scholarly journals Dynamic Optimization Self-adaptive AI Controller for a Four-wheel Independent Drive Electric Rover

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Hasitha Ruwan Jayetileke ◽  
W.R. de Mel ◽  
H.U.W. Ratnayake

In this paper, a dynamic optimization self-adaptive controller for a four-wheel independent drive electric rover has been investigated to enhance the dynamic stability. The proposed self-adaptive AI controller is based on dynamic Fuzzy Logic (FL) control mechanism. The dynamic self-adaptive properties have been integrated into the proposed FL controller through a dynamically tuned Particle Swarm Optimization (PSO) mechanism. Nevertheless, the dynamic FL controller and the dynamic PSO mechanism has been synchronized together for every sampling instance k to obtain the optimum performance of the electric rover. In this electric rover, all the four wheels have a fixed orientation and each wheel powered by a 250-Watt Brushless Direct Current (BLDC) motor through separate gear ratio mechanisms to obtain the desired torque and angular velocity. Therefore, the steering mechanism was achieved in this rover through the proposed AI controller, which was based on the differential speed mechanism. However, this paper presents the control methodology and obtained test results related to straight road tests under different slippery road conditions. The rover test results show that on different slippery road conditions the proposed PSO based FL controller has maintained the wheel slip ratio of all the four wheels which was less than 0.35 approximately. Here, the translational speed has been limited to 40 km/hr approximately within its recorded top speed of 90 km/hr while maintaining the desired fix orientation.

2014 ◽  
Vol 971-973 ◽  
pp. 454-457
Author(s):  
Gang He ◽  
Li Qiang Jin

Based on the independent design front wheel drive vehicle traction control system (TCS), we finished the two kinds of working condition winter low adhesion real vehicle road test, including homogenous pavement and separate pavement straight accelerate, respectively completed the contrastive experiment with TCS and without TCS. Test results show that based on driver (AMR) and brake (BMR) joint control ASR system worked reliably, controlled effectively, being able to control excessive driving wheel slip in time, effectively improved the driving ability and handling stability of vehicle.


Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2501 ◽  
Author(s):  
Jinhong Sun ◽  
Xiangdang Xue ◽  
Ka Wai Eric Cheng

With the development of in-wheel technology (IWT), the design of the electric vehicles (EV) is getting much improved. The anti-lock braking system (ABS), which is a safety benchmark for automotive braking, is particularly important. Installing the braking motor at each fixed position of the wheel improves the intelligent control of each wheel. The nonlinear ABS with robustness performance is highly needed during the vehicle’s braking. The anti-lock braking controller (CAB) designed in this paper considered the well-known adhesion force, the resistance force from air and the wheel rolling friction force, which bring the vehicle model closer to the real situation. A sliding mode wheel slip ratio controller (SMWSC) is proposed to yield anti-lock control of wheels with an adaptive sliding surface. The vehicle dynamics model is established and simulated with consideration of different initial braking velocities, different vehicle masses and different road conditions. By comparing the braking effects with various CAB parameters, including stop distance, braking torque and wheel slip ratio, the SMWSC proposed in this paper has superior fast convergence and stability characteristics. Moreover, this SMWSC also has an added road-detection module, which makes the proposed braking controller more intelligent. In addition, the important brain of this proposed ABS controller is the control algorithm, which can be used in all vehicles’ ABS controller design.


2013 ◽  
Vol 347-350 ◽  
pp. 753-757
Author(s):  
Li Zhou ◽  
Lu Xiong ◽  
Zhuo Ping Yu

This paper proposes a wheel slip control strategy for 4WD Electrical Vehicle with In-wheel Motors. In the first part of this paper, a brief introduction of sliding mode control for acceleration slip regulation is given. Consider that its control effect varies with road conditions, another algorithm which can automatically adapt to different roads is designed. This method takes advantage of the peculiarity of the longitudinal static tire force curve and regulates wheel slip ratio to the detected optimal value, aiming to maximize the traction force while preserving sufficient lateral tire force. Simulation results show that the slip rate can be regulated to a value around the optimal slip ratio, and the driving torque is very close to the maximum transmissible torque. The control strategy achieves stronger stability, shorter driving distance and hence better control performance.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guodong Yin ◽  
Shanbao Wang ◽  
Xianjian Jin

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.


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