We at the ABRP team are happy to share with you some insight regarding what different wind conditions have on the power consumption of vehicles in different winds. Vehicles in general are highly affected by weather conditions, and for EVs this is actually clearly visible due to the high efficiency - anything which makes it easier or hard to push the vehicle forward will - noticeably - affect consumption. An ICE car with 25-30% efficiency will see the same weather effects, the bad efficiency of the engine will simply hide it.
As some of you may know ABRP collects anonymous driving and charging data to improve the quality of our service (see our reader-friendly Integrity Policy), and as mentioned in a previous blog post Tesla Model 3 Performance vs RWD consumption - Real Driving Data from 233 Cars, we want to share with you when we find something worth sharing.
By studying the collected data from our most common car model - the Tesla Model 3 - we have been able to assemble a graph that gives some insight into how the wind is affecting power consumption, the result of which can be seen below. The graph is entirely based on data reported from the live data connected vehicles of ABRP users - there is no modeling or other assumptions at all.
The diagram shows the effect that wind has on the instantaneous power consumption of vehicles traveling at highway speeds, 100 to 120 kmh (62 to 75 mph). Each square illustrates three components: wind speed, wind direction, and the influence they have on the car's power consumption. Both wind speed and wind direction are relative to the car's heading, where each square can be imagined to be the origin of a wind blowing at a car located in the middle of the graph. What that means is the further away a point is from the center the stronger winds are acting on the vehicle, i.e., the point furthest to the right is a direct headwind and, the left-most point is a direct tailwind. The color of each square addresses the additional power consumed by the when that wind is acting on the car. A negative number means that the wind is helping and the opposite is true for positive numbers. This relates to the colors of the image, where the bluer a square is the more wind is helping, and the redder it is wind is a hindrance. See the example below explaining how to read the result.
Based on this we can answer a few important questions
- When are tailwinds beneficial?
- What are the worst kinds of winds?
- The effect of crosswind
Firstly, let’s start off by exploring what winds are helping the car. Notice that the area where the wind helps the car is relatively smaller than the rest of the circle. Remarkably, some tailwinds are even bad for the effectiveness, for a tailwind to be helpful it must almost always come straight behind.
Secondly, to answer the question of what the worst kinds of winds are, we look at the places where the graph is as dark red as possible, that is on the right-hand side of the circle. It can be hard to figure out exactly where the worst wind is hail from. But winds that originate either directly in front of the car or in the closest proximity to it seem to be the most unfavorable origin.
Lastly, what are the effects of crosswinds? Intuitively, it may seem like crosswinds would have no effect at all, but it has been known for a long time by aerodynamics engineers that crosswinds harm the efficiency of an object traveling through the air, and we can just confirm that.
Some things we can note from the graph is:
- A nice tailwind of 10 m/s (36 km/h, 22 mph) decreases consumption of a typical Tesla Model 3 by 6% at highway speeds
- A headwind of 10 m/s increases the consumption a Model 3 by 19%
Direct cross winds of 10 m/s can increase the consumption by 8%
A model of this effect of winds model has already been implemented into our vehicle consumption model and the full weather prediction is available for ABRP Premium members, and any user can enter the wind assumptions manually.
Wind really can affect the consumption of your vehicle quite a lot, and ABRP helps you plan for it with zero effort.
Thanks to the vehicle data provided by ABRP users, we made your experience with the app even better!