In the context of automated driving, Electric Power Steering (EPS) systems represent an enabling technology. They introduce the ergonomic function of reducing the physical effort required by the driver during the steering maneuver. Furthermore, EPS gives the possibility of high precision control of the steering system, thus paving the way to autonomous driving capability. In this context, the present work presents a performance assessment of an EPS system designed for a full-electric all-wheel-drive electric prototype racing in Formula Student Driverless (FSD) competitions. Specifically, the system is based on the linear actuation of the steering rack by using a ball screw. The screw nut is rotated through a belt transmission driven by a brushless DC motor. Modeling and motion control techniques for this system are presented. Moreover, the numerical model is tuned through a grey-box identification approach. Finally, the performance of the proposed EPS system is tested experimentally on the vehicle through both sine-sweep profiles and co-simulated driverless sessions. The system performance is assessed in terms of reference tracking capability, thus showing favorable results for the proposed actuation solution.

This work proposes a systematic methodology for designing an active leveling system (ALS) actuator for lunar landing application. The ALS actuator is integrated into an inverted tripod leg layout, exploiting a honeycomb crushable damper as a shock absorber. The proposed ALS actuator is fitted within the leg’s primary strut and features a custom permanent-magnet synchronous machine rigidly coupled with a lead screw. The actuator aims to both provide proper leg deployment functioning and compensate for the different shock absorber deformations during landing. The leg dynamic behavior is simulated through a parameterized multi-body model to investigate different landing scenarios. First, a parametric sensitivity approach is used to optimize the transmission system and the electric machine characteristics. Then, the electric motor model is numerically validated and optimized through electromagnetic finite element analysis. To validate the proposed ALS design methodology, a virtual test bench is used to assess the ALS performances under different load scenarios. It is found that the proposed methodology is able to yield a compact, well-sized actuator which is numerically validated with the EL3 platform as a case study.

This paper describes the modeling and experimental validation of the performance of two height adjustment suspensions with concentrically and eccentrically mounted screws. In the former solution, an anti-rotation system is required for the generation of reaction torque on the power screw–nut mechanism. The anti-rotation represents the main drawback of such mechanisms. In contrast, the eccentric solution attempts to solve this problem by placing the screw–nut mechanism eccentrically with respect to the shock absorber tube axis. In this paper, the working principle of the eccentric solution is explained. Its performance is compared to the concentric counterpart through simulations and experiments. Although the efficiencies of eccentric and concentric systems are very similar at the power screw, overall efficiencies differ substantially. During lifting, average efficiencies are around 3.4% and 6.5% for concentric and eccentric systems, respectively. When lowering, these values are 6.2% and 26%. The higher overall efficiency of the eccentric screw system is attributed to the anti-rotation system and the balancing of the bending moment due to the offset application of the load. To yield a complete perspective on the eccentric mounted screw solution, four prototypes are installed and tested on a demo vehicle.

Real-time estimation of vehicle sideslip angle is essential for both safety and performance applications. This study presents a temperature-adaptive Extended Kalman Filter (EKF) that estimates the sideslip angle of a racing vehicle by integrating dynamic and kinematic information. A temperature-dependent Pacejka tire model, derived directly from track tests, is embedded in a 3-degree-of-freedom dual-track vehicle model and used within the EKF to compensate for temperature-induced variations in tire behavior. The adaptive model parameters are identified from standard on-track maneuvers conducted at different tire temperatures, without the need for additional indoor rig testing. Experimental validation on a race track demonstrates that incorporating tire temperature adaptation and combining dynamic and kinematic estimation significantly enhance estimation accuracy, particularly underow-grip and high-performance driving conditions attested by a reduction of 40–50% in RMS error and a further reduction in maximum absolute error.