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Bo (ABRP) last won the day on November 5

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  1. New feature! ABRP now keeps track of charging networks/operators and allows you to prefer one or more of them. This is done by clicking a charger which has an operator and selecting "Prefer...". The planner will treat preferred chargers as "less costly" than other chargers will therefore more often use them. It is still a soft decision though, so if a non-preferred charger gives a significantly faster plan, it will still be selected. Let us know hownit works!
  2. Bo (ABRP)

    Supercharger Lully properly considered one-way only

    ... and fixed. Thanks for the re-report of the same bug
  3. Bo (ABRP)

    Supercharger Lully properly considered one-way only

    This is actually not a bug with OSRM, it is us. We don't have 3D coordinates for chargers, and this one is just on top of a highway lane. Last time I asked supercharge.info to move the coordinates 20 m south, and this solved the issue. Since then we have switched to using tesla.com directly instead for SuC positions, and they have the old/true position. I'll need to implement some position override, should be easy.
  4. Bo (ABRP)

    Route waypoint text looks clickable

    This got lost when we transitioned from Google Maps. Now back again!
  5. I'd love to break it down more, but the issue is that Model 3s all report exactly the same option codes through the API, so I can only use what the owners select as car model. We recently included specific AWD 18- and 19-inch wheel models so hopefully this will enable us to look at the differences between AWD and non-AWD too. We do log outside temperature; we'll look at that once winter is coming (in the northern hemisphere). Otherwise, the median filtering we do at each speed means that the curve we get is for the most common weather and driving - likely nice dry summer driving since the data is mostly from the summer and early fall.
  6. Bo (ABRP)

    Who do I get higher arrival charge than specified?

    ABRP finds a route by optimizing the total time, charging+driving+overhead. Getting to a charger in a modern Tesla with less than 10% is usually not a good idea, timewise, so ABRP will typically avoid that. There is no cost to getting to the destination at very low SoC %, so it will always arrive with the lowest allowed SoC. The ABRP optimizer is currently slightly granular and will typically optimize the time in steps of 5% charging - which is why it sometimes jumps from 10% to 15% arrival SoC if that turns out to be (slightly) better.
  7. The issue with Model 3 specifically is that the option codes reported by the MyTesla API are broken - they are all the same for any Model 3. This means that we have to trust what the user chooses in ABRP as car model, and this is quite often not completely correct. Also, we have, so far been lacking a choice for AWD. Will fix that soon!
  8. Thanks for the catch, the imperial unit efficiency numbers were switched. Now fixed! Also, we do not treat 110 km/h as equal to 65 mph. These speeds were chosen to be common highway speeds in the different regions. But perhaps we should have chosen 120 km/h which is pretty much 75 mph spot on 🙂
  9. As you may already know, ABetterRouteplanner.com collects driving data from contributing users. This data is used to improve the ABRP car models (i.e. the mathematical representation of each type of car) and also, to give back to the ABRP community providing the data, to be published here in the blog! At this point, we have received a lot of Model 3 Long Range driving data, and even enough data from Model 3 Performance to draw some first conclusions on how they differ. We have 220 different Model 3 Long Range users who have contributed a total of 70,000 km (43,000 miles) of driving, which caters for very good data. Most of these Model 3 Long Range are the RWD version. For P3D, there is "only" 13 cars contributing so far, having driven around 7,000 km (4,300 miles) of driving, which means that statistics is a little bit more shaky, but still usable. Just to show off what those numbers mean, this is the graph of the 7,000 km of P3D data - every blue point corresponds to 30 seconds of driving at a certain speed and how much power that car has consumed during those 30 seconds. Yellow dots show the median power consumption for that speed and red line is our fitted model. Now let's boil that data down to something more understandable! First, the reference consumption, constant speed on flat land at 110 km/h (65 mph) becomes: Tesla P3D: 173 Wh/km at 110 km/h (267 Wh/km at 65 mph) Tesla Model 3 Long Range, mostly RWD: 150 Wh/km at 110 km/h (232 Wh/km at 65 mph) This means that our real-world driving data shows that the P3D consumes about 15% more than the RWD version at highway speeds. This is expected, or actually somewhat low - most P3Ds run on 20" sports wheels instead of 18" Aeros, and perhaps more importantly, P3Ds may be driven more like performance cars by their drivers. (Note that in https://abetterrouteplanner.com, we add some margin to the reference consumption to be on the safe side.) Looking at efficiency numbers for different speeds, we get the following comparison between the Tesla Model 3 Long Range, P3D and Model S100D: We can see from this graph that there is a clear difference in efficiency between the RWD and the P3D, and at higher speeds where the Aero wheels with better aerodynamics, the difference grows even more. This efficiency leads to this range-vs-speed graph: And finally, in our standard road-trip challenge of a virtual 1,000 km (621 mile) drive with fast chargers every 200 km gives us: Tesla Model 3 Long Range: Total trip time 09:44, of which charging 01:24. Tesla Model P3D: Total trip time 09:59 of which charging 01:39. Tesla Model S100D: Total trip time 10:05 of which charging 01:45. So the slightly higher consumption in a P3D does equate to 15 minutes more charging time in a 1,000 km road trip. Not too shabby! Appendix - Graphs in Imperial Units
  10. Bo (ABRP)

