Effect of Inner and Outer Wheels Driving Force Control on Small Electric Vehicle

Author(s):  
K. Shibazaki ◽  
H. Nozaki

In this study, in order to improve steering stability during turning, we devised an inner and outer wheel driving force control system that is based on the steering angle and steering angular velocity, and verified its effectiveness via running tests. In the driving force control system based on steering angle, the inner wheel driving force is weakened in proportion to the steering angle during a turn, and the difference in driving force is applied to the inner and outer wheels by strengthening the outer wheel driving force. In the driving force control (based on steering angular velocity), the value obtained by multiplying the driving force constant and the steering angular velocity,  that differentiates the driver steering input during turning output as the driving force of the inner and outer wheels. By controlling the driving force of the inner and outer wheels, it reduces the maximum steering angle by 40 deg and it became possible to improve the cornering marginal performance and improve the steering stability at the J-turn. In the pylon slalom it reduces the maximum steering angle by 45 deg and it became possible to improve the responsiveness of the vehicle. Control by steering angle is effective during steady turning, while control by steering angular velocity is effective during sharp turning. The inner and outer wheel driving force control are expected to further improve steering stability.

2021 ◽  
Vol 21 (2) ◽  
pp. 1-22
Author(s):  
Chen Zhang ◽  
Zhuo Tang ◽  
Kenli Li ◽  
Jianzhong Yang ◽  
Li Yang

Installing a six-dimensional force/torque sensor on an industrial arm for force feedback is a common robotic force control strategy. However, because of the high price of force/torque sensors and the closedness of an industrial robot control system, this method is not convenient for industrial mass production applications. Various types of data generated by industrial robots during the polishing process can be saved, transmitted, and applied, benefiting from the growth of the industrial internet of things (IIoT). Therefore, we propose a constant force control system that combines an industrial robot control system and industrial robot offline programming software for a polishing robot based on IIoT time series data. The system mainly consists of four parts, which can achieve constant force polishing of industrial robots in mass production. (1) Data collection module. Install a six-dimensional force/torque sensor at a manipulator and collect the robot data (current series data, etc.) and sensor data (force/torque series data). (2) Data analysis module. Establish a relationship model based on variant long short-term memory which we propose between current time series data of the polishing manipulator and data of the force sensor. (3) Data prediction module. A large number of sensorless polishing robots of the same type can utilize that model to predict force time series. (4) Trajectory optimization module. The polishing trajectories can be adjusted according to the prediction sequences. The experiments verified that the relational model we proposed has an accurate prediction, small error, and a manipulator taking advantage of this method has a better polishing effect.


2015 ◽  
Author(s):  
Shengdong Feng ◽  
Xiaojun Liu ◽  
Liangzhou Chen ◽  
Liping Zhou ◽  
Wenlong Lu

1998 ◽  
Vol 16 (8) ◽  
pp. 1108-1114 ◽  
Author(s):  
Masamichi Sakaguchi ◽  
Junji Furusho ◽  
Guoguang Zhang ◽  
Zhidan Wei

2018 ◽  
Vol 205 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Daiki Yonemoto ◽  
Daisuke Yashiro ◽  
Kazuhiro Yubai ◽  
Satoshi Komada

1993 ◽  
Vol 94 (6) ◽  
pp. 3533-3533
Author(s):  
Masatsugu Yokote ◽  
Fukashi Sugasawa ◽  
Tomohiro Yamamura

Robotica ◽  
1989 ◽  
Vol 7 (4) ◽  
pp. 303-308 ◽  
Author(s):  
G. M. Bone ◽  
M. A. Elbestawi

SUMMARYAn active force control system for robotic deburring based on an active end effector is developed. The system utilizes a PUMA-560 six axis robot. The robot's structural dynamics, positioning errors, and the deburring cutting process are examined in detail. Based on ARMAX plant models identified using the least squares method, a discrete PID controller is designed and tested in real-time. The control system is shown to maintain the force within l N of the reference, and reduce chamfer depth errors to 0.12 mm from the 1 mm possible without closed-loop control.


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