FFD Explanatory Notes¶

Objective¶

Present an initial Fundamental Financial Driver (FFD-1) for rider fuel-cost differential to establish LEV market opportunity narrative.

Canonical narrative for LEV market communication: - Every kWh of electricity serviced generates savings for all involved.

Scenario Inputs (2W Baseline)¶

gas_price_per_l: 1.00 USD/L
electricity_price_per_kwh: 0.15 USD/kWh
2w_km_per_liter: 31 km/L
2w_km_per_kwh: 28 km/kWh

These values are codified in data/model_parameters.json under fundamental_financial_drivers.

Driver Results (FFD-1)¶

Computed using models/ffd_model.py (calculate_2w_fuel_savings_driver).

Metric	Value	Unit
`2w_gas_cost_per_km`	`0.03`	USD/km
`2w_elec_cost_per_km`	`0.01`	USD/km
`2w_savings_per_km`	`0.03`	USD/km
`2w_savings_pct`	`83.39`	%
`2w_savings_per_kwh`	`0.75`	USD/kWh

Savings Apportioning Baseline¶

Initial split array (sum = 100%):

Rider: 25%
BCS: 25%
SNS: 25%
X: 25%
Others: 0% (auto-computed as 1 - sum(identified shares))

Applied to 2w_savings_per_kwh = 0.75 USD/kWh:

Party	Share	Allocated Savings
Rider	25%	0.19 USD/kWh
BCS	25%	0.19 USD/kWh
SNS	25%	0.19 USD/kWh
X	25%	0.19 USD/kWh
Others	0%	0.00 USD/kWh

Interpretation¶

The baseline shows a strong positive fuel-cost differential in favor of electric operation.
2w_savings_per_kwh is the bridge metric from rider economics to ecosystem value allocation.
The kWh-centric framing is intuitive for riders (who buy electricity) and for ecosystem operators (who manage energy throughput).
Apportioning avoids over-optimistic single-party interpretation by distributing the gross savings signal across ecosystem participants.

Financial Team Notes: How to Explain This to Riders¶

Use this walk-through when discussing price and fairness of savings split.

Example Question¶

If a rider purchases 3 kWh at 0.60 USD/kWh, did they save money?

Step-by-step (Rider Lens)¶

Rider pays for electricity:
3 x 0.60 = 1.80 USD
Distance from that energy:
3 x 28 = 84 km
Gas needed for same distance:
84 / 31 = 2.71 L
Gas cost for same trip:
2.71 x 1.00 = 2.71 USD
Rider savings:
2.71 - 1.80 = 0.91 USD

Conclusion: yes, rider saves money (0.91 USD over that trip).

Why This Can Still Break the Allocation Rule¶

Saving money alone is not enough. We also enforce savings apportioning across ecosystem parties.

With baseline assumptions: - Gas-equivalent value per electric kWh: - V = (28/31) x 1.00 = 0.9032 USD/kWh - Total system savings pool per kWh: - Pool = V - 0.15 = 0.7532 USD/kWh

At rider selling price 0.60 USD/kWh: - Rider savings per kWh: - 0.9032 - 0.60 = 0.3032 USD/kWh - Rider share of pool: - 0.3032 / 0.7532 = 40.3%

This is above the 25% rider allocation target, so it leaves too little for the rest of the ecosystem.

Price That Satisfies 25% Rider Allocation¶

Target rider savings per kWh: - 0.25 x 0.7532 = 0.1883 USD/kWh

Required rider price: - Price = 0.9032 - 0.1883 = 0.7149 USD/kWh

Practical guidance: - Use 0.715 USD/kWh as the exact target. - If pricing to cents and avoiding rider overallocation, use 0.72 USD/kWh.

Mind Twister for Training: The Near-Break-Even Price¶

Question: - If station price is 0.9024 USD/kWh, does rider gas money cover the same range?

Use baseline assumptions: - gas_price_per_l = 1.00 - 2w_km_per_liter = 31 - 2w_km_per_kwh = 28

Circular test:

Electric cost per km:
0.9024 / 28 = 0.03223 USD/km
Gas cost per km:
1.00 / 31 = 0.03226 USD/km
Difference:
0.03226 - 0.03223 = 0.00003 USD/km (tiny rider savings)

Equivalent trip check at 28 km: - Electric spend: 1 x 0.9024 = 0.9024 USD - Gas spend for same 28 km: (28/31) x 1.00 = 0.9032 USD - Rider savings: 0.0008 USD

Training takeaway: - At this price, rider economics are almost identical to gas. - This is a useful boundary case to explain how sensitive rider FFD is to electricity pricing. - It also shows why enforcing savings allocation discipline matters for ecosystem balance.

Next FFD Reporting Blocks¶

Compare 2W scenarios across multiple market price bands.
Extend FFD family with additional non-fuel opportunity drivers.