    A Better Routeplanner 3.3

    Driving mode for Everyone! A Better Routeplanner has always been about two things to make life as an EV owner as smooth as possible: Planning at home, and following up while driving. In a Tesla, specifically with telemetry via MyTesla, the ABRP driving mode has been working smoothly, but in a mobile phone or iPad, driving mode has been absent. Now ABRP 3.3 changes that! Release highlights Driving mode, with or without telemetry. As soon as you move fast enough, ABRP will switch to driving mode and display a graph of the next route leg including elevation and expected battery State-of-Charge % (SoC) together with estimated arrival time. Full screen mobile web app. If you go to ABRP in your mobile phone or iPad browser, you can “Add to Home Screen” in your browser. The ABRP icon on your home screen will then launch ABRP in a full screen mode which works more like an ordinary app. More space for graphs! Avoid ferries, tolls and highways. If you want to have more interesting routes, you can now disable any of these. This also improves the previous avoid ferries function which was not ideal. OBD telemetry. Just like we fetch SoC and other car data via MyTesla, we can use OBD data for other car brands and get real-time SoC and other information for convenience while driving. How to set up an OBD reader with ABRP. Manual SoC input. If you are not fetching information from your car via telemetry (MyTesla or ODB), you can now manually input your actual SoC. This is shown as a big battery symbol above the driving mode window. Improved reference consumption estimation. With telemetry or manual battery input, ABRP will now estimate your reference consumption, even if you do not have a route planned. The end user’s license agreement has been updated to allow ABRP to store anonymous drive data. There is no way to track this data back to any person, even if our servers get hacked, and we will use it to improve our planning and car models even further for a better experience for everyone. The lowlight of the release is Teslas v9 software, which forces their own map in the background at all times. For Model S and X users with the old MCU (before March 2018) this makes ABRP almost unusably slow in the car browser. Tell your Tesla representatives. Driving Mode with Manual SoC Input If you are driving a car without telemetry, you can still get a visual indication of your actual SoC (battery %) compared to the plan by letting ABRP know your actual SoC. Do this by adjusting the estimated SoC in the green battery icon to match your car’s SoC. Click to the left of the icon to decrease the actual SoC Click to the right of the icon to increase the actual SoC Click in the middle of the icon to confirm that ABRP’s estimate is correct By doing this you get a blue SoC graph overlaid on the grey planned SoC in driving mode and you can visually see how you are doing. Also, you help ABRP improve our car models and planning, and thereby help all other fellow EV owners!
  11. Bo (ABRP)

