wanted to do since I moved here that I don't think is possible under assist from start to finish even with the range extender. The segment prediction part is hard, as the terrain is mostly rolling. It's not like I'm riding in the country with climb 1, climb 2, climb 3, etc. on the ride route.

Sounds great, let us know how it goes.

I am going to try a 75 mile/5000ft loop I have been eyeballing this weekend. The estimator predicts 75mile range for this ride with my settings, with little safety margin. lets see..

 

[mschwett]

that's a good profile to test out such a thing, the end is all downhill

 

[apctjb]

Changed the start point so could end with some climbing. The estimator did a good job a predicting duration, average speed and ending SOC. 13.4% estimated vs 15% showing on the bike display at end of ride.

Its probably been 10 years since I last did this loop and today with a little assist from TQ I felt like I had stepped 10 years back in time. Amazing technology, why did I wait?

 

[stompandgo]

Do you feel that you changed the assist levels at the same points as the estimator?

 

[apctjb]

Do you feel that you changed the assist levels at the same points as the estimator?

Great question. Answer is Yes on the main climbs and descents. For those sections I could predict before the ride where I would change assist levels, and based on watching the watt meter on past rides what my average input was likely to be. No on the rolling sections as I was not consistent on assist or power input. There were some steep bumps and I kicked the assist up climbing and then turned it off entirely descending and that was not predicted in advance as I assumed I would be riding in Eco the entire section. That said it seems the Eco, Mid, Off pattern for that section averaged out in terms of energy draw as the bottom line prediction for the ride was close.

 

[stompandgo]

Thanks, that makes sense.