Electric Vehicle Braking System Design

This assignment delves into the design of a braking system for a front-wheel drive electric vehicle. The system incorporates BLDC motors with individual wheel braking forces controlled by MOSFETs. A detailed analysis is presented on how the system utilizes feedback from various sensors (speed, SOC, FBF, Pedal) to calculate and distribute braking force between the front and rear wheels. A PID controller and a duty cycle limit are implemented for precise motor control. The overall objective is to design an efficient and safe braking system that ensures optimal vehicle performance and stability.

SYNOPSIS OF THESIS
PERFORMANCE ANALYSIS OF A NOVEL
SINGLE STAGE INTERCONNECTED
CONVERTER AND POWER FLOW CONTROL
METHOD FOR PV AND BATTERY POWERED
EHV SYSTEMS
A SYNOPSIS
Submitted by
JAMBULINGAM. S.
Registration Number: 0114909204
in partial fulfillment of the requirements for the degree of
DOCTOR OF PHILOSOPHY
Under the Supervision of
Dr. D. M. MARY SYNTHIA REGIS PRABHA
DEPARTMENT OF ELECTRICAL & ELECTRONICS
ENGINEERING
NOORUL ISLAM CENTRE FOR HIGHER EDUCATION
(Deemed-to-be-University under section 3 of the U.G.C. Act 1956)
Accredited by NAAC with ‘A’ Grade
KUMARACOIL, KANYAKUMARI DISTRICT,
TAMILNADU, INDIA - 629 180
OCTOBER - 2020

PERFORMANCE ANALYSIS OF A NOVEL SINGLE STAGE
INTERCONNECTED CONVERTER AND POWER FLOW CONTROL
METHOD FOR PV AND BATTERY POWERED EHV SYSTEMS
1. INTRODUCTION
The rapid change in global energy demands and the environmental
problems caused by fossil fuels have resulted in the need of solar energy which
becomes a potential solution and is one amongst the most popular renewable energy
sources. However, Photovoltaic (PV) energy has some boundaries such as high cost
of capitation and low conversion efficiency, but it has grasped the interest of the
researchers Wang et al., (2013). The PV system comprises a friendly environment
and it is an alternative method for production of energy by utilising the energy from
the sun. Without any noise and emissions it can operate, even if the load is increased.
The output from a solar PV cell is a DC, in which the magnitude of such
output current is always calculated by the PV cell area and the amount of solar
irradiation exposed. The magnitude of output voltage from the individual solar cell is
normally in the range of 0.5V.These cells are generally connected in a series manner
in order to comprise modules with a realistic level of voltage. When the magnitude of
PV system and load resistance is equal, then maximum power is delivered at the
operating point. This can be achieved by an interfacing DC-DC power converter
utilizing some assured techniques of MPPT.
Among the various types of arrangements of photovoltaic technology, a
stand-alone PV-battery-powered backup system can be utilised in different types of
applications Chen et al., (2013). For maintaining the system operation, the energy
stored can be helpful during the shading to the PV panel. In such cases, to keep the
power demand an efficient converter is required within the limit of the maximum
availability and to prevent any failure, and shut down or damage. To diminish these
problems, a novel single stage Interconnected converter named Modified Boost
Bidirectional Buck-Boost Converter (MB4C) is proposed.
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Electric Vehicles (EV’s) are becoming an interesting topic for research
and development, which gives a reasonable solution for decreasing the greenhouse
gas emissions. Brushless DC (BLDC) motors are one among the guaranteed motors
for EV applications. Regenerative Braking (RGB) enhances energy usage
effectiveness as well as extends the driving distance of Electric vehicles. In this
research, by a single foot pedal, coordination of reformative as well as mechanical
braking is attained, and the distribution of braking force is attained using Fuzzy
Logic Controller (FLC). With the intention of prolonging the EV’s driving miles, the
usage of PV panels over the EV reduce the dependence on vehicle batteries. In this
research, a Single Stage Interaction Converter (SSIC) is introduced for directing the
energy flow amid the PV panel, battery and BLDC machine.
The performance assessment is done in the environment of MATLAB
Simulink, in which the speed, stator current and voltage, and state of battery are
evaluated. When compared to other approaches, the novel proposed approach
provides improved performance in terms of robustness, realization, and efficiency.
