| Autor: |
Arof, Saharul, Arof, H., A. K., Muhd Khairulzaman, P. A., Mawby, J. A., Jalil |
| Předmět: |
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| Zdroj: |
International Journal of Simulation: Systems, Science & Technology; 2015, Vol. 16 Issue 4, p3.1-3.10, 10p |
| Abstrakt: |
DC drive system for traction is predominantly powered by separately excited as compared to series dc motor and both drive systems are controlled by four quadrants dc chopper. However, the operation modes of the conventional HBridge four quadrants drive dc chopper for series motor are limited to driving and regenerative braking (only with the presence of residual magnetism), with no capability of reverse operation, field weakening, resistive braking and parallel mode. As there are six chopper operations required for considerations, it is thus necessary to have controller that is able to choose the appropriate operation with respect to the chopper input signals. Hence, a new Four Quadrants dc drive chopper for series motor in EV's application, optimized by Artificial Intelligence is developed. This paper further describes the application of Artificial Intelligence with Self Tuning Fuzzy Logic (STFL), Neural Network (NN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) controllers for controlling chopper operation of the proposed chopper. Both the controller and EV system were developed using MATLAB/Simulink. The AI algorithms were tested and a comparative analysis has been performed on the three methods of control. Simulation results showed that all the controllers are able to select the expected operation for the proposed chopper with respect to the test signals given. It is also observed that the appropriate mode of operation guaranteed better EV performance in terms of battery power consumption, vehicle speed and distance traversed. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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