    How to Add Your Car to ABRP

    Introduction One of the questions we get fairly regularly at ABRP is if and when we will support other Electric Vehicles in the planner. To create a model the planner can use we need two aspects defined: Driving Consumption and Charging. Once we have a model for a car, we have three markers we’ll put in the planner: Alpha – An initial model based on measurements or data by external parties, not thoroughly verified. Beta – A more mature model validated by matching to owners’ actual road trip numbers Release – Model verified and improved by recorded real life driving data. Once you have the data we need to make Driving Consumption and Charging Models, email it to the ABRP Team, and we’ll work with you to get the model on the site. We won’t make any car model available on ABRP without first verifying accuracy with an actual owner of a car, so it helps immensely if you’ve got an example road trip you can recreate in the planner once we’ve prepared the model. Emails: bo@abetterrouteplanner.com jason@abetterrouteplanner.com Driving Consumption Model The driving model is the most important part of the planner, as it calculates how much battery you’ll use on each leg of the trip. To do this calculation, the planner uses a third order polynomial to calculate consumption. This is based on the physics of driving. There are several ways to create this driving model, listed here in order of accuracy: 1 – Analytical Physics Model Creating an analytical model requires the least access to a car, but it’s the least guaranteed to be accurate. To create an analytical model, we use the physics of driving: Pdrag = η*Cd*A*v3 Prolling resistance = η*Crr*M*g*v Pidle = Constant Combining these three terms, we get a full equation for the consumption of a given car. We then multiply by the drivetrain efficiency, what percent of battery energy goes into creating motion. To create this model, we need to fill in a few variables: Parameter Description Cd Coefficient of Drag - Typically available online, but takes a little bit of research to verify. A Frontal Area - Cross-sectional area of the vehicle. This can be calculated roughly from front or rear photos of the vehicle and the vehicle's dimensions Crr Coefficient of Rolling Resistance - Mainly based on the tires, and drivetrain of the vehicle. A little harder to dig up. This typically varies from about 0.007 for very efficient tires to 0.014 for wide performance tires. M Mass - Curb mass of the vehicle. Pidle Idle Power - The amount of power drawn by the vehicle when sitting still. Best drawn by looking at the built-in energy meter while at a stop. Typically around 1-1.5kW η Drivetrain Efficiency - Efficiency of turning battery power into movement. Generally between 85%-95% If you can provide all of these parameters, we can create a model that is fairly accurate. 2 – Manually Collected Driving Data The next-best method is calculating the driving model from approximate real-world data. This can be gathered by recording consumption while driving. By observing the power draw at various speeds on flat ground, and providing data points we can calculate a better consumption model. In general, we need the highest number of data points at freeway speeds, as you tend to spend most of your driving on a trip at those speeds. I would recommend noting the power consumption readout at the following speeds (km/h and mph are not exactly equivalent, for ease of use, please note which unit you used to collect data so our model can be as accurate as possible). If you plan to use this method, be sure to drive safely, you may want to recruit an assistant to take the power draw notes while you drive. Speed (km/h) Speed (mph) Power (kW) 30 20 45 30 60 40 75 50 90 55 100 60 110 65 120 70 130 75 140 80 150 85 3 – Collecting Driving Data Directly This is the best way to build an accurate model. This can vary by vehicle or manufacturer, but most vehicles provide data via the OBD port. For an example, see the for the generic OBD and Torque instructions. To contribute data this way, set yourself up with Torque Pro, and find a PID list for your car. If you can find these things, and can verify the data shown on the Realtime Information display in Torque is accurate, contact me (jason@abetterrouteplanner.com) to set up the server to receive your data. Once there’s enough data for your vehicle, we’ll perform the same analysis we’ve done for all the currently released models in the planner. Charging Model The charging model is a little easier to build from available information. If you can find a plot of the maximum charging speed relative to State of Charge, or a video that shows power in kW and battery %, we can build a charging model from that. Something like the following chart (sourced from Fastned for the Hyundai Ioniq): Fastned charging data for the Hyundai Ioniq Again, however, the best way to build a charging model is to contribute OBD data directly from a charging session. See the setup instructions in the previous section for what’s needed to submit OBD data.
  12. Bo (ABRP)