The major beneficiary features of EV’s include greater efficiency, less emission,
quiet operation, and so on. The EV’s turn out to be the most hopeful alternate to the
traditional fuel vehicles by means of the growth of battery and motor technology J.
Cao et al., (2011). In numerous industrial applications, Chemical batteries are
utilized as the major Energy Storage System (ESS). In the electric bike/car industry,
they are presently the leading technology. On the other hand, because of the
inadequate battery capacities, EV’s still experience the foremost issue of shorter
driving range when matched up with the fuel vehicles With the intention of
prolonging the EV’s driving miles, the usage of PV panels on the vehicle reduces the
dependence on vehicle batteries.
1.1. Objectives of the Research
The main objectives of the proposed research work are as follows,
 By designing with minimum number of power semiconductor devices hence
reduces the current conduction losses in the proposed converter without
affecting the performance of the system
 Design and evaluate the dynamic performance of the proposed converter by
using Voltage Distribution method.
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 Manage and control a strong power flow between PV and battery for electric
hybrid vehicle with proposed technology.
 Increase the overall efficiency of the proposed converter by using a single
stage power conversion technique and compared with conventional converter
in terms of average losses and conversion efficiency.
 Increase the driving efficiency and performance of the Electric Vehicle by
controlling the braking torque with a Fuzzy Logic based new regenerative
braking system and ANN based improved regenerative braking system.
1.2. RESEARCH CONTRIBUTION
This research work is mainly focused to design and analyze the performance of a
novel single stage Interconnected converter Chen et al., (2013) in a PV system. The
working principle of the proposed converter under various operating modes and
mathematical modelling are explained. The new control strategy for the proposed
system is also discussed.
The dynamic performance of the proposed converter can be evaluated by
implementing a three domain voltage distribution control method in terms of overall
component count, average losses and efficiency. Based on the solar radiation, they
are classified as Sun Domain (SD), Minimum Battery Charging Domain (MBCD)
and Maximum Battery Discharge Domain (MBDD). When the proposed converter is
operating under different domains, it has less number of conducting components
hence resulting in reduction of converter size and conduction losses thereby
improving the efficiency. It is also proved that the performance of the proposed
converter is superior when compared with other conventional converters while
operating in three distribution domains.
The strong power flow between PV port and battery port for Electric hybrid
vehicle can be controlled by using a single stage proposed interconnected converter.
The Fuzzy Logic based new regenerative braking system was implemented in order
to control the braking torque hence increase the driving efficiency and performance
of an Electric Vehicle. An Artificial Neural Network (ANN) based improved
regenerative braking system was suggested to control the braking torque hence
increase the driving efficiency and driving distance also performance of an Electric
Vehicle in terms of robustness and realization.
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2. PROBLEM SPECIFICATION
From the literature survey, the dynamic performance of the conventional converter is
found to be poor due to more number of power semiconductor devices, there by
gaining a complex system design. Due to high current conduction losses the
efficiency of the converter is reduced. The conventional converter has a non-uniform
flow of current between battery and load port when the battery is connected for
charging and the life period of the battery is reduced. Because of these drawbacks,
they are not suitable for a PV-battery powered Electric Hybrid Vehicle system. This
could be rectified by using a boost bidirectional buck with buck boost converter
(MB4C) which decreases the usage of power devices and the whole system design is
found to be more compact.
The strong power flow management between PV and battery for Electric
vehicle can be controlled by using single stage proposed converter. A Fuzzy Logic
based new regenerative braking system is proposed to control the braking torque
hence increase the driving efficiency and performance of an Electric Vehicle. An
Artificial Neural Network (ANN) based Z. Chen et al., (2014) improved regenerative
braking system to control the braking torque hence increase the driving efficiency,
distance and performance of an Electric Vehicle in terms of strength and recognition.
3. LITERATURE SURVEY
A new systematic approach of deriving a three port converter from the fuel
bridge converter is proposed by Wu et al., (2012). The proposed converter can be
applied for renewable power system applications. A single stage power conversion
method is used to achieve high efficiency and also to reduce the number of power
devices used. But due to the high conduction losses, the conversion efficiency was
decreased. The pulse width modulation techniques are utilized to reduce the DC
biasing of the transformer.
