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International Journal of Automotive Technology > Volume 24(2); 2023 > Article
International Journal of Automotive Technology 2023;24(2): 347-365.
doi: https://doi.org/10.1007/s12239-023-0029-2
Giuseppe Guastadisegni 1, Kai Man So 1, Alberto Parra 2, Davide Tavernini 1, Umberto Montanaro 1, Patrick Gruber 1, Leonardo Soria 3, Giacomo Mantriota 3, Aldo Sorniotti 1
1Centre of Automotive Engineering, School of Mechanical Engineering Sciences
2Tecnalia Research and Innovation, Basqua Research and Technology Alliance
3Department of Mechanical Engineering, Mathematics and Management
PDF Links Corresponding Author.  Aldo Sorniotti  , Email. a.sorniotti@surrey.ac.uk
Next-generation accurate vehicle localization and connectivity technologies will enable significant improvements in vehicle dynamics control. This study proposes a novel control function, referred to as pre-emptive braking, which imposes a braking action if the current vehicle speed is deemed safety-critical with respect to the curvature of the expected path ahead. Differently from the implementations in the literature, the pre-emptive braking input is designed to: a) enhance the safety of the transient vehicle response without compromising the capability of reaching the cornering limit, which is a significant limitation of the algorithms proposed so far; and b) allow – in its most advanced implementation – to precisely constrain the sideslip angle to set levels only through the pre-emptive control of the longitudinal vehicle dynamics, without the application of any direct yaw moment, typical of conventional stability control systems. To this purpose, a real-time-capable nonlinear model predictive control (NMPC) formulation based on a double track vehicle prediction model is presented, and implemented in its implicit form, which is applicable to both human-driven and automated vehicles, and acts as an additional safety function to compensate for human or virtual driver errors in extreme conditions. Its performance is compared with that of: i) two simpler – yet innovative with respect to the state-of-the-art – pre-emptive braking controllers, namely an NMPC implementation based on a dynamic point mass vehicle model, and a pre-emptive rule-based controller; and ii) a benchmarking non-pre-emptive rule-based trail braking controller. The benefits of pre-emptive braking are evaluated through vehicle dynamics simulations with an experimentally validated vehicle model, as well as a proof-of-concept implementation on an automated electric vehicle prototype.
Key Words: Nonlinear model predictive control, Stability control, Pre-emptive control, Braking, Sideslip angle constraint, Reference curvature
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