Publication:
Intelligent Temperature Controller for Energy Storage System in Electric Vehicle Applications

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dc.contributor.authorMannan M.en_US
dc.contributor.authorAl-Shetwi A.Q.en_US
dc.contributor.authorFitriah Nor S.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorJern K.P.en_US
dc.contributor.authorRahman S.A.en_US
dc.contributor.authorMuttaqi K.M.en_US
dc.contributor.authorid57224923024en_US
dc.contributor.authorid57004922700en_US
dc.contributor.authorid57456843100en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid57220589801en_US
dc.contributor.authorid36609854400en_US
dc.contributor.authorid55582332500en_US
dc.date.accessioned2023-05-29T09:09:49Z
dc.date.available2023-05-29T09:09:49Z
dc.date.issued2021
dc.descriptionBattery management systems; Charging (batteries); Computer circuits; Controllers; Electric control equipment; Electric vehicles; Fuzzy logic; Global warming; Lithium-ion batteries; MATLAB; Proportional control systems; Storage management; Thermal management (electronics); Three term control systems; Battery energy storage systems; Carbon emissions; Fuzzy logic controllers; Performance; Proportional integral and derivatives; Proportional integral controllers; Proportional-derivative controllers; Storage systems; Temperature controllers; Vehicle applications; Temperature controlen_US
dc.description.abstractToday, studies on battery tech in electric vehicle (EV) applications is growing rapidly in order to tackle the concerns of global warming and carbon emissions. The efficiency of EVs is dependent on precise measurement of essential factors in addition to the appropriate battery storage system performance based on its thermal management. Therefore, this paper discusses about the performance of lithium-ion battery with different types of controllers for EV which are proportional, integral and derivative (PID) controller and Fuzzy Logic controller (FLC). Based on the simulation that has been carried out using MATLAB/Simulink, the implementation of FLC helps in increasing the output response of battery compared to not using the controller or by using the PID controller. The results of FLC shown better performance than PID in which percentage overshoot of FLC is (0.501%) lesser than PID controller (8.152%). The comparison of the controllers is carried out in order to deploy the best controller of the battery thermal management system for the EV. Obtained results also show that the increased temperature effect the battery state of charge (SOC) which might deteriorate the EV performance. � 2021 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICCCA52192.2021.9666422
dc.identifier.epage862
dc.identifier.scopus2-s2.0-85124797114
dc.identifier.spage854
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85124797114&doi=10.1109%2fICCCA52192.2021.9666422&partnerID=40&md5=48e01ca623ac9ae8d9220f2c5850efab
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26387
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2021 IEEE 6th International Conference on Computing, Communication and Automation, ICCCA 2021
dc.titleIntelligent Temperature Controller for Energy Storage System in Electric Vehicle Applicationsen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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