The document discusses a student project that aims to improve the driving range of electric vehicles through enhanced regenerative braking of brushless DC motors. The project will use fuzzy logic control to distribute braking force more efficiently. A literature review was conducted on regenerative braking systems and brushless motors. The expected outcomes are to test the system through MATLAB/Simulink simulations showing improved battery state of charge and driving distance through regenerative braking while maintaining braking quality, and then apply the system to hardware. The goal is to develop a more efficient electric vehicle motor driver controller combining various strategies.

1. Mentor By,
Ms.N.SUBHALAKSHMI
(Assistant Professor/EEE)
SRI KRISHNA COLLEGE OF
ENGINEERING AND TECHNOLOGY
(An Autonomous Institution)
Affiliated to Anna University, Chennai
Accredited by NBA-AICTE | An ISO 9001-2008 Institution
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TEAM MEMBERS
BALAMURUGAN A 20EUEE012
BALASUNDAR V 20EUEE014
DIVYA DHANYA K 20EUEE022
KAVIYA M 20EUEE039
ZEROTH REVIEW
REGENERATIVE BRAKING IN BRUSHLESS DC
MOTOR DRIVE USING FUZZY INFERENCE
SYSTEM

2. INTRODUCTION
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o Fossil fuels are used to meet the energy demand in transportation(for Traditional IC engine). But
fossil fuels are harmful to the environment due to greenhouse gas emissions. They are also
exhaustible.
o So In recent years, electric vehicles (EVs) have received much attention as an alternative to
traditional internal combustion engine (ICE) vehicles.
o The inadequacy in the batteries and the lack of charging stations require these vehicles to
be used within certain distances.
o One of the ways to increase the distance is the regenerative braking of brushless direct current
(BLDC) motors, which makes it re-usable when the vehicle is braking.
o Here We are going to enhance the Regenerative braking using brushless DC Motor in EVs, it is the
process of feeding energy from the drive motor back into the battery during the braking process,
when the vehicle's inertia forces the motor into generator mode.

3. OBJECTIVES
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• Regenerative braking can improve energy usage efficiency and can prolong the
driving distance of electric vehicles (EVs).
• The objective of this project is to design a concept, which will distribute the
braking force. In this project different techniques are used, such as equal
distribution braking force by fuzzy logic control.
• The Project presents a controller for this EV motor driver with increased
efficiency by combining various strategies.

4. PROBLEM STATEMENT
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Suggest a redefined solution to increase the driving range of Electric
vehicles due to the inadequacy in the batteries and the lack of charging
stations.

5. LITERATURE REVIEW
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MINIPROJECT II
No. AUTHOR & YEAR TITLE REMARKS
1
ARUNKUMAR
UDAYAKUMAR
KAVYAGANESAN
(2022)
REGENERATIVE
BRAKING SYSTEM OF
EV DRIVEN BY BLDC
MOTOR
Provides the Knowledge
about
Regenerative Braking.
2
DR DUANE
HANSELMAN
(2022)
BRUSH LESS MOTOR
Gives the basic
knowledge about motor
design, performance, and
electrical control.
3
CHANDAR
MOHAN(2021)
AN INTRODUCTION TO
FUZZY SET THEORY
AND FUZZY LOGIC
Gives the basic idea
about FUZZY SYSTEM.

6. NOVELTY OF THE WORK
 Regenerative braking is an established technique that can improve the driving
range of vehicles with full-electric or hybrid /hybridized powertrain, thus
promoting their large-scale adoption.
 The performance of the system is first tested as a simulation and then applied to
hardware.
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7. EXPECTED OUTCOME
o This project presents the simulation results by analysing the battery state of
charge, braking force, and dc bus current under the environment of MATLAB and
Simulink.
o The simulation results show that the fuzzy logic can realize the regenerative
braking and can prolong the driving distance of EVs under the condition of
ensuring braking quality.
o The performance of the system is first tested as a simulation and then applied to
hardware.
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8. REFERENCES
1. R. Palanisamy ,Rohit Sahasrabuddhe, Mathur Kartik Hiteshkumar, Jay Anil PuranikA new energy
regeneration system for a BLDC motor driven electric vehicle International Journal of Electrical and
Computer Engineering (IJECE) ,2021.
2. Akhila M. and Ratnan P., “Analysis of Regenerative Braking In Brushless DC Motor Drive Using Adaptive
Neuro Based Fuzzy Inference System,” International Journal of Science and Research (IJSR), vol. 02, no.
09, pp. 2019-2021, 2015.
3. A. Joseph Godfrey and V. Sankaranarayanan, “A new electric braking system with energy regeneration for a
BLDC motor driven electric vehicle,” an International Journal Engineering Science and Technology, vol. 21,
no. 4, pp. 704-713, 2018.
4. F. Naseri, E. Farjah, and T. Ghanbari, “An Efficient Regenerative Braking System Based on
Battery/Supercapacitor for Electric, Hybrid and Plug-In Hybrid Electric Vehicles with BLDC Motor,” IEEE
Transactions on Vehicular Technology, vol. 66, no. 5, pp. 3724-3738, 2017.Akhila M. and Ratnan P.,
“Analysis of Regenerative Braking In Brushless DC Motor Drive Using Adaptive Neuro Based Fuzzy
Inference System,” International Journal of Science and Research (IJSR), vol. 02, no. 09, pp. 2019-2021,
2015.
5. Xiaohong Nian, Fei Peng and Hang Zhang, "Regenerative Braking System of Electric Vehicle Driven by
Brushless DC Motor", IEEE Transactions On Industrial Electronics, vol. 61, no. 10, OCTOBER 2014.
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9. Thank You
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