Planning an itinerary for an electric vehicle

The steady increase in oil prices and awareness regarding environmental risks due to carbon dioxide emissions are promoting the current interest in electric vehicles. However, the current relatively low driving range (autonomy) of these vehicles, especially compared with the autonomy of existing internal combustion vehicles, remains an obstacle to their development. In order to reassure a driver of an electric vehicle and allow him to reach his destinations beyond the battery capacity, we describe a system which generates an energy plan for the driver. We present in this paper the electric vehicle ecosystem and we focus on the contribution of using the generalized multi-commodity network flow (GMCNF) model as a vehicle routing model that considers energy consumption and charging time in order to ensure the usage of an electric vehicle beyond its embedded autonomy by selecting the best routes to reach the destination with minimal time and/or cost. We also present some perspectives related to the utilization of autonomous electric vehicles and wireless charging systems. We conclude with some open research questions

Reducing the Gap Between Formal and Informal Worlds in Automotive Safety-Critical Systems

Presented also at IEEE 5th Annual International System Conference, Montreal, April 2011.The upcoming ISO26262 standard, which deals with the functional safety of roadvehicles, will induce car manufacturers to adapt the way in which vehicle systems are usuallydeveloped. To achieve this, more rigorous development processes along with new tools andtechniques will most certainly be necessary. This paper presents an overview of currentinitiatives at Renault dealing with the improvement of development processes for mechatronicsystems to comply with ISO 26262. It focuses on introducing more formalization in thesystems engineering design process via the definition of an ontology to formalize the conceptsand knowledge of the systems engineering, functional safety and automotive specialty domains(e.g. braking, energy management). The ontology is at the heart of our improvement initiativessince it allows establishing logical consistency of the whole design process. A regenerativehybrid braking system integrated into a full electrical vehicle will serve as the case study for theevaluation of the improvements made possible by the approach

Confiance.ai, avancées scientifiques et technologiques

Pilier technologique du Grand Défi National « Sécuriser, fiabiliser et certifier des systèmes fondés sur FIA », le programme Confiance. ai est une initiative financée par France 2030, avec pour ambition de développer un environnement méthodologique outillé au service de la conception et de l'intégration d'une lA sûre, fiable et sécurisée dans les systèmes critiques (automobile, aéronautique, défense et sécurité, énergie, industrie...).Lancé en 2021 pour quatre ans, de nombreuses avancées scientifiques et technologiques ont été réalisées depuis et se sont matérialisées au travers de la définition d'une approche globale d'ingénierie de l'IA et de quatre plateformes enrichies par plus d'une centaine de composants:1) plateforme consacrée à l'ingénierie de la donnée tout au long de son cycle de vie ; 2) plateforme dédiée à l'explicabilité; 3) ensemble de librairies dédiées à la robustesse et au monitoring des systèmes critiques à base d'IA, et 4) plateforme destinée à l'embarquabilité des composants d'IA