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Numerical hazard analysis of torque vectoring system for electric drivetrain considering handling uncertainty

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Abstract

This work aims to perform a hazard analysis and a risk assessment considering vehicle handling and control when an electric drivetrain delivers power to the ground with the support of a torque vectoring control system. In addition, the objective is to discover pathways to dynamics control that allows the synthesis and implementation of devices that yield improvements to vehicle handling. The scope of the evaluation is to assess the impact of the tyre dynamics’ variability on a Formula SAE Electric Vehicle independently driven by rear in-wheel motors. The context considers the tyre dynamics’ variability in coping with a torque vectoring strategy composed of feedforward and feedback signals. This strategy is derived using the simplest model for evaluating lateral vehicle dynamics, a bicycle model. However, the impact of the tyre dynamics’ variability is numerically assessed using a vehicle model comprising a TMEasy Tire model, suspension parameters, and the lateral transfer load. Numerical results demonstrate the importance of evaluating the specification to which vehicle systems are designed to ensure the safety of intended functionality by the system’s components.

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Acknowledgements

We would like to acknowledge the Rota 2030 programme enabling this and further studies with torque vectoring by independent traction motors. Maíra M. da Silva is also grateful to the National Council for Scientific and Technological Development—CNPq [grant number 303884/2021-5].

Funding

This research is carried out under the Rota2030 programme for developing automotive technology, with funding provided by the Federal Government of Brazil and the FUNDEP Research Foundation [project number 27192*55].

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Correspondence to Vinicius K. Marini.

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Marini, V.K., Sorban, B.A., da Silva, M.M. et al. Numerical hazard analysis of torque vectoring system for electric drivetrain considering handling uncertainty. J Braz. Soc. Mech. Sci. Eng. 46, 52 (2024). https://doi.org/10.1007/s40430-023-04604-0

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