Falcones et al., (2010) presented a novel control technique for a three-port
DC-DC converter based PV system with large storage capacity. The proposed
controller has the advantage of fast transient response and cross coupling
characteristics. The three port topology is used to obtain a transient journey from the
storage. The other conventional design techniques such as SISO (Single Input Single
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Output) control design and Feed forward compensation are also presented. The
performance of the proposed control systems is verified against simulation results.
Chen, Wang et al., (2014) presented a novel micro-converter photovoltaic
system consisting of Buck-Boost converters connected in a series manner and a
central inverter. Each PV panel is able to work at its limited maximum power point.
The cascaded converter can function in buck or boost mode to comprehend the
output voltage of wide range. The power balance between the series-connected
converter and central inverter is maintained. A new updated procedure and safety
approach is also proposed to improve stabilization and to start the converters
continuously. The converter output voltage and control scheme are presented. The
simulation results are compared with experimental results and they prove the
advantages of the proposed control approach.
Balamurugan et al. (2012) presented a fuzzy logic controller to control and
tracking the maximum power for a combined PV and wind turbine system. The
hybrid integrated structure fed by PV and wind turbine sources suitable for
distributed generation is also proposed. Under all conditions, the proposed method is
capable of feeding a minimum amount of power to the power grid and working as an
uninterruptable power source. When the switches are turned on/off the efficiency of
conventional boost converter is reduced due to hard switching and produces losses.
The switching losses and voltage stress are reduced by the proposed switching
pattern.
Jiang et al., (2009) presented a comparative calculation of the existing control
methods for switch-mode converters suitable for PV applications. They are hysteresis
current control; current programmed control, average current control and nonlinear
carrier control methods under the load variations and input fluctuations. The static
and dynamic responses of the PV systems are examined and harmonic analysis is
also implemented.
Sahin et al., (2012) examined various control techniques to control the output
voltage of the DC-DC converter. The presented techniques are successfully
implemented and they are also proposed a technique with FLC. The techniques are
implemented for the buck-boost DC-DC converter useful for a PV battery-load
system. Two membership functions are used in the FLC to control the output voltage
of the converter and by using gauss membership functions the output voltage was
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very near to the reference voltage value, hence there is no overshoot and large
ripples.
XU GQ LI et al., (2011) proposed an intelligent regenerative braking strategy
for electric vehicles. Regenerative braking is an effective approach for electric
vehicles to extend their driving range. An ANN -based regenerative braking strategy
integrated with series regenerative braking is developed in this paper to advance the
level of energy-savings. From the viewpoint of securing car stability in braking
operations, the braking force distribution between the front and rear wheels so as to
accord with the ideal distribution curve are considered to prevent vehicles from
experiencing wheel lock and slip phenomena during braking.
S S Bhurse, et al., (2018) presented a new regenerative braking system which
is about extracting the kinetic energy which was wasted as heat from the wheels and
friction in conventional braking. This method is more efficient for vehicles moving at
higher speeds. The improvement was achieved by flywheel, ultra-capacitor,
advanced power electronic converter and efficient energy storage systems. The
regenerative braking improves the driving range around 16.25%. also then by using a
fuzzy RBS and the driver's braking force command, vehicle speed, battery SOC,
battery temperature are designed to determine the distribution between friction
braking force and regenerative braking force to improve the energy recuperation
efficiency.
Kiddee K et al., (2018) proposed a regenerative braking system strategy for
battery electric vehicles with a hybrid energy storage system driven by a brushless
DC motor. In the regenerative braking mode of Battery Electric Vehicle (BEV), and
the BLDC (Brushless D.C) motor works as a generator. The DC-link voltage is
boosted and regenerative braking energy is transported to a battery using a suitable
switching pattern. The energy stored in the HESS through reverse current flow can
be broken to improve acceleration and maintain the batteries from frequent deep
discharging during high power mode. In addition, the ANN based RBS control
mechanism was utilized to optimize the switching scheme of the vehicular breaking
force distribution. Different imitation and experiments were employed and carried
out to verify the performance of the proposed RBS strategy.
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4. OVERVIEW OF THE THESIS
The first chapter clearly discusses the background of DC-DC converters
and their role in PV powered backup systems in order to increase the efficiency of
the proposed converter by reducing the number of power semiconductor components
and also current conduction losses.
