Multi-plate wet clutches and theirs actuators are an important part of the automatic transmission gearboxes. Modern electronic controls operate the clutch by an electro-hydraulic actuator. In this paper a new model for a wet clutch actuated by an electro-hydraulic valve used in a real vehicle for automatic transmission is developed. The model captures the essential dynamics of the electro-hydraulic valve and clutch circuit, which operates on a given pressure range commanded by a transmission shifting signal. The model is validated against the data obtained from a test bench which includes the DQ250 wet clutch actuated by the electro-hydraulic valve DQ500 and the comparison shows good agreement. Based on the developed model, a useful clutch prediction control scheme was designed. Simulation results obtained with predictive control strategy are presented and discussed.

The control of autonomous vehicles is a topic of great interest nowadays due to their inherent advantages. They can increase the safety, lower the fuel consumption and thus reduce the travel costs, improve the driving comfort and reduce the traffic congestion. Still the control of vehicle dynamics is an open subject, many researchers and companies wanting to improve the existing strategies or to develop novel ones. The developed solutions should help the driver and ensure a safer driving at the same time. Thus, this paper proposes a solution to control the lateral and longitudinal dynamics of a vehicle. The first step is the modeling of both dynamics by constructing a nonlinear model based on the laws of physics that considers the lateral and longitudinal motions of a vehicle. To design a linear model predictive control (MPC) strategy, the nonlinear lateral model is linearized. The aim is to design two control algorithms based on the linear model of the vehicle dynamics, one for the lateral dynamics and one for the longitudinal dynamics and apply them for the full nonlinear model of the system. Both controllers were tested together by simulating an overpassing. This is a maneuver in which the lateral position and the longitudinal velocity must be controlled. The MPC algorithm for the lateral dynamics uses a predefined reference trajectory and the states of the system to compute the command for the vehicle such that the vehicle follows the trajectory and satisfies the imposed constraints. The controller for the longitudinal velocity of the vehicle computes the command such that the velocity of the vehicle follows its reference. The results illustrate that the MPC algorithms manage to control the vehicle and to satisfy the defined requirements.

The 5G technology offers a higher complexity than earlier generations, introducing a new type of network designed to connect virtually everyone and everything together, including vehicles, smart devices, and road infrastructure, while ensuring security, coverage, and increased performance. Therefore, following all these aspects introduced by 5G technology, different reliability assessments are necessary for optimal operation. This paper presents a practical method of real-time data measurement, which aims to obtain the necessary information to thoroughly evaluate the 5G network. The used hardware setup is based on the SIM8200EA-M2 platform for connecting to different mobile terminals. Moreover, different types of measurements are illustrated, as well as the validation of various 5G network parameters. To evaluate the 5G network performance, several performance indicators resulting from data measurement were analyzed, such as 5G network coverage, signal strength and quality, signal-to-noise ratio, throughput, communication channel quality, and transmission power. The obtained results deal with different aspects of cellular communication and can be used to analyze the performance of 5G networks.