Torque Vectoring Control as an Energy-Efficient Alternative to Vehicle Suspensions Tuning

Michele Asperti (), Michele Vignati and Edoardo Sabbioni ()
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Michele Asperti: Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
Michele Vignati: Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy
Edoardo Sabbioni: Department of Mechanical Engineering, Politecnico di Milano, Via La Masa 1, 20156 Milan, Italy

Energies, 2024, vol. 17, issue 12, 1-17

Abstract: With a shift in the automotive industry’s focus towards sustainability and energy efficiency, optimizing vehicle handling dynamics has been put on a secondary level. Moreover, there is a growing trend towards comfort-oriented design, conversely to the vehicle-handling one. Nevertheless, recent advancements such as the integration of multiple independently controlled electric motors on a vehicle is enabling torque vectoring, which offers a promising opportunity for reconciling these conflicting objectives. This paper proposes a novel approach for jointly improving vehicle handling and energy efficiency performance. Indeed, through advanced simulation techniques, the effects of various suspension configurations are explored to strike a balance between cornering performance and energy consumption. Then, a torque vectoring controller is designed in combination with a meticulous tuning of the suspension setup. This innovative approach of considering the active control design together with the suspensions’ setup allows to obtain superior performances. Indeed, the desired vehicle cornering capabilities can be achieved while also guaranteeing a significantly more efficient vehicle in straight-line running, which covers most of the usual road driving time.

Keywords: vehicle lateral dynamics; suspension setup optimization; torque vectoring; camber angle; toe angle; energy consumption (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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