The second chapter clearly discusses the design and performance analysis of
the Proposed Interconnected converter. Using Voltage Distribution control method
the performance evaluation of the proposed converter was done which improves the
dynamic performance of the proposed converter. The simulation execution of the
proposed converter is also presented.
The third chapter discusses the robust power flow between PV and battery
port for Electric vehicle using single stage proposed interconnected converter. A
Fuzzy Logic based new regenerative braking system is developed in order to control
the braking torque during regenerative braking thus increasing the driving efficiency
and performance of the Electric Vehicle.
The fourth chapter presents an Artificial Neural Network based new and
improved regenerative braking system to control the braking torque for increasing
the driving efficiency and performance of an Electric Vehicle. The simulation of the
converter is also presented.
The fifth chapter concludes the thesis, with the findings from the proposed
approaches. Moreover, it also discusses the forthcoming scope of the proposed
system for further improvement.
5. RESULTS AND DISCUSSION
The research work is summarized in the following three sections.
5.1. Working Principle and Performance Analysis of Proposed MB4C
The first section explains the working principle and performance
analysis of the proposed MB4C and also voltage based three domain control scheme
for the three port converter. The circuit diagram of the proposed converter is
presented in the Figure 1. Depending on the connection between PV generation
power and load demand power, MB4C can operate under various power flow modes.
The principles of circuit operation and analysis are illustrated with the subsequent
assumptions: 1) All switches are assumed to be ideal; 2) the capacitors are massive
enough in order that the voltage ripples owing to switch are negligible and will be
8

taken as constant voltage sources. In the Sun Domain the solar power is totally
obtainable and in the Maximum Battery Charging Domain, the solar power is
moderately available. Whereas, in the third domain namely Minimum Battery
Discharging Domain due to poor level of irradiation there is no solar power obtained.
The various operating modes under normal motor and regenerative mode was also
presented. A new method of control strategy has been developed for the MB4C in
MATLAB/SIMULINK for maintaining the load demand. It has a capability to
support the unexpected load demand through battery backup. The simulation results
proved the proposed converter works efficiently and the converter output voltage is
maintained constant when the battery is in charging and discharging condition.
Figure 1. Circuit Diagram for Proposed MB4C
The chief achievements of this proposed MB4converter are as given: 1) Current in the
proposed MB4 converter is in discontinuous conduction mode for improving the life
time of the battery. 2) Due to the single-stage power conversion existing between PV
and load port or between battery and load port, the efficiency of the converter gets
highly improved. 3) Design of the converter, along with minimal number of power
components, is introduced for reducing the current conduction losses. 4) On the basis
of the three-domain voltage control method, the load voltage is regulated always with
high quality in all power flow conditions. The projected system primarily focused on
less range of power utility devices and current physical phenomenon parts throughout
device operation and also this device will manage power flow between PV, battery
and load ports.
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5.2 Fuzzy Logic based new Regenerative Braking System for EHV
This section explains a Fuzzy Logic based new regenerative braking system for
EHV in order to control the braking torque during regenerative braking hence
increasing the driving Efficiency and performance of an Electric Vehicle. Brushless
DC (BLDC) motors are one among the guaranteed motors for EV applications.
Regenerative Braking (RGB) enhances energy usage effectiveness as well as extends
the driving distance of Electric vehicles. In this research, by a single foot pedal,
coordination of reformative as well as mechanical braking is attained, and the
distribution of braking force is done using a Fuzzy Logic Controller (FLC) and in
this research, MB4C is utilized for directing the energy flow between the PV panel,
battery and BLDC machine.
The regenerative braking does not work all circumstances, e.g., when the
induced back emf's are too little or when the battery is completely charged, braking
should be affected by disseminating the vitality in a resistive load (i.e. mechanical
braking). Consequently, the mechanical brake in the EV is as yet utilized. In this
work coordination of mechanical braking and regenerative braking is accomplished
by a single foot pedal: The initial segment of the foot pedal manages the regenerative
braking, and the next part manages the mechanical brake. At the point when the
brake command is connected, the controller alters the dc-link voltage for steady
torque braking with battery. In this mode, the battery is considered as a load,
subsequently giving a braking power to EV.
