Rafel Perelló i Ribas submitted his PhD thesis Data assimilation for real-time dynamic prediction of wind-induced forces in vehicle platooning, supervised by Antonio Huerta and Sergio Zlotnik at the Universitat Politècnica de Catalunya (November 2025).
Nowadays, in the field of automotive aerodynamics, there is a big concern on concepts such as safety and energy efficiency. This binds with the emerging field of autonomous vehicles where it is critical to ensure safe control and stability of the vehicle under all conditions that might be encountered in realistic situations [1-3]. Moreover, it allows the possibility to explore innovative solutions such as platooning techniques to improve energy efficiency and increase road capacity [4, 5].
The increase of computational power over recent years has allowed engineers and scientists to study the problems of parametric Partial Differential Equations (PDE). That is, to study how the solution of a PDE depends on some parameters defining material constants, body forces, boundary conditions, domain geometry, etc. [6, 7]. However, in many engineering applications, the computational cost of finding a solution of a PDE for a single combination of the parameters is still very high. This is particularly true in Computational Fluid Dynamics (CFD) [8], thus it is unfeasible to predict the aerodynamic effects on vehicles under a wide range of conditions using standard techniques.
Surrogate modelling techniques are introduced to obtain a surface response of parametric PDEs for problems where traditional methods are unfeasible. An interesting family of surrogate methods are those base on multifidelity, i.e., methods that combine information obtained from low and high-fidelity simulations [9, 10]. Multifidelity methods do not simply use low fidelity simulations to obtain cheap approximations and then switch to high fidelity if higher accuracy is desired. In contrast, they use simultaneously information obtained from low and high-fidelity simulations to obtain a single surrogate.
In this work we devise surrogate techniques based on multifidelity extensions of the Smolyak approximation method [9, 11] to predict the aerodynamic forces acting on a vehicle in platoon conditions on realistic road conditions. We consider the geometry of the leading vehicle, the spacing between vehicles, the speed of travelling and the presence of cross-wind as paramters of our model and show that the devised methodology is able to construct an accurate surrogate model while reducing considerably the computational cost required by standard techniques.
References
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[2] P. Gilliéron and C. Noger Contribution to the analysis of transient aerodynamic effects acting on vehicles SAE transactions113 (2004), 893–900.
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[10] B. Peherstorfer, K. Willcox, and M. Gunzburger Survey of multifidelity methods in uncertainty propagation, inference, and optimization SIAM review60.3 (2018), 550–591.
[11] C. Piazzola, L. Tamellini, R. Pellegrini, R. Broglia, A. Serani, and M. Díiez. Comparing multi-index stochastic collocation and multi-fidelity stochastic radial basis functions for forward uncertainty quantification of ship resistance Engineering with computers39 (2023), 2209–2237.