Energy and Stint Model
The energy and stint model is the first tool that makes the project serious.
Without a model, the conversation becomes emotional. One side says EVs are too heavy and charging takes too long. The other side says electric motors are efficient and fast. Neither position is enough. Le Mans is a timing problem, an energy problem, and a probability problem.
The model must answer a practical question:
How much energy can the car use per lap, how long can it run, and how much charging time can the strategy afford?
The Base Variables
The first version of the model should be deliberately simple. It does not need to simulate every tire, weather, and traffic detail at the start. It needs to expose the relationships.
The core variables are:
- race duration
- average lap time
- energy used per lap
- usable battery capacity
- charging power
- charging efficiency
- pit loss
- number of stops
- neutralization time
- thermal derating time
The simplest EV stint equation is:
laps_per_stint = usable_battery_kWh / kWh_per_lap
The simplest charging equation is:
charge_time_hours = energy_added_kWh / effective_charging_power_kW
The simplest race distance equation is:
total_laps ~= available_track_time / average_lap_time
The value is not that these equations are complete. The value is that they make trade-offs visible.
kWh Per Lap Is the Key Number
For a pure-electric Le Mans concept, the most important number is not total battery capacity. It is energy per lap.
If the car uses too much energy per lap, every other part of the system becomes harder. The battery must be larger. The charging stops must be longer. The cooling load increases. The pack becomes heavier. Tire and brake load increase. Strategy flexibility decreases.
The project must therefore define target energy bands:
- ideal kWh/lap
- acceptable kWh/lap
- emergency kWh/lap
- wet-condition kWh/lap
- Safety Car kWh/lap
These bands matter more than one headline number because race conditions are not constant.
Stint Length Is a Strategic Choice
A conventional GT car often organizes its race around fuel, tires, and driver rotation. A pure EV must organize its race around battery state of charge, temperature, charging availability, and traffic.
The target does not have to be the longest possible stint. A longer stint may require a larger battery and create more mass than it saves. A shorter stint may require more pit stops and more charging events. The optimum may sit between those extremes.
The model should test several stint concepts:
- short stints with lower battery mass and more frequent charging
- medium stints aligned with driver and tire windows
- long stints requiring larger usable capacity
- flexible stints that extend during Safety Car periods
- conservative stints that protect pack temperature
The correct answer is not fixed until the car's energy use and charging behavior are validated.
Charging Time Must Be Compared With Track Gain
Charging time is the obvious weakness. The question is whether track performance, consistency, and neutralization strategy can offset it.
A useful model compares:
- time gained per lap versus benchmark pace
- time lost per charging stop
- number of stops required
- time recovered during Safety Car or Full Course Yellow periods
- time lost to derating
This creates a race equation:
net_race_time = driving_time + pit_time + derating_time - neutralization_absorption
The project must not hide the pit loss. It must make the pit loss explicit and then design around it.
Neutralizations Change the Economics
Le Mans is rarely a perfectly green 24-hour run. Safety Cars, slow zones, and Full Course Yellows change the value of time. If the field is already slowed, the relative penalty of entering the pits and charging can be reduced.
This does not make charging free. It creates opportunity windows.
The model should include:
- probability of Safety Car events
- expected duration of neutralizations
- pit entry timing during neutralizations
- minimum charge versus deep charge decisions
- track position effects
- restart energy targets
This is where the EV strategy becomes different from a fuel strategy. The car may choose to charge not because it is empty, but because the race has created a lower-cost energy window.
Mass Sensitivity Must Be Included Early
Energy use is not independent of mass. The model must test vehicle mass bands, for example:
- lightweight target mass
- realistic engineering mass
- safety-heavy mass
- worst-case growth mass
For each mass band, the model should estimate:
- lap time
- energy per lap
- tire degradation
- brake demand
- regeneration potential
- cooling requirement
The most dangerous mistake is to build a model around an optimistic mass target and then discover that the real vehicle is 150 kg heavier.
The Output of the Model
The energy and stint model should produce:
- target kWh/lap
- usable battery capacity range
- expected laps per stint
- minimum charging power
- expected green-flag pit loss
- Safety Car charging value
- derating sensitivity
- mass sensitivity
- total race distance scenarios
These outputs become requirements for the battery, cooling, drivetrain, charging, and race strategy teams.
The Model Philosophy
The model should not be built to prove that the project works. It should be built to find where the project breaks.
If the model shows that the car needs impossible charging power, the concept must change. If it shows that mass sensitivity is too high, the architecture must change. If it shows that the car depends on unrealistic Safety Car luck, the strategy must change.
The model is not the answer. It is the first honest filter.
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