Results 31 to 40 of about 9,438,636 (286)

Reinforcement Learning for Torque Vectoring in Electric Vehicles: A Review of Stability and Energy Optimization Methods

open access: yesIEEE Open Journal of Vehicular Technology
Torque vectoring can enhance dynamic stability and concurrently enable efficient energy management in electric vehicles (EVs) through optimized torque distribution. Nevertheless, conventional torque vectoring schemes often rely on fixed models and tuning,
Reza Jafari   +4 more
doaj   +1 more source

Reconfigurable Slip Vectoring Control in Four In-Wheel Drive Electric Vehicles

open access: yesActuators, 2021
Controllability, maneuverability, fault-tolerance/isolation and safety are significantly enhanced in electric vehicles (EV) equipped with the redundant actuator configuration of four-in-wheel electric motors (4IWM).
Gerardo Amato, Riccardo Marino
doaj   +1 more source

Implementation of torque vectoring control on a 1:12 scale electric vehicle with individually controlled motors

open access: yes, 2023
openQuesto lavoro è basato lo sviluppo di un veicolo elettrico in scala 1:12 con 4 motori che controllano in maniera indipendente ciascuna delle 4 ruote.
CANTON, ALICE
core  

Vehicle Dynamic Control with 4WS, ESC and TVD under Constraint on Front Slip Angles

open access: yesEnergies, 2021
To enhance vehicle maneuverability and stability, a controller with 4-wheel steering (4WS), electronic stability control (ESC) and a torque vectoring device (TVD) under constraint on the front slip angles is designed in this research.
Jaewon Nah, Seongjin Yim
doaj   +1 more source

Improved Torque Control Performance in Direct Torque Control using Optimal Switching Vectors

open access: yesInternational Journal of Power Electronics and Drive Systems (IJPEDS), 2015
This paper presents the significant improvement of Direct Torque Control (DTC) of 3-phases induction machine using a Cascaded H-Bidge Multilevel Inverter (CHMI). The largest torque ripple and variable switching frequency are known as the major problem founded in DTC of induction motor.
Muhd Zharif Rifqi Zuber Ahmadi   +4 more
openaire   +1 more source

Data-Driven Feedforward Compensation Tuning in Torque Vectoring Control

open access: yes, 2023
In automotive control, torque vectoring enhances a vehicle dynamical characteristic by independently allocating wheel torques. Torque vectoring algorithms are often based on some form of closed-loop yaw rate tracking, whose reference is generated ...
Corno M., Senofieni R., Savaresi S. M.
core   +1 more source

Implementation and Performances Evaluation of Advanced Automotive Lateral Stability Controls on a Real-Time Hardware in the Loop Driving Simulator

open access: yesApplied Sciences, 2023
This study concerns the comparative investigation of two advanced lateral stability automotive controllers with respect to a commercial solution. The research aims to improve the stability performances achieved by a combined tracking of yaw rate and side-
Federico Alfatti   +7 more
doaj   +1 more source

Comparison of Triply Periodic Minimal Surface Energy Absorbers Under Uniaxial Compressive Loading

open access: yesAdvanced Engineering Materials, EarlyView.
This study investigates LCD 3D printed Triply Periodic Minimal Surface (TPMS) structures as mechanical energy absorbers. By comparing various base designs and layered combinations under uniaxial compression, it identifies that a Diamond‐Gyroid sandwich structure offers superior performance.
Sergej Grednev   +2 more
wiley   +1 more source

Torque Vectoring Control for Enhancing Vehicle Safety and Energy Efficiency [PDF]

open access: yes, 2021
Torque vectoring control is one of the most interesting techniques applicable to electric vehicles with multiple motors. Essentially it is the possibility to allocate desired amounts of torque to each motor.
Basilio Lenzo, Lenzo B.
core   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

open access: yesAdvanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare   +5 more
wiley   +1 more source

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