The behavior of FLC mainly depends on membership functions and rule
base and these rules are selected based on the practical experience. Here the FLC is
developed with three inputs they are the FBF, speed, and State of Charge of the
battery (SOC). For the front-wheel drive EVs, the Front Braking Force (FBF) is
made out of two sections: Mechanical Braking Force (MBF) and Regenerative
Braking Force (RGBF). RGBF in EV is impacted by many components, and
numerous parameters are continually changing, so reusing technique is hard to be
communicated. In this manner, the Fuzzy Logic Control strategy for EV braking
force distribution can be effortlessly shown by the impact of various elements.
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The various waveforms related to proposed system when operating at motor and
regenerative modes are indicated in Figure 2. Which explains also the back emfs,
stator currents, Hall-effect signals and the switching pattern of MOSFET.
(b)
(a) (c)
Figure 2. The waveforms of the BEMF’s, stator currents, Hall-effect signals and
the switching pattern (a) Motor and RC mode, operational behavior of the VSC
under (b) motor mode at (240° − 300°) (c) RC mode at (0° − 60°)
Where ha, hb and hc are Hall-effect signals ( ) for identifying the rotor
position, Hall-effect sensors are generally used.
F1, F2 ……..F6 are switching pattern of VSC.
The structure of the braking control methodology for the proposed converter is
indicated in Figure 3. During braking, kinetic energy of the EV will be exchanged to
the battery. In some braking events, the battery will achieve its greatest limit and it
can't acknowledge additionally charge from the BLDC machine, which restrains the
regenerative ability. Hence, association of mechanical (frictional) braking is basic for
finishing the braking objective. Through the pedal sensor, we can get the driver's
required braking power.
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M
B4
C
M
B4
C

Figure 3. Braking control strategy for SSIC using FLC
The Table 1 indicates the fuzzy logic controller rules for inputs and outputs. The
yield variable is the proportion which is relative to the RGBF taking in the FBF. The
estimation of the FBF speaks to the braking distance and time the driver requires. We
incline toward the concourse of speed to be low, middle, and high, and the universe
of discourse is [0, 2000].
Table.1 FLC rules for the Regenerative Braking System
Speed SOC FBF mf Speed SOC FBF mf
L L L 2 H L L 5
L L M 1 H M M 5
L L H 0 H H H 4
L M L 4 H L L 10
L M M 2 H M M 9
L M H 3 H H H 8
L H L 3 H L L 5
L H M 1 H H M 3
12
BLDC
Front
Wheel
Error
RGBF
Brake Force
Distribution
Speed
SOC
FBFPedal
FLC
Force to
Current
PID Duty cycle
limit
Battery
MOSFET
Rear MBF
Front MBF
Total braking
force
Rear
Wheel

To reveal the working and convenience of the proposed framework, PV and battery
fed EV with BLDC machine has been demonstrated in the MATLAB environment.
A SSIC alongside VSC utilizing MOSFET's has been utilized for feeding control
voltage to the BLDC machine. The input and output details of the structure of this
proposed EV are recorded in Table 2. The proposed EV is approved by a 250 W
three-phase BLDC machine. A 150 W PV board and 24 V, 14 A/h battery are
utilized as information sources individually. Consider, PV gets greatest insulation
(1000 W/m^2) in both motor and braking conditions
Table 2. Input and output specifications of proposed EV
Objects Specifications
PV Panel specifications at standard test conditions (STC)
PV voltage @ STC 12 V
PV current @ STC 12.5 A
PV power @ STC 150 W
Battery specifications
Battery voltage 24 V
Battery current 14 A/h
Battery power 336 W
BLDC machine specifications
Voltage 48 V
Power 250 W
Speed 227 rpm (45 km/h)
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Maximum Torque 15 Nm
5.3 Aritificial Neural Network based modified Regenerative Braking System
for EHV
This section explains an Aritificial Neural Network (ANN) based new
regenerative braking system in order to control the braking torque during
regenerative braking hence increasing the driving efficiency and performance of an
Electric Vehicle. The ANN controllers are very effective and efficient compared to
the PI and Fuzzy controllers, because the steady state error in case of ANN control is
less and the stabilization of the system is better. Also in the ANN methodology the
time taken for computation is less since there is no mathematical model involve in it.
The performance of the ANN essentially depends on the design process.
