Study on Drive Cycle Tracking ability of Different Control Algorithms for an Electric Vehicle

Fundamental tracking control algorithms of a differentially steered wheeled mobile robot with two conventional driven wheels are studied through analyzing the robot’s inherent kinematics. This includes the tracking variable assignment as well as the tracking singularity and position-orientation tracking decoupling problems. Globally convergent tracking control algorithms are proposed, which can exactly track any differentiable reference path. A fundamental motion orientation equation under the condition of exact position tracking is developed, and it is shown that it is not possible to exactly track both position and orientation concurrently for this kind of mobile robot configuration if the tracking point is not on the baseline. Examples are provided illustrating the tracking ability of the developed control algorithms.

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A Research on Anti-Slip Regulation of In-Wheel Motor Driven Electric Vehicle

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.536-537.1059 ◽

2014 ◽

Vol 536-537 ◽

pp. 1059-1064 ◽

Cited By ~ 1

Author(s):

Miao Hua Huang ◽

Ya Chao Zhao

Keyword(s):

Electric Vehicle ◽

Vehicle Dynamics ◽

Control Algorithms ◽

Ratio Estimator ◽

Slip Ratio ◽

The Road ◽

Model Following Control ◽

Model Following ◽

Optimal Slip Ratio ◽

The One

In order to develop the four in-wheel motors driven Electric Vehicle (EV), this paper designed a skidding detector depending on the motor torque, established a slip-ratio estimator. Then, the Model Following Control (MFC) and Optimal Slip-ratio Control algorithms were analysed, compared and optimized. All of the algorithms were simulated using the one-wheel vehicle model. The simultion results show that the algorithms can make full use of the road adhesion characteristics and do good work on the ASR and the vehicle dynamics.

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Modified Strong Tracking Filter for the SOC Estimation of Lithium Battery in Electric Vehicle

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.236-237.1362 ◽

2012 ◽

Vol 236-237 ◽

pp. 1362-1367

Author(s):

Ze Cheng ◽

Yu Hui Zhang ◽

Yan Li Liu

Keyword(s):

Electric Vehicle ◽

Lithium Battery ◽

State Of Charge ◽

Estimation Accuracy ◽

Original Algorithm ◽

Soc Estimation ◽

Tracking Ability ◽

Strong Tracking Filter ◽

Vehicle Management ◽

Tracking Filter

In electric vehicle management system, the key technology is to estimate the SOC (state of charge) of battery in dynamic process. This paper builds the state space equation of lithium battery based on improved Randle’s model, realizes the tracking estimation of SOC using modified STF(strong tracking filter) algorithm. The simulation result proves that compared with the original algorithm, modified algorithm can greatly improve the system’s tracking ability as well as the estimation accuracy of SOC.

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