    Hyundai Ioniq – Specific Instructions

    Thank you for contributing your Ioniq EV Data! You will note in the Desired PIDs table, there are two entries per item. This is intentional, to work around a limitation of the Ioniq PIDs. Please make sure you select all PIDs listed in the table. There are two options for PID Lists: Full PID Lists from JeJuSoul on GitHub. You will need the following files from the Ioniq EV > extendedpids directory: ABRP_Hyundai_Ioniq_Data.csv Hyundai_Ioniq_EV_BMS_data.csv Hyundai_Ioniq_EV_VMCU_data.csv Download one of these to your phone and return to the Generic Instructions. Keep this tab open, as you will need to reference the desired PID list. When needed by the Generic Instructions, these are the PIDs you will need to select for Logging. Required PIDs PID Title !_ABRP_Battery Current !_ABRP_Battery DC Voltage !_ABRP_Battery Power !_ABRP_Cumulative Energy Charged !_ABRP_Cumulative Energy Discharged !_ABRP_HV_Charging !_ABRP_State of Charge BMS !_ABRP_State of Charge Display !_ABRP_State of Health !_ABRP_VMCU Real Vehicle Speed GPS Altitude GPS Latitude GPS Longitude Speed (GPS) Speed (OBD) Again, there are apparent duplicates in the table, but all PIDs need to be selected, or we will not receive good data from your Ioniq. Webserver URL http://abetterrouteplanner.com:4441/ioniq_data
  13. Bo (ABRP)

