A crisis in the making

ITA

It’s easy to see Electric Mobility fans indulge in the guilty pleasure of contemplating the disarray in which the fossil camp seems to find itself: to be fair, the rather clumsy statements of high-profile key players such as the CEOs of Toyota or Bosch all but confirm that the auto industry never truly believed in the electric mobility revolution and, in many instances, it was caught with its pants down.

I still think the timescale of the transition is very long, and there is ample manoeuvering space left, also because the electric camp doesn’t lack its own industrial challenges.

The first of such challenges was to put online sufficient manufacturing capacity to meet the explosive demand for electric vehicles nobody really anticipated; this was the daunting task at hand for OEMs in the first half of 2020, and it looks like we can put a checkmark next to it.

The second problem is of an infrastructural nature; I will limit my analysis to the Italian situation, where it is so patently evident, even though it is true for many European countries: a while back we described on those very pages the strong correlation existing between the capillarity of the DC charging network the adoption rate of EVs, by which metric Italy ranks among the worst countries

This delay further accumulated as EV sales in Italy nearly tripled in 2020 vs. the previous year and we predict will more than double again in 2021.

In this chart we can the the evolution of the EV stock (blue line) vs. the DC charging network (orange line)(note* on data sources).

It’s easy to see the charging network is growing roughly linearly, while the EV stock is growing much faster, as we are smack in the exponential phase of the accumulation sigmoid.

To fully understand the effect of the difference in the growth rates of the curves, we must introduce the concept of Occupancy Rate.

What is the “Occupancy Rate” ?

To simplify calculations, let’s assume EVs are all identical, with a mileage of 10.000 km per year, consuming 200Wh/km; furthermore, let’s also assume that 80% of the required energy is charged at home. Every EV will therefore need about 400 kWh per year, and the 55.000 BEV which are on Italian roads at end 2020 will need 22.000 MWh. How many DC stations will we need to supply this amount of energy?

To continue with our simplification assumptions, let’s say all DC chargers are identical and deliver 50kW of power: in the 8.760 hours of a year one such station could therefore deliver 438 MWh; however, since it’s not very likely that many people will want to get up and go charge their car in the dead of the night, we must reduce service hours to about 5.000 per year (which means about 14 hours per day, say from 7:00AM to 9:00PM, which in turn reduces the deliverable energy from a single DC station to about 250 MWh per year.

The “Occupancy Rate” (OR) is simply the ratio between the total energy required out-of-home by the EV stock and the total energy deliverable by the existing DC charging network; in other words, it describes how “busy” is the infrastructure or, again, what is the probability that stopping at a station, the driver finds it already occupied.

In our example, if each station worked incessantly for all the 14 hours every day, we would only need 88 of them, but obviously we need more.

The evolution of OR in the last 3 years

As we saw in the definition, OR is calculated at each moment in time, and using the data (*) for EV sales and charging station installations in Italy, we derive another chart:

The two grey lines represent the two extremes of 24h service and 8h service, while the red one represents the more realistic 14h service. The horizontal dashed line represents the OR of the about 80.000 fossil pumps, each of which can deliver 50 litres of gasoline in 3 minutes.

We conclude that in Italy you find the gasoline pump busy only once every 10 refuelings; for the electric driver this happened even less frequently, but at end 2020 the electric service level was about the same as the fossil service level.

Obviously the data for 2021 are only forecasts based on these assumptions:

  1. extrapolation of the installation rates of 2020 to 2021
  2. new EV sales in 2021 of about 70.000.

If these assumptions hold true, we should expect to find the charging station occupied once every five times!

Deconstructing the average

But, as always, reality is a bit more complex; in the total represented by the red line above are included two sub-networks which are very different in nature and scope:

  • the Tesla Supercharger network (dedicated solely to their namesake vehicles)
  • the non-Tesla network (open to all EV brands)

We want now to know how the two sub-networks behave. To perform this calculation, we will assume Tesla vehicles ONLY charge at the SuperCharger network (which is obviously not true) and recalculate the two ORs keeping into account sales and installations over time, but also the fact that the SuperCharger network is on average quite a bit faster than the non-Tesla network.

The red curve decomposes therefore in a blue Tesla and a green non–Tesla lines:

It’s easy to see how the two networks are in starkly different conditions: the Tesla OR is only now closing in on 3% (the over-estimation due to the fact that some Teslas do indeed charge elsewhere is probably compensated by the fact that, especially in the summer, there is a influx of foreign vehicles) while the non-Tesla OR is already well over 20% and could reach 40% by the end of 2021.

This makes total sense: in fact, the 8,600 Teslas in Italy represent only 13% of the EV stock, but the Tesla SuperCharger network offers about 40% of the DC stalls in our country.

Why care about OR?

We said the OR represents the likelihood of finding the station already occupied and having to wait for your turn; this means doubling (at least) the duration of the stop: what would be the small annoyance of a few minutes more with a fossil car becomes one full hour in electric. What amounts to a mere nuisance for people traveling for tourism can become a disruption in service so important to block the transition to electric of a company’s fleet.

The OneWedge answer to this conundrum consists in building a B2B-focused network alongside but segregated from the B2C network, with a much lower OR.


Note (*) on data sources: Car sales data come from UNRAE monthly reports; the data about DC stations installations come from the European Alternative Fuel Observatory; I would have liked to confirm them with data from OpenChargeMap and from the Motus-E annual report, but they were wildly different, so I decided to keep only the EAFO data.


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