Vehicular control systems are required to be both extremely reliable and robust to different environmental conditions, e.g. load or tire-road friction. In this paper, we extend a new paradigm for state estimation, called Twin-in-the-Loop filtering (TiL-F), to the estimation of the unknown parameters describing the vehicle operating conditions. In such an approach, a digital-twin of the vehicle (usually already available to the car manufacturer) is employed on-board as a plant replica within a closed-loop scheme, and the observer gains are tuned purely from experimental data. The proposed approach is validated against experimental data, showing to significantly outperform the state-of-the-art solutions.
@article{arxiv.2309.01461,
title = {Joint vehicle state and parameters estimation via Twin-in-the-Loop observers},
author = {Federico Dettù and Simone Formentin and Sergio Matteo Savaresi},
journal= {arXiv preprint arXiv:2309.01461},
year = {2023}
}