Petrol car
The same commute on fuel. Nothing to schedule and nothing to optimise.
per year
- Per week
- Fuel used
The same commute, three ways to pay for it
Put your own numbers in
EV, one fixed target SOC
A standard Sigenergy setup. It charges to the same state of charge every night, because that is the only instruction it can be given.
per year
- Per week
- Energy used
EV, EnergyPilot black box
The OBD2 dongle reports real state of charge and distance driven, so the black box charges to whatever level tomorrow actually needs, and waits for the cheap hours.
per year
- Per week
- Energy used
a year saved by scenario 3 over scenario 2. Same car, same kilometres, same energy into the battery. What changes is how much of it is bought from the grid, and when.
a year saved against petrol. Most of this is simply going electric, and any EV would get it.
Either way, the parts of this that never show up in a sum: the car actually charged overnight rather than probably charged, an alert when it did not, one app for the solar, the battery, the house and the car, and the numbers to see what any of it is doing.
Why anything has to be bought at all
The house gets to the battery first, every night. What is left over is all the car can have for nothing, and the rest has to come off the grid. This one sum decides more than any other number on the page.
A week in the life
Where each night's energy comes from. A bar covers the evening and the small hours that follow it, so a single overnight charge is a single bar rather than being split across two dates. Both rows deliver exactly the same kilometres.
Show these numbers as a table
What the car's battery does
Both weeks start and finish on the same charge, so this is like for like. A fixed target has to haul the car back to the same line every night, and pays for it every night. Knowing the real state of charge means the level can ride down through the week, recharging less each time, and then refill on the weekend when the energy is free.
Every assumption, in the open
A model is only as good as what it admits to. These are the figures behind the numbers above, and the sliders change the first five.
What this model does not claim
- The same energy reaches the car in both scenarios, because the car drives the same distance. EnergyPilot does not make it more efficient. What changes is how much of that energy is paid for: it takes more from the free window and from stored solar, and buys far less from the grid.
- It also pulls slightly more energy off the grid overall, not less. A free hour is worth taking whether or not the car needs it right then, so it fills the house battery during the free window and spends that overnight. Total import goes up; the bill goes down.
- Scenario 2 is modelled generously. Its charging is already scheduled into the off-peak window rather than starting the moment the car is plugged in, it only pays a peak rate if a night's charge will not fit inside that window, and it draws on the same house battery scenario 3 does.
- Both setups fill the house battery during the free window, and both are served after the house. The saving is not that one has a battery trick the other lacks. It is that asking for the same state of charge every night needs more than the residual, so the shortfall is imported and paid for.
- Scenario 3 is never modelled as worse than scenario 2. Holding a single overnight target is one of the strategies available to it, so where nothing cleverer helps it simply does that, and the two lines land on top of each other. The gap you see is only what adapting actually buys.
- The week is simulated hour by hour. On weekdays the car leaves before the free window opens and returns after it closes, so neither setup can touch free or solar energy between Monday and Friday. That is why the weekend does the heavy lifting.
- Servicing, registration, tyres and depreciation are left out entirely. They would widen the gap against petrol, not narrow it.
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