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Vehicle dynamics stability control systems rely on the amount of so-called sideslip angle and yaw rate. As the sideslip angle can be measured directly only with very expensive sensors, its estimation has been widely studied in the literature. Because of the large non-linearities and uncertainties in the dynamics, model-based methods are not a good solution to estimate the sideslip angle. On the contrary, machine learning techniques require large datasets that cover the entire working range for a correct estimation. In this paper, we propose an integrated artificial neural network and unscented Kalman filter observer using only inertial measurement unit measurements, which can work as a standalone sensor. The artificial neural network is trained solely with numerical data obtained with a Vi-Grade model and outputs a pseudo-sideslip angle which is used as input for the unscented Kalman filter. This is based on a kinematic model making the filter completely transparent to model uncertainty. A direct integration with integral damping and integral reset value allows the estimation of the longitudinal velocity of the kinematic model. A modification strategy of the pseudo-sideslip angle is then proposed to improve the convergence of the filter’s output. The algorithm is tested on both numerical data and experimental data. The results show the effectiveness of the solution.

No abstract

Current ADAS systems can improve vehicle safety directly influencing its dynamics, reducing the impact of human error while driving. These functionalities have a high impact on the complexity of each unit installed on the car, potentially increasing the development time. In this work, a Hardware in the Loop testing bench and methodology for Autonomous Emergency Braking system is presented, aiming to enable a faster system development process. A commercial production brake by wire unit has been installed on a real-time driving simulator. The AEB functionality of the unit is activable in real-time during the simulation, by the means of a customizable control strategy. Two different AEB controllers have been https://saemobilus.sae.org/content/2022-01-0099/ 3/3

The performance of semi-active differential systems is deeply influenced by the way in which they are actuated. Conventional semi-active systems are actuated by pressure-controlled hydraulic actuators that, despite their good dynamical behaviour, are relatively inefficient. In this work, the authors propose an innovative controlled hydraulic pump solution that is able to drastically improve the efficiency and to reduce the overall encumbrances, maintaining very high performance in terms of dynamical behaviour and corresponding frequency response. The authors investigate design criteria of the proposed solution, describe a simulation model and validate design and simulation models with experimental data.