Electrical exploration: temperature, speed and autonomy

While the battery-powered electric vehicle (EV) has many advantages, including being free from oil in use, it makes efficiency even more dependent on the type of use made of it and its environment. The autonomy of cars depends on many factors*, including speed and temperature.

_{* aerodynamics, engine, driving style, road gradient and surface, load carried, tires, etc.}

The impact of these different factors on the autonomy of electric vehicles is the focus of this study. The analysis covers continental France at the departmental level and the rest of Europe at the country level.

Our interactive map allows you to visualise, in each territory studied, the relative range loss of an electric vehicle depending on the month of the year. The calculation of the autonomy takes into account the average temperature observed during the month in question as well as the average speed permitted on the road network. This information and its sources are detailed in the box below. The analyses are broken down into two different electric vehicles: a car (maximum theoretical autonomy of 620km) and a utility vehicle (maximum theoretical autonomy 366km) whose batteries are standardised at 65kWh.

Temperature : the significant impact...

At the heart of our investigation is the significant impact of the seasons. Paris, for example, suffers the consequences of these seasonal variations with a substantial difference of 22% between the months of June and January. The autonomy of electric vehicles reveals a remarkable performance in summer, benefiting from mild temperatures. However, in winter, a more pronounced loss is observed in the capital compared to other predominantly rural departments. This disparity is explained by an average speed that remains below the 50 km/h mark for Paris. Therefore, it is above all the temperature that plays the predominant role in this reduction in autonomy.

In contrast, in Savoie, where the average speed reaches 60.7 km/h, with a temperature range of 17.4°C between January and June, compared to 14°C in Paris.

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In June, the autonomy climbs to 556 km (597 km in Paris);

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In January, the autonomy decreases to 441 km (460 km in Paris);

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This results in a loss of 115 km for Savoie (and 137 km for Paris).

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... but speed: The main factor in range loss beyond 80 km/h

Now let's see the influence of a speed variation. Let's take maximum speeds of 30, 50, 80, 110 and 130 km/h. For a temperature of 20°C, here are the results:

We observe that the urban environment favors the autonomy of electric vehicles while long highway journeys strongly affect the battery capacity.

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🧛 At 110 km/h, a 1°C decrease in temperature results in a modest decrease of only 2 km in range. However, at 50 km/h, the same -1°C temperature change has a much greater impact, resulting in 11 km reduction in range. At 30 km/h, increasing speed by 10 km/h results in a 10 km loss in range. On the other hand, at 110 km/h, an acceleration of 10 km/h has a heavy impact with a 33 km decrease in range.

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Figures in Focus: A glance at the map

Focus on France : Among the highlights to consider, we note significant range losses compared to the theoretical maximum capacity. In January, for the departments of Haute-Loire and Lozère, the most drastic loss reached -29.4%.

The maximum autonomy with a minimal loss of only -3.7% is reached in Paris in June (combining urban network and mild temperatures). Conversely, Maine-et-Loire presents the worst results for this same month, with a marked drop of -17.6%.

The best annual performance is for Pyrénées-Atlantiques with an average reduction of -15.3%, while Aube has the least favorable result, with -22.4%.

Moving to Europe : On a European scale, a first empirical observation is necessary: ​​a gradient from blue to red extends from Portugal to the Balkans. Overall, autonomy therefore decreases the closer one moves towards the Baltic.

In detail, Finland recorded the greatest range loss (-36.6%) in January. Portugal, for its part, presented relatively constant conditions: a 14.4% average range loss over the year, with an amplitude of only 12.3% between the minimum in June and the maximum in December.

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Conclusion

France is a country where the decline in autonomy remains measured (-18.2% on average per year). Variations from one region to another do indeed exist but are not so marked. However, seasonal disparities in terms of autonomy are significant and can constrain the actual use of the vehicle.

Taking into account the carbon profile of the electricity mix, scrutinized in the MBP4 , the electrification of the French vehicle fleet emerges as a viable option for abandoning fossil fuels. However, in countries such as Poland, where the electricity mix is ​​highly carbon-intensive and climatic conditions less favorable, the electrification of the fleet presents more disadvantages than advantages, potentially worsening emissions.

Finally, it is interesting to note that the optimal conditions for using an electric vehicle coincide with those for cycling. Saddle up!

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🧙 ‍ ♂️ Limits of the study

• First, it should be noted that the classification of roads differs from one country to another, leading to a relatively rough estimate of the maximum average speed (especially in some countries where the data seem to be incomplete). However, for a comparative analysis between French departments, the data are harmonised according to a uniform methodology;
• The maximum average speeds discussed here do not correspond to the average speeds actually reached, as these vary depending on traffic conditions at a specific time;
• Road relief, an influential factor, was not considered due to resource and data limitations;
• Battery life also depends on the vehicle model (for example, a Tesla Model 3 will not suffer the same loss of range on the highway as an SUV);
• Finally, there are variations related to battery cooling systems and battery technologies themselves. However, our goal is not to conduct an exhaustive comparison in this regard.