Independent-wheel-drive electric vehicle handling and stability assessment via composite nonlinear feedback controller

2015 ◽  
Author(s):  
M. H. M. Ariff ◽  
H. Zamzuri ◽  
N. R. N. Idris ◽  
S. A. Mazlan ◽  
M. A. M. Nordin
Keyword(s):  
Electric Vehicle ◽  
Feedback Controller ◽  
Stability Assessment ◽  
Nonlinear Feedback ◽  
Composite Nonlinear Feedback ◽  
Vehicle Handling ◽  
Wheel Drive

Composite Nonlinear Feedback Control with Multi-objective Particle Swarm Optimization for Active Front Steering System

2015 ◽  
Vol 72 (2) ◽  
Author(s):  
Liyana Ramli ◽  
Yahaya Md. Sam ◽  
Zaharuddin Mohamed ◽  
M. Khairi Aripin ◽  
M. Fahezal Ismail
Keyword(s):  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Nonlinear Feedback ◽  
Nonlinear Gain ◽  
Composite Nonlinear Feedback ◽  
Swarm Optimization ◽  
Vehicle Handling ◽  
Multi Objective ◽  
Yaw Rate ◽  
Active Front Steering

The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller.  

Stochastic synchronization of complex networks via a novel adaptive composite nonlinear feedback controller

2014 ◽  
Vol 80 (1-2) ◽  
pp. 363-374 ◽  
Author(s):  
Weiping Wang ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Jürgen Kurths ◽  
Jinghua Xiao ◽  
...  
Keyword(s):  
Complex Networks ◽  
Feedback Controller ◽  
Nonlinear Feedback ◽  
Composite Nonlinear Feedback ◽  
Stochastic Synchronization ◽  
Adaptive Composite

Optimal Composite Nonlinear Feedback Controller for an Active Front Steering System

2014 ◽  
Vol 554 ◽  
pp. 526-530 ◽  
Author(s):  
Liyana Ramli ◽  
Yahya M. Sam ◽  
Zaharuddin Mohamed ◽  
Muhamad Khairi Aripin ◽  
Muhamad Fahezal Ismail
Keyword(s):  
Parameter Optimization ◽  
Optimization Problems ◽  
Steering System ◽  
Stability Control ◽  
Feedback Controller ◽  
Nonlinear Feedback ◽  
Composite Nonlinear Feedback ◽  
Fast Tracking ◽  
Active Front Steering ◽  
Yaw Stability

Yaw stability control is the most popular topics in the automotive field. Several studies have been done in searching the effective method in controlling yaw moment. Hence, an integration of the active front steering system (AFS) with Composite Nonlinear Feedback controller is presented in this paper. Recently, this controller has been used by a lot of researchers in controlling their system performance due to its main advantage that can be seen in transient response which demonstrate super fast tracking. An optimal CNF feedback control problem is formulated as a parameter optimization problem with performance index and restrictions on stability. To handle such restrictions and constraint, the particle swarm optimization algorithm is applied to solve parameter optimization problems.

Torque Vectoring Control of a Four Independent Wheel Drive Electric Vehicle

2013 ◽  
Author(s):  
Federico Cheli ◽  
Stefano Melzi ◽  
Edoardo Sabbioni ◽  
Michele Vignati
Keyword(s):  
Numerical Simulations ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Closed Loop ◽  
Control Strategies ◽  
Energetic Efficiency ◽  
Vehicle Handling ◽  
Wheel Drive ◽  
Torque Vectoring ◽  
Yaw Moment

In recent years the interest towards electric vehicles has increased. Among the different layout of the electric powertrain, four in-wheel motors appear to be one of the most attractive. This configuration in fact allows to re-design inner spaces of the vehicle and presents, as an embedded feature, the possibility of independently distributed braking and driving torques on the wheels in order to generate a yaw moment able to improve vehicle handling (torque vectoring). The present paper presents and compares two different torque vectoring control strategies for an electric vehicle with four in-wheel motors. Performances of the control strategies are evaluated by means of numerical simulations of open and closed loop maneuvers, also taking into account their energetic efficiency.

Research on the Influence of Unsprung Mass on Vehicle Handling Stability

2012 ◽  
Vol 562-564 ◽  
pp. 816-820 ◽  
Author(s):  
Ming Chun Liu ◽  
Chen Ning Zhang ◽  
Zhi Fu Wang
Keyword(s):  
Electric Vehicle ◽  
Degrees Of Freedom ◽  
Dynamical Model ◽  
Steering Wheel ◽  
Simulation Experiments ◽  
Vehicle Handling ◽  
Response Characteristics ◽  
Wheel Drive ◽  
Frequency Response Characteristics ◽  
Unsprung Mass

A dynamical model of engine vehicle was built by using ADAMS/Car. Based on that, another dynamical model of four-independent-wheel-drive electric vehicle was built too. Two simulation experiments of steering wheel angle step input and steering wheel angle impulse input were done. Considering the vehicle mathematical model with two linear degrees of freedom, the transient response and frequency response characteristics were evaluated. Simulation results indicated that time-domain and frequency-domain characteristics of four-independent-wheel-drive electric vehicle were influenced because of its heavy unsprung mass, and that leaded to the deteriorative handling stability.

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