First, all possible cases that the ANN needs to learn must be prepared in a training
dataset. Second, the structure of the ANN including the type, number of the hidden
layers, and the number of the neurons in each layer needs to be selected for a given
application. The next stage is training the ANN using the collected datasets. Finally,
the trained ANN must be evaluated and validated using some other datasets to check
its accuracy in generalization. Different simulations show that a four layer feed-
forward Multilayer Perceptron (MLP) neural network structure gives desirable
performance for the ANN in this application. The inputs of the MLP network are
SOC of the battery, the vehicle speed, the PV power and the depression of the brake
pedal. Two hidden layers with 5 and 3 neurons are considered. The outputs of the
utilized ANN are the mechanical braking forces of the rear and front wheels and the
regenerative braking force of the front wheel. Sigmoid function is selected as the
activation function for the neurons in the hidden layers.
During regenerative braking, the motor acts as a generator. Hence, using
appropriate switching algorithm the BLDC generator back- emf is boosted to DC-
link voltage through the inverter and using MB4C the DC link voltage reference is
reduced up to minimum or bucked to charge the battery, this offer efficient
regenerative braking. In this research, by a single foot pedal, coordination of
reformative as well as mechanical braking is attained with a reliable and smooth
brake, braking force distribution is realized through an Artificial Neural Network .
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However, in case of EVs equipped with PV fed EV, the PV power must be
taken into account which leads to implementation complexity. Accordingly, ANN-
based controller is proposed to share the required braking force between the rear and
front wheels of the EV. ANNs are intelligent computing tools which are constructed
from multiple interconnected components, called neurons, which are able to
determine the underlying relationship between the input and output patterns. In order
to evaluate the performance of the proposed Regenerative Braking System (RBS)
different simulation is done in the environment of MATLAB and Simulink, in which
the speed, torque, total braking force, front regenerative braking force, rear
mechanical braking force, dc link current, DC – link voltage and power of
PV/BAT/DC-link are evaluated.
The proposed EV is validated by a 250 W three-phase BLDC machine. A
150 W PV panel and 24 V, 14 A/h battery are employed as input sources. Assume,
PV receives maximum isolation ( ) in both motor and braking conditions.
An SSIC and VSC are employed as the bidirectional converter and the PI algorithm
is used for closed-loop control. Based on the rotor position information using Hall-
effect signals, the EV is accelerated from standstill to a constant speed (40 km/h) at 0
to 1 s. Then, it is decelerated (i.e. regenerative braking through battery) again to near
stationary condition between 1 s to 1.18 s, Moreover to increase the speed of
deceleration performance, mechanical braking is applied at 1.18 s as shown in Figure
4. The simulation results of ANN based modified RGB system for EHV is indicated
in the Figure 5 and it explains the performance of ANN based EHV under motoring
and braking conditions.
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Figure 4. Simulation results of the speed (km/h) of ANN based proposed EV in
motor and braking modes
Figure 5. Waveforms of ANN based EV during motor and braking conditions
To create the training dataset, various simulations are carried out in
MATLAB/SIMULINK by applying different values of SOC of the battery and PV
power. The vehicle speed and the brake strength are established by the training drive
cycle. The selection of the drive cycle is very important for simulation of sufficient
braking scenarios. The braking scenarios occur at different EV speeds and different
brake strengths. Hence, a rich training dataset can be obtained. The specifications of
the training drive cycle can be found in the Appendix A. The braking forces are
calculated based on three criteria: 1) the vehicle is decelerated or stopped in the
specified distance and the time determined by the drive cycle 2) maximum
regeneration is achieved 3) SOC of battery remain within the safe margins.
At increased constant speeds, the regenerative braking torque is increased,
which clearly demonstrates the efficient operation of the proposed ANN controller.
The DC link voltage varies according to the motor speed during EV acceleration and
reduced to minimum during breaking which achieve regenerative braking at low EV
speed. However, it is difficult to achieve regenerative braking at further lowest EV
speed due to relatively low voltage generated by the motor/generator. If the
mechanical braking is not engaged under such circumstance, the EV will not stop in
the specified distance. Hence, it is seen that the ANN controller reduces the
regenerative braking torque as the EV speed decreases, ensuring reliable operation of
the front mechanical braking system.