    Chevy Bolt – Specific Instructions

    Thank you for contributing your Bolt EV Data! There are no special additional steps required to set up your Bolt EV to contribute data. There are two options for PID Lists: Full PID List from Sean Graham on the Chevy Bolt Forum Short PID List, listing only the parameters needed by ABRP Download one of these to your phone and return to the Generic Instructions. Keep this tab open, as you will need to reference the desired PID list. When needed by the Generic Instructions, these are the PIDs you will need to select for Logging: Required PIDs PID Title !Charger HV Current !Charger HV Voltage !Charger HV Power !HV Current !MG Voltage !State of Charge Raw !Battery Capacity !Air Temp 0 *Speed kmh GPS Altitude GPS Latitude GPS Longitude Speed (GPS) Speed (OBD) All other parameters are optional, and are not recorded by ABRP. Webserver URL http://abetterrouteplanner.com:4441/bolt_data
  14. Overview These instructions will walk through the steps to be performed once you have downloaded a PID list for your vehicle to your phone. You will need to reference vehicle-specific instructions at points when there are differences in setup between vehicles. At a high level, you will need to: Create an ABRP account Find a bluetooth OBD reader that works with your vehicle and pair it with your phone Set up Torque Pro or other app to log data to the ABRP Server These instructions assume you have an Android phone, as that’s what I have access to to figure out the setup. Once you’re set up and driving, the data that helps us out the most is Consistent Speed on Flat Ground, and Charging on a DC Fast Charger that’s faster than your car can charge. Of course, we’ll take any and all data you’re willing to provide, but those two sets help us the most. Step 1 – Create an ABRP Account To prevent unexpected data from being added to the server, and to allow us to delete your data upon request, you will need to create an ABRP account. This can be done on the planner, under Show Settings > Show More Settings > Login or Register Step 2 – Set Up Your OBD Reader You will need to pick an OBD Reader that works for your phone and your car. The main differences between bluetooth readers are in read speed. My first Vgate iCar was a dud, and ended up going with the OBDLink, as it’s a better overall adapter. For our purposes, we’d like at least 1 read every 10 seconds, so here are a few other adapters that should work: Name Read Rate (<15 Selected) Read Rate (>15 Selected) BAFX OBDII Reader/Scanner every 10 seconds every 30 seconds Veepak BLE1 every 5 seconds every 10 seconds Veepak Bluetooth 3 every 5 seconds every 10 seconds Vgate iCar Pro Bluetooth every 1 second every 5 seconds Vgate iCar Pro BLE every 1 second every 5 seconds OBDLink LX BLE every 1 second every 1 second Reference this table later when selecting how quickly to log to the ABRP Server in Torque. Once you have the OBD II reader, installation is pretty easy. Most cars have the OBD Port near the steering wheel, the port is a roughly trapezoidal shape: Step 3 – Configure Torque for Upload If your car has a vehicle-specific app listed, perform the instructions linked below, then you're done! Car App Nissan Leaf LeafSpy Pro (Android) (iOS) Download Torque Pro from the Play Store. You will also need a file manager if you don’t already have one. These instructions assume you’re using ES File Manager. All of the following steps are performed on your Android Phone. Download the appropriate PID file for your car and perform any additional setup steps per the links below: Show entries Search: Car Notes Chevy Bolt PID List courtesy of user Telek on the Chevy Bolt Forum Hyundai Ioniq PID List courtesy of JejuSoul on Github Hyundai Kona PID List courtesy of JejuSoul on Github Kia Niro PID List courtesy of JejuSoul on Github Showing 1 to 2 of 2 entries PreviousNext In ES File Manager, select the ☰ in the upper left, and select “Show hidden files”. Select Internal Storage at the top left (Note: The name Internal Storage may vary by device) Move the downloaded PID file(s) from /Downloads to /.torque/extendedpids If /extendedpids/ doesn’t exist yet, do the actions in step 5, then come back and move the file. If you perform step 5 here, you will need to perform it again after step 4.2 to import the file. To move the file(s): Long press the file and select “Cut” Navigate to /.torque/extendedpids Press “Paste” Open Torque Pro and import the file: Navigate to ⚙ > Settings > Manage Extra PIDs / Sensors If there are already PIDs on this page, select ⋮ and pick “Clear List” Select ⋮ and pick “Add Predefined Set” Pick the file you moved. Repeat this step for any additional files required. Configure what data to save: Navigate to ⚙ > Settings > Data Logging & Upload > Select what to log > ⋮ > Select what to log If there are already PIDs on this page, select ⋮ and pick “Clear List” Reference the “Required PIDs” table on your particular vehicle’s page. Finally, configure file save or webserver upload (Direct upload to the ABRP server is easier, you don’t have to remember to send us your data after a drive, but either method is fine. You can also do both methods simultaneously, if you want to save a local copy of your data.): If configuring Webserver Upload (Realtime web upload): Navigate to ⚙ > Settings > Data Logging & Upload Under “Realtime web upload”: ☑ Upload to webserver Web Logging Interval – Set appropriate to your adapter per the table in section 2. If in doubt, set to “every 5 seconds”. ☑ Only when OBD connected Set the Webserver URL per your vehicle specific instructions. Torque ID is not used User Email must match your ABRP login email Test Settings – Verify “No problems found!” If configuring File Save: Navigate to ⚙ > Settings > Data Logging & Upload Under “File Logging”: ☑ Synchronous Logging ☑ Log when Torque is started ☑ Only when OBD connected ☑ Automatically log GPS G Sensors are not used by ABRP ☑ Rotate Logfiles ☐ Format Log values (Do not have this option selected) Go for a drive! If using File Save: After each drive or charging session navigate to Realtime Information > ⚙ > Email Logs Select the logfile you want to send to ABRP Select “CSV (Comma Separated Values)” Send the file to jason@abetterrouteplanner.com Once you’re set up, if you’d like confirmation that your data is getting to us, you’re welcome to send me an email, and I’ll check it out for you! Also, feel free to ask for help getting set up if you run into issues.
  15. Bo (ABRP)

