=Paper=
{{Paper
|id=Vol-3058/paper60
|storemode=property
|title=Electric Vehicle Battery Charger Using PV Array With FOPID Controller
|pdfUrl=https://ceur-ws.org/Vol-3058/Paper-090.pdf
|volume=Vol-3058
|authors=Aminuddeen,Sulata Bhandari
}}
==Electric Vehicle Battery Charger Using PV Array With FOPID Controller==
https://ceur-ws.org/Vol-3058/Paper-090.pdf
Electric Vehicle Battery Charger using PV Array
with FOPID Controller
Aminuddeen1and Sulata Bhandari2
12
, Punjab Engineering College, Chandigarh, India
Abstract
Electric vehicles (EVs) are emerging as a viable option to gasoline-powered automobiles. The
functioning of these vehicles necessitates the “recharging” of their batteries. Although EV
charging has usually been done via the grid, solar-powered chargers have emerged as a promising
alternative. In addition to this, the biggest concern for experts was to charge EV when solar
irradiance is decreased to zero. For this the proposed model used a battery bank as an alternative
source of energy and is responsible for providing enough power to EV battery in absence of
sunlight. This is done efficiently by using the solar PV panels, sepic dc-dc boost converter,
MPPT charging controller, alternate battery bank.This paper proposes an electric vehicle battery
charger using PV array with FOPID (fractional order PID) controller. The proposed model
works in three modes, firstly when EV battery and battery bank is getting charged by the PV
panels, secondly when EV battery is getting charged by the battery bank and third, when battery
bank supply is cut off and EV battery is getting charged by solar panel only. Experiments were
conducted on MATLAB platform and the simulated outcomes proved that the proposed model is
effective in charging the batteries of EVs. A comparative performance analysis of the battery
bank SOC and that of EV battery reflects that the proposed FOPID controlleris definitely more
efficient and effective for charging the EV.
Keywords 1
EV battery, battery charger, FOPID controller
1. Introduction
Over the last few years, the use of renewable power generation techniques has expanded drastically,
thus it is critical to develop a mechanism in order to ease the implementation of Renewable Energy
Resources (RER) so that the overall efficiency, safety and dependability of the grid is enhanced. As there
is a drastic increase in electricity demand all over the world which makes it crucial to use new sources of
power generation which include solar, wind fuel cells etc. [1]. These RERs have been found very
effective in order to meet the rising demand of energy while also addressing some major environmental
issues. Out of the all the Renewable power generation sources, Solar PV is the most common and
effective one because it is cost effective, highly efficient with low maintenance charges [2].
In a typical solar power generation system, solar PV panels are installed serially or parallelly to
maximize power generation. The power generated by the solar panel directly depends on the intensity
of sunlight which means if intensity of sