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E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Still, major challenges for large scale deployment remain. They include higher maturity with respect to performance (e.g., range, interaction with the grid), development efficiency (e.g., time-to-market), or production costs. Additionally, an important market transformation currently occurs with the co-development of automated driving functions, connectivity, mobility-as-a-service. New opportunities arise to customize road transportation systems toward application-driven, user-centric smart mobility solutions.

E-mobility is a game changer for the automotive domain. It promises significant reduction in terms of complexity and in terms of local emissions. With falling prices and recent technological advances, the second generation of electric vehicles (EVs) that is now in production makes electromobility an affordable and viable option for more and more transport mission (people, freight). Current e-vehicle platforms still present architectural similarities with respect to combustion engine vehicle (e.g., centralized motor). Target of the European project EVC1000 is to introduce corner solutions with in-wheel motors supported by electrified chassis components (brake-by-wire, active suspension) and advanced control strategies for full potential exploitation. Especially, it is expected that this solution will provide more architectural freedom toward “design-for-purpose” vehicles built for dedicated usage models, further providing higher performances.

Brush models permit a more physical simulation of tire performance in comparison with models based on empirical formulas. The paper presents an empirical model for the estimation of tire temperature as function of the actual working conditions of the component. The estimated temperature values enter a tire brush model and provoke the variation of the performance in terms of tangential forces. The model can be empirically tuned through experimental data showing the variation of tire performance as function of temperature. The experimental validation of the model is dealt with in detail.

This paper deals with the development of a Lap Time Simulator in order to carry out a first approximate evaluation of the potential benefits related to the adoption of the Kinetic Energy Recovery System (KERS). KERS will be introduced in the 2009 Formula 1 Season. This system will be able to store energy during braking and then use it in order to supply an extra acceleration during traction. Different technologies (e.g. electrical, hydraulic and mechanical) could be applied in order to achieve this target. The lap time simulator developed by the authors permits to investigate the advantages both in terms of fuel consumption reduction and the improvement of the lap time.

The aim of this paper is the conception of a tire model which allows a good fit with the physical experimental behavior of the component. In the meanwhile, the model should be simple enough to permit real time vehicle dynamics simulation, in the same way as the diffused Pacejka's model. The paper discusses the influence of the model for the estimation of contact patch properties on the overall tire forces and moments. It demonstrates that unrealistic models of the contact patch can lead to a good fit with the experimental data (in terms of forces and self-aligning moment), even if the real physics of the tire is not reproduced. A realistic model implies a significant reduction of the stiffness of the brushes as a function of the vertical load between the tire and the road surface.