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: A.Hanifah, Rabiatuladawiah, Toha, Siti Fauziah, Ahmad, Salmiah, Hassan, Mohd Khair
Format: Article
Language:English
English
English
Published: IEEE 2017
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Online Access: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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Institution: Universiti Islam Antarabangsa Malaysia
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spelling my.iium.irep.631402019-01-24T06:12:19Z http://irep.iium.edu.my/63140/ Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle A.Hanifah, Rabiatuladawiah Toha, Siti Fauziah Ahmad, Salmiah Hassan, Mohd Khair T Technology (General) 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. IEEE 2017 Article PeerReviewed application/pdf en http://irep.iium.edu.my/63140/1/63140_Swarm-Intelligence%20Tuned%20Current%20Reduction%20for%20Power-Assisted.pdf application/pdf en http://irep.iium.edu.my/63140/2/63140_Swarm-Intelligence%20Tuned%20Current%20Reduction%20for%20Power-Assisted_SCOPUS.pdf application/pdf en http://irep.iium.edu.my/63140/13/63140_Swarm-intelligence%20tuned%20current%20reduction_WOS.pdf A.Hanifah, Rabiatuladawiah and Toha, Siti Fauziah and Ahmad, Salmiah and Hassan, Mohd Khair (2017) Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle. IEEE Transactions on Industrial Electronics, PP (99). pp. 1-9. ISSN 0278-0046 http://ieeexplore.ieee.org/document/8219702/ 10.1109/TIE.2017.2784344
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
English
topic T Technology (General)
spellingShingle T Technology (General)
A.Hanifah, Rabiatuladawiah
Toha, Siti Fauziah
Ahmad, Salmiah
Hassan, Mohd Khair
Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
description 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.
format Article
author A.Hanifah, Rabiatuladawiah
Toha, Siti Fauziah
Ahmad, Salmiah
Hassan, Mohd Khair
author_facet A.Hanifah, Rabiatuladawiah
Toha, Siti Fauziah
Ahmad, Salmiah
Hassan, Mohd Khair
author_sort A.Hanifah, Rabiatuladawiah
title Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
title_short Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
title_full Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
title_fullStr Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
title_full_unstemmed Swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
title_sort swarm-intelligence tuned current reduction for power assisted steering control in electric vehicle
publisher IEEE
publishDate 2017
url 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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