    Bolt EV Consumption and Modelling

    Thanks to the 5 Bolt EV drivers contributing driving data to ABRP, we’ve finally got enough data points to define our first real world consumption curve for the Chevy Bolt EV! We can still use driving data to improve the model even further, so if you’d like to contribute your data, have a look at the instructions. Also, if you’ve got an electric car you’d like us to support, contact myself and Bo, and we’ll run you through what we need to add the car to the planner. Much of the data comes from day-to-day driving, with a few road trips sprinkled. Thanks to everyone who contributed their driving data! Bolt EV Power at Constant Speed The ABRP Model, as you know, is driven by calculating the power consumed for each leg of the trip by plugging in the speed, elevation, and other factors for each segment of the trip, determining how much power the car must output to drive that segment. It then adds up all the segments, and subtracts it from the battery to determine when a charging stop is needed. For this purpose, we need an accurate driving model on flat ground as a baseline, that turns speeds into power. Then we can add all the other driving factors on top of that: Bolt driving data fit to a third order polynomial The blue dots are consumption samples (30 seconds of driving), adjusted for elevation and speed changes, and the yellow dots are median points within a 1 m/s bin. This means that the red line consumption model is fitted to the median consumption which means that most weather issues, car defects, aggressive driving and so on is typically ignored. As can be seen, we mostly have data points from very low speed and from highway speeds, but that is where things are most interesting. For the Bolt EV, the bottom line is, it’s actually a quite efficient vehicle, though its somewhat unaerodynamic shape really hits it at high speeds. The model gives us a reference efficiency of: 6.06 km/kWh (165 Wh/km) at 110 km/h or 3.92 mi/kWh (255 Wh/mile) at 65 mph That’s pretty good for a boxy little hatchback! For comparison, that’s about halfway between the Model 3 (143 Wh/km) and the Model S (188 Wh/km). We’ve now updated the live model for the Chevy Bolt (and Ampera-E), so you should see the benefits of this higher efficiency in your route planning! Do note that we still set the default a little lower than that, just to ensure we give you a plan that’s not going to over-promise your car’s capabilities. Comparing to the Analytical Model Driving range vs speed comparison between the real world driving data and the original analytical model. Up to this point, we’ve been using an analytical model, using the drag characteristics, rolling resistance, and other parameters to determine an approximate driving model for the Bolt. Since we’ll be building a lot of these as more EVs come to market, we wondered how accurate the analytical model really is: As you can see, the models match quite closely! In fact, when building the Bolt analytical model, I added a 10% margin of safety to the model until we could validate using real world data, and you can see that at freeway speeds, the Analytical Bolt is about 10% lower than the Real World Bolt. Road Tripping in the Bolt With all the data we’ve got, let’s add the Bolt into the road table, and see where it falls: Model 3 Long Range: Total trip duration 09:43, of which charging 01:23 Model S100D: Total trip duration 10:05, of which charging 01:45 Model X100D: Total trip duration 10:29, of which charging 02:09 Model S60: Total trip duration 10:35, of which charging 02:15 Model X60: Total trip duration 11:28, of which charging 03:08 Bolt EV: Total trip duration 12:20, of which charging 04:00 This is using the “ABRP hypothetical road trip” is 1000 km (621 mi) in 200 km (124 mi) steps at 120km/h (75mph). The Bolt’s overall road trip speed is pretty slow. Even slower than the slowest Tesla. This is a consequence of the relatively slow charging that Chevy has built into the Bolt: Charge speed comparison, accounting for vehicle efficiency and battery size. Comparing the Bolt’s charge speed to that of the Model 3, we can see why our road trip takes so long! Accounting for battery size and driving efficiency differences, the Model 3 can charge nearly 2.5 times faster than the Bolt at each relative peak. All in all, the Bolt definitely can do those road trips, but it’s going to be at a much slower overall pace than the Model 3. The upcoming Hyundai Kona is a little bit faster than the Bolt, but not hugely, since it’s slightly less efficient. The larger battery makes for slightly longer range, but also means it takes a little longer to charge. Once we start getting some data, we’ll do a comparison to see how much faster the Kona really is than the Bolt. Appendix: Graphs in Imperial Units

Contact Us

Bo - Lead Developer and Tesla owner: bo@abetterrouteplanner.com

Jason - New Car Models, Developer and Bolt owner : jason@abetterrouteplanner.com

Idreams - Forums Administrator, Forums Developer and Tesla owner : idreams@abetterrouteplanner.com