ECOGEM is an integrated intelligence and learning functionalities approach towards on-board systems for fully electric vehicles (FEVs). This allows these vehicles reaching their destination via energy efficient itineraries while considering in real-time technical and surrounding features (i.e. battery level, traffic, available charging points, etc.).
A key acceptability criterion for drivers regarding a switch towards FEVs is their range, i.e. the degree of autonomy they are likely to offer. In view of providing the highest possible autonomy, ICT-based solutions are needed to inform the driver of energy-related issues and strengthen FEVs' autonomy and reliability. However, these solutions should consider several parameters in order to offer in real-time a relevant diagnosis of the FEVs autonomy as well as comprehensive information regarding the immediate external situation the FEV is actually involved in. The outcome of such a solution then should be capable of delivering routes options to the driver for reaching his/her destination.
ECOGEM is a trans-European project, co-financed by the FP 7 grant funding programme. It was coordinated by TEMSA Global (Turkey) from September 2010 to August 2013. ECOGEM has developed an on-board device (called Advanced Driver Assistance System or ADAS) capable of proposing the driver the most energy-efficient and optimised time-to-destination itinerary. As a matter of fact, the innovative machine learning approach lied in its learning-by-doing ability to predict congested routes and bottlenecks. This feature was based on the knowledge the system gathers through its own experience as well as information sharing with other vehicles (vehicles-to-vehicles or V2V) and surrounding communication infrastructure (vehicle-to-infrastructure or V2I). However, ADAS was a multifaceted innovation as it covered many areas:
- ADAS carried out a continuous tracking of the energy consumption and connected it to the vehicle travel history.
- ADAS performed an autonomous optimised route planning based on the tracked records, i.e. its own experience.
- ADAS made a cooperative optimised route planning via V2V interactions. This community-based approach would allow any equipped FEV to enrich its knowledge thanks to shared experience. This would also make possible an optimised fleet management with a centralized management platform (i.e. V2I interactions) towards public transport.
- ADAS achieved a real-time mapping of available recharging points and book the most convenient. The system was able to suggest the best location and the recharging strategy according to the battery level and contextual information.
Why did it work?
ECOGEM gathered a multidisciplinary team throughout Europe covering the transport value chain by including universities, technical centres and experts and the industry. The approach was therefore not only developed at laboratory level but also demonstrated in real-life conditions. To this end, two developed solutions were carried out with actual vehicles: a two-seater car was provided by Pininfarina (Italy) and two alternative sustainable transport electric buses were provided by TEMSA Global.
As the FEV’s ADAS has been demonstrated, the maturity level of the on-board system is estimated to be 8 on the TRL scale. The next step to be considered is the validation of the economic feasibility of the approach.