Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
In electric vehicle technology, battery energy conservation is paramount due to the dependency of all system operations on the available battery. The proportional, integral and derivative (PID) controller parameters in the electric power assisted steering system for electric vehicle needs to be...
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| Main Authors: | , , , |
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| 格式: | Article |
| 語言: | English English English |
| 出版: |
IEEE
2017
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| 主題: | |
| 在線閱讀: | http://irep.iium.edu.my/63140/1/63140_Swarm-Intelligence%20Tuned%20Current%20Reduction%20for%20Power-Assisted.pdf http://irep.iium.edu.my/63140/2/63140_Swarm-Intelligence%20Tuned%20Current%20Reduction%20for%20Power-Assisted_SCOPUS.pdf http://irep.iium.edu.my/63140/13/63140_Swarm-intelligence%20tuned%20current%20reduction_WOS.pdf http://irep.iium.edu.my/63140/ http://ieeexplore.ieee.org/document/8219702/ |
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| 機構: | Universiti Islam Antarabangsa Malaysia |
| 語言: | English English English |
| 總結: | In electric vehicle technology, battery energy
conservation is paramount due to the dependency of all
system operations on the available battery. The
proportional, integral and derivative (PID) controller
parameters in the electric power assisted steering system
for electric vehicle needs to be tuned with the optimal
performance setting so that less current is needed for its
operation. This proposed two methods under the umbrella
of swarm intelligence technique namely Particle Swarm
Optimization (PSO) and Ant Colony Optimization (ACO) in
order to reduce current consumption and to improve
controller performance. The investigation involves an
analysis on the convergence behavior of both techniques
in search for accurate controller parameters. A
comprehensive assessment on the assist current supplied
to the assist motor of the system is also presented.
Investigation reveals that the proposed controllers, PIDParticle
Swarm Optimization and PID-Ant Colony
Optimization are able to reduce the assist current supplied
to the assist motor as compared to the conventional PID
controller. This study also demonstrate the feasibility of
applying both swarm intelligence tuning method in terms of
reduced time taken to tune the PID controller as compared
to the conventional tuning method. |
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