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6. CONCLUSION
This research work presents a novel approach to design a single stage three port
interconnected converter and three domain voltage control method to validate the
dynamic performance of the system. The proposed converter is simulated in
MATLAB/ Simulation tool box environment and the results are verified in terms of
component count, efficiency and average current conduction losses when compared
with other conventional converters. To manage the power flow between PV and
battery port the proposed topology was identified. A new FLC based regenerative
braking system and ANN based modified regenerative braking system in order to
enhance its performance in terms of driving efficiency and driving distance was
presented.
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8. PROPOSED CONTENTS OF THE THESIS
Chapter 1 INTRODUCTION
1.1 Literature Survey
1.2 Objective of the research
1.3 Research Contribution
1.4 Outline of the research work
1.5 Summary
Chapter 2 DESIGN IMPLEMENTATION AND PERFORMANCE ANALYSIS OF
THE PROPOSED INTERCONNECTED CONVERTER WITH SOLAR PV
SYSTEM 2.1 Introduction
2.2 The architecture of two stage power conditioning system.
2.3 Proposed Methodology
2.4 Operating Principle of MB4 Converter
2.5 Design Procedure of MB4 Converter
2.6 Selection of Perturb and Observe method (PAO)
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2.7 Proposed MB4C control methodology
2.8 Performance analysis of MB4 converter
2.9 Conclusion
CHAPTER 3 FUZZY LOGIC BASED SINGLE STAGE INTERACTION
CONVERTER FOR THE POWER FLOW MANAGEMENT OF PV AND
BATTERY POWERED ELECTRIC VEHICLES
3.1 Introduction
3.2 Proposed PV fed Electric Vehicle system
3.3 Operating modes of proposed PV fed EV system
3.4 Working principle of SSIC under motor mode
3.5 Working principle of SSIC under RGB mode
3.6 Control strategy for proposed PV fed EV system
3.7 Braking control strategy for SSIC using FLC Method
3.8 Conclusion
CHAPTER 4 ARTIFICIAL NEURAL NETWORK BASED SINGLE STAGE
INTERACTION CONVERTER FOR THE POWER FLOW MANAGEMENT OF
PV AND BATTERY POWERED ELECTRIC VEHICLES
4.1 Introduction
4.2 Operating modes of proposed PV fed EV system
4.3 Control strategy for proposed PV fed EV system
4.4 Braking control strategy for SSIC using ANN Method
4.5 Conclusion
CHAPTER 5 SUMMARY AND CONCLUSION
5.1 Summary
5.2 Conclusions
5.3 Scope for Future Work
9. LIST OF PUBLICATIONS
National/International Journals
1. S. Jambulingam and D.M.Mary Synthia Regis Prabha , “Robust Power Flow
Control of PV and Battery Powered Electric Vehicle with Single Stage
Interaction Converter” in Journal of Green Engineering (JGE), Volume-10,
Issue-3, March 2020,ISSN:1904 – 4720(print), ISSN :2245 -4586(online),
[SCOPUS].
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2. S.Jambulingam and D.M.Mary Synthia Regis Prabha, ”ANN Based
Improved Regenerative Braking System on PV/Battery Powered Electric
Vehicles with Single Stage Interaction Converter” in International Journal of
Innovative Technology and Exploring Engineering (IJITEE),ISSN : 2278 –
3075 ,Volume-8,Issue- 9S2, July 2019 ),[SCOPUS].
3. S Jambulingam and M.Mary Synthia Regis Prabha, “A HYBRID AC/DC
MICRO GRID CONVERTER CONTROL”,in International Journal of
Engineering Research and Science and Technology (IJERST), ISSN 2319 –
5991, Volume 4, Issue 3, August 2015.
National/International Conferences
1. S. Jambulingam, “A Novel Three Port Converter Design for Integrated PV
Battery Power Systems” IEEE International Conference on Intelligent
Computing, Instrumentation and Control Technologies, July 2017.
2. S. Jambulingam, “A Comparative Performance Analysis of a Novel Single
Stage Three Port Converter”, International Conference on Advances and
Developments in Electrical and Electronics Engineering (ICADEE 2K20) Feb
2020.
3. S. Jambulingam, “A High Efficiency and High Power Buck and Boost Switch
Snubberfor Electric Vehicle Drives”, National Conference on Recent Trends in
Electrical System, April 2011.
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