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BetterFleet Assumptions

Last updated: 07/06/2022
The following is an overview of the key assumptions that have been used in the BetterFleet product.

Electricity Type and Costs

There are currently two tariff types included - a time of use, peak / shoulder / offpeak or single rate, where all rate bands are the same. The electricity price is configurable by the user, but by default uses cheapest suitable local prices from and an appropriate feed in tariff from

Car Costs

Purchase Price

The purchase price is the base price before on-road costs and taxes, based on manufacturer pricing, excluding GST.

Servicing and Tyre Costs

Our methodology for maintenance and servicing uses a regression based on the latest RACV dataset, tyres sizes and published servicing costs, that includes vehicles across the main power trains BEV, PHEV, HEV and ICE.

Fuel Prices

The cost of Diesel and Petrol at the pump is user configurable. The default is based on prices at State Capitals provided by the Australian Automobile Association

Taxes and Duties

Our tax model uses state specific registration costs including the registration fee and all relevant levies, insurances (where mandated), transfer registration, stamp duties (where applicable), administration fees (where applicable) and other relevant fees and charges as outlined on the following websites:
In addition we include Federal government fees such as Luxury Car Tax (LCT) and Fringe Benefit Tax (FBT).


Depreciation is the estimate of loss in value of vehicle, currently calculated using the ATO tax office values.
Months Value
12 65.6%
24 56.3%
36 46.9%
48 37.5%
60 28.1%
A custom depreciation model, based on second market prices and other variables has been developed and is being tested based on a hedonic model created using actual sold data from North America.
Elements of the price were constructed on a Hedonic Pricing Basis, breaking the value into the following elements: Age, Initial Cost, Mileage and Range.
An ordinary least square (OLS) regression was fitted for each powertrain, using a set of all used vehicle makes and models sold in North American in 2015, with data gathered from
It was found that the Range did not influence the value and it was dropped from the equation. The other coefficients vary by powertrain in magnitude of their effect on the final predicted price.
The overall formula is:
Predicted Price = AgeCoeff x Age + AgeSquaredCoeff x Age2 + CostCoeff x InitialCost + MileageCoeff x Mileage with each powertrain having their own Coeff as fitted from the OLS regression. The R2 error, or how well the fitted line explains the data, in each case is above 96%.

Tax Refund

The tax refund amount is a guide figure based on the ATO calculation for income tax return and generally accepted accounting practices (GAAP).
The overall formula is:
Income Tax Relief = (Apportioned Cost + FBT Cost) x Corporation Tax where Apportioned Cost = (Operating Costs + Operating Lease Payments + Finance Lease Interest - Gain or Loss on Sale + Depreciation Amount) x Percent Business Use, and FBT Cost = (Gross Taxable Value - Employee Contribution) x Gross-Up Rate for Schedule 1 Assets x The Rate of FBT for Schedule 1 Assets
See ATO website for further details.

Carbon Emissions

The carbon emissions are calculated using carbon emitted based on the driving distances under pure electric and pure fossil usage, and a mix for hybrid.
For all vehicles they are based on well to wheel (WTW) emissions, which includes the well to tank (WTT) and tailpipe emissions.
The vehicle efficiency is calculated based on driving and fuel mix, and the car specific g/km for tailpipe emissions.
The WTT carbon for ICE fuel is calculated based on researched well to tank factors from LowCVP.
The WTT for electricity is based on the intensity factors of the electrical grid in kg/kWh from local sources, updated on a regular basis and where possible using projections of the grid intensity over time. This is modified by the amount of green energy that is purchased by the user.

Further Details

For further details of the specific data please contact us at