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ANN Based Improved Regenerative Braking System on PV/Battery Powered Electric Vehicles with Single Stage Interaction Converter
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i1153.0789s219
Subject(s) - automotive engineering , engineering , battery (electricity) , regenerative brake , photovoltaic system , brake , voltage , electric vehicle , inverter , torque , state of charge , electrical engineering , power (physics) , computer science , physics , quantum mechanics , thermodynamics
Hybrid features batteriesand photovoltaic (PV) module located on the roof of electric Vehicles (EV) can be effectively used by a single stage interaction converter (SSIC). SSIC is introduced for directing the energy flow amid the PV panel, battery and BLDC machine.In this paper a novel braking system is used for charing electrical vehicles using solar battery system (PV) integrated with BLDC motor. It is called as RBS (Regenerative Braking System). During the RB process, generator function is provided by BLDC motor. In order to boost the BLDC-Back-EMF, a suitable switching algorithm is used. By boosting the inverter and SSIC converter the DC-Link voltage reference is reduced to charge the battery. It increases the efficiency of the RB system. In this paper Aritifical Neural Network is used to provide a smooth and reliable brake with distributed force. This proposed BLDC-Back-EMF is experimented in MATLAB Simulink software and the results are verified. Speed, Breaking-Force, torque and front-RB force, rearmeachnical-RB force and other voltage, power are verified.

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