Affiliations: [a] Instrumentation and Control Engineering Division, Netaji Subhas Institute of Technology, University of Delhi, New Delhi, India
| [b] Instrumentation and Control Engineering Department, Netaji Subhas University of Technology (formerly NSIT), New Delhi, India
Correspondence:
[*]
Corresponding author. Manish Kumar, Division of Instrumentation and Control Engineering, Netaji Subhas
Institute of Technology, University of Delhi, New Delhi-110078, India.
E-mail: [email protected].
Abstract: The primary objective of this work is to optimize the induction motor rotor flux so that maximum efficiency is attained in the facets of parameter and load variations. The conventional approaches based on loss model are sensitive to modelling accuracy and parameter variations. The problem is further aggravated due to nonlinear motor parameters in different speed regions. Therefore, this work introduces an adaptive neuro-fuzzy inference system-based rotor flux estimator for electric vehicle. The proposed estimator is an amalgamation of fuzzy inference system and artificial neural network, in which fuzzy inference system is designed using artificial neural network. The training data for neuro-fuzzy estimator is generated offline by acquiring rotor flux for different values of torque. The conventional fuzzy logic and differential calculation methods are also developed for comparative analysis. The efficacy of developed system is established by analyzing it under varying load conditions. It is revealed from the results that suggested methodology provides an improved efficiency i.e. 94.51% in comparison to 82.68% for constant flux operation.
Keywords: Loss minimization, torque estimation, adaptive neuro fuzzy inference system
(ANFIS), electrical vehicle (EV)
