Performance Evaluation of Battery and Super-Capacitor for Electric Vehicle with Hybrid Techniques
Nagesh B.K.1, B. R. LakshmiKantha2

1Nagesh B.K., Department of Electrical and Electronics Engineering, REVA University, Bangalore, India.
2Dr. B. R. Lakshmi Kantha, Electrical and Electronics Engineering, Dayananda Sagar Academy of Technology & Management, Bangalore, India.

Manuscript received on 15 August 2019 | Revised Manuscript received on 22 August 2019 | Manuscript published on 30 August 2019 | PP: 3049-3056 | Volume-8 Issue-10, August 2019 | Retrieval Number: J94920881019/19©BEIESP | DOI: 10.35940/ijitee.J94921.0881019
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Abstract: In recent trends, Plug-in Hybrid Electric Vehicles (PHEVs) have an excessive opportunity due to its charging facilities and charge storage system. Through appropriate design and development, Electric Vehicles (EVs) not only eliminate the pollution but also make the system more efficient over traditional vehicles. However, still it is in the progress of the investigation and has several unanswered issues. The performance of PHEV depends upon proper utilization of electric power which is solely affected by the battery State-Of-Charge (SOC). SOC determination becomes a vital problem in whole area where it comprises a battery storage; because it has several drawbacks such as weak power density, longevity, etc. one probable and favourable resolution for this issue is multi-source EV. Both the batteries and Ultra-Capacitors (UC) can reduce the aforementioned disadvantages in existing systems. This proposed work has more efficiency because of the combined design model of both battery and super-capacitor. Hence, in this work, the Particle Swarm Optimization (PSO) technique with Fuzzy Logic Controller (FLC) is implemented for optimal sharing of power between the battery and the super-capacitor.
Index Terms: Plug-in Hybrid Electric Vehicles (PHEVs), State-Of-Charge (SOC), Energy Management System (EMS), Particle Swarm Optimization (PSO), Fuzzy Logic Controller (FLC).

Scope of the Article: Performance Evaluation of Networks