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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.

Electric vehicles with multiple motors permit continuous direct yaw moment control, also called torque-vectoring. This allows to significantly enhance the cornering response, e.g., by extending the linear region of the vehicle understeer characteristic, and by increasing the maximum achievable lateral acceleration. These benefits are well documented for human-driven cars, yet limited information is available for autonomous/driverless vehicles. In particular, over the last few years, steering controllers for automated driving at the cornering limit have considerably advanced, but it is unclear how these controllers should be integrated alongside a torque-vectoring system. This contribution discusses the integration of torque-vectoring control and automated driving, including the design and implementation of the torque-vectoring controller of an autonomous electric vehicle for a novel racing competition. The paper presents the main vehicle characteristics and control architecture.

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.

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.

It is universally recognized that torsional stiffness is one of the most important properties of a vehicle chassis, [ 1 ]. There are several reasons for which high chassis stiffness is preferable. Lack of chassis torsional stiffness affects the lateral load transfer distribution, it allows displacements of the suspension attachment points that modify suspension kinematics and it can trigger unwanted dynamic effects like resonance phenomena or vibrations, [ 2 ]. The present paper introduces two analytical vehicle models that constitute an efficient tool for a correct evaluation of the main effects of chassis torsional stiffness on vehicle dynamics. In the first part an enhanced steady-state vehicle model is derived and employed for the analysis of the vehicle handling. The model takes account of chassis torsional stiffness for the evaluation of the lateral load transfer and, by means of the concept of the axle cornering stiffness, includes the effects of tire non-linear behavior.