Abstract
This manuscript presents an optimal control system for energy management of the hybrid energy storage system (HESS) as battery and super capacitor (SC) on electric vehicles (EVs). The proposed system is parallel execution of levy flight with Tunicate swarm optimization. The proposed method is improved by levy flight distribution; hence, it is named Improved Tunicate swarm optimization (ITSA). Here, the HESS method calculates the super capacitor reference voltage in terms of load dynamics and improves the power. At first, compute the super capacitor reference voltage assuming real-time load dynamics. Furthermore, diminish the range of battery power magnitude and power loss concurrently. In the proposed system, the Improved Tunicate swarm optimization is merged for generating the probable HESS control signal data set. Furthermore, the proposed method gains the super capacitor voltage, amount of battery current, variation of battery current. Through the proposed method, the hybrid energy storage system parameters are enhanced, and the proposed system gives a reliable solution. The proposed method is performed on the MATLAB/Simulink work platform. The quality of a hybrid energy storage system is compared with that of other methods.
DISCLOSURE STATEMENT
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
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R. Kannan
R Kannan received a BE degree in EEE from Coimbatore Institute of Technology, Coimbatore, affiliated to Bharathiar University, Coimbatore, Tamilnadu, in 2001. He received an ME degree in control systems from PSG College of Technology, Coimbatore, affiliated to Anna University, Chennai, Tamilnadu, in 2004. He received a PhD degree in control systems from the same college in 2016. He is currently working as professor in the electrical and electronics engineering Department at Nehru Institute of Engineering and Technology, Coimbatore, Tamilnadu. His research interests include soft computing applications in electric drives and power system engineering.
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Paulthurai Rajesh
Paulthurai Rajesh received his Bachelor of Engineering and Master of Engineering in electrical and electronics engineering from Anna University, Chennai, India. He has got more than seven years of IT experience. His current research interests include artificial intelligence, power system, smart grid technologies and soft computing. Email: [email protected]
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Francis H. Shajin
Francis H Shajin received his Bachelor of Engineering and Master of Engineering in electronics and communication engineering from Anna University, Chennai, India. He has got more than 7 years of IT experience. His current research interests include very-large-scale integration, soft computing, image processing, machine learning and networking. Email: [email protected]