Torque vectoring is a widely known technique to improve vehicle handling and to increase stability in limit conditions. With the advent of electric vehicles, this is becoming a key topic since it is possible to have distributed powertrains, i.e., multiple motors are adopted, in which each motor is controlled separately from the others. Moreover, electric motors deliver the torque required by the controller faster and more precisely than internal combustion engines, active differentials and conventional hydraulic brakes. The state of the art of Direct Yaw Moment Control (DYC) techniques, ranging from classical to modern control theories, are analyzed and discussed in this paper. The aim is to give an overview of the currently available approaches while identifying their drawbacks regarding performances and robustness when dealing with common issues like model uncertainties, external disturbances, friction limit and common state estimation problems. This contribution analyzes all the steps from the lateral dynamics reference generation to the desired control action computation and allocation to the available actuators. In addition, some of the presented control logic is evaluated in a simulation environment for a passenger car. Results of both open-loop and closed-loop maneuvers allow the comparison and clarification of each control strategy’s key advantages.

Nowadays, micro-mobility is one of the major global trends in cities for the innovation of the transport system. In this context a breakthrough introduction of electric kick scooters (e-scooters) has taken place. Unfortunately, these mobility systems cause several accidents mainly for two reasons: wrong use and inadequate safety requirements. Since e-scooters are quite a new type of vehicle, generally accepted mathematical models are yet to be developed. These models can be useful in understanding the dynamical properties of this type of vehicle thus improving its design to reduce riding accidents. The present paper presents a model for the simulation of the vertical dynamic behavior of e-scooters that accounts also for the mechanical impedance of the driver, thus allowing to estimate the overall driver's comfort and road holding capabilities providing information on possible speed limitations in case of bad road conditions. Furthermore, the paper shows experimental envelope curves for lumped obstacles obtained with a dedicated test bench on which the e-scooter is fixed and tested under different conditions of vertical load and tire inflation pressure.

With a shift in the automotive industry’s focus towards sustainability and energy efficiency, optimizing vehicle handling dynamics has been put on a secondary level. Moreover, there is a growing trend towards comfort-oriented design, conversely to the vehicle-handling one. Nevertheless, recent advancements such as the integration of multiple independently controlled electric motors on a vehicle is enabling torque vectoring, which offers a promising opportunity for reconciling these conflicting objectives. This paper proposes a novel approach for jointly improving vehicle handling and energy efficiency performance. Indeed, through advanced simulation techniques, the effects of various suspension configurations are explored to strike a balance between cornering performance and energy consumption. Then, a torque vectoring controller is designed in combination with a meticulous tuning of the suspension setup. This innovative approach of considering the active control design together with the suspensions’ setup allows to obtain superior performances. Indeed, the desired vehicle cornering capabilities can be achieved while also guaranteeing a significantly more efficient vehicle in straight-line running, which covers most of the usual road driving time.

Railway transportation is widely known for its high safety level. Nevertheless, derailments still occur, typically causing large service disruptions and economic losses. For these reasons, identifying derailments is of paramount importance for improving the railway transportation safety. This paper presents the design and testing of a derailment detection system for freight trains. A derailment detection algorithm able to process and analyze data in real-time has been designed leveraging the knowledge gained from full-scale derailment tests on freight wagons. Moreover, a LoRa-based wireless communication system has been implemented to relay freight wagon derailment warnings to the locomotive. The effectiveness of the proposed derailment detection algorithm is proved through its deployment to a freight wagon used for common operations. In that, it demonstrated increased robustness against derailment false triggering compared to traditional mechanic-pneumatic detectors. Furthermore, the proposed wagon-locomotive wireless communication system is proven effective in transmitting information across various convoy compositions and freight wagon loading conditions during operational testing on the railway line.