Project SummaryThe development and adoption of fuel economy technologies can be hindered by the diversity of existing vehicles, operating conditions, driver behaviour, etc. This diversity of conditions increases the complexity a technology has to cater for and also adds uncertainty to any predictions of technology effects - be it for certification of CO2 reduction or for defining a business case for technology adoption by an operator.
We propose the development and piloting of a system for collecting trip data from light and heavy vehicles and for estimation of fuel consumption. Data sources can be GPS, maps, OBD2, vehicle specs and load data and others. Data security and privacy considerations need to be addressed approriately. The feasibility of such an approach has previously been positively tested using RDE data for a single vehicle.
Use cases are seen in (1) technology development, e.g., big data approaches for optimizing load factors or driver behaviour; (2) technology marketing by addressing technology specific segments where CO2 reductions can be delivered; (3) operator business cases can be supported by robust predictions of technology benefits; (4) CO2 reduction metrics by delivering transparent and auditable models for with / without technology; (5) policy development.
As a pilot we propose demonstrating the system using a mature fuel consumption technology. Evoxar's lubrication product, GERnano, is one option for this; typical CO2 reduction is above 5%, therefore significant results should be possible without excessively long timeframes for collecting baseline data.
The regional collaboration is required to capture the full breadth of regulation and policies, vehicles, geography and road conditions. Also appreciating the cultural dimension of adopting such a system calls for broad engagement.