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International Journal of Automotive Technology > Volume 24(4); 2023 > Article
International Journal of Automotive Technology 2023;24(4): 1213-1221.
doi: https://doi.org/10.1007/s12239-023-0099-1
ANF-RBC CONTROLLER TO REGULATE POWER FLOW OF ELECTRIC PROPULSION IN ELECTRIC VEHICLES
Shaik Ruksana Begam 1,2, B. Loveswara Rao 1, D. Shobha Rani 2
1EEE Department, Koneru Lakshmaiah Educational Foundation
2EEE Department, Institute of Aeronautical Engineering
PDF Links Corresponding Author.  Shaik Ruksana Begam  , Email. ruksanabegam@iare.ac.in
ABSTRACT
In this paper design and simulation of a rule-based controller explained with performance analysis by using an adaptive-neuro-fuzzy and hybrid electric energy storage system to regulate power flow of electric propulsion in EVs named as (ANF-RBC) controller. In this proposed controller a hybrid electric energy storage system (HEESS) generated reference current and proposed controller for decreasing non-linear similarity generated by the usage of HEESS. Performance analysis of proposed controller carried out under three different load conditions and comparative analysis performed with existing one linear and three non-linear controllers. For performance trac under various loaded conditions done with greater than or equal to 90 % of battery current. By observing performance results of proposed controller, reducing non-linearity generated by HEESS and smooth tracking done well than that of traditional linear and non-linear controllers used in EVs. In performance analysis by using obtained results, we can infer proposed controller 17 %, 12 %, 10 % higher than existing RFOSM control, when compared with ASMC controller the proposed controller 25 %, 17 %, 13 % greater, proposed controller performance is 29 %, 21 %, 15 % greater than that of SMC controller and in case of comparing with existing PIDC controller with that of proposed controller performance is 32 %, 26 %, 19 % greater under heavily loaded, mediumly loaded and under lightly loaded condition respectively for all linear and non-linear traditional controllers.
Key Words: (ANF-RBC) controller, Takagi sugano fuzzy based rules, HEESS, Performance analysis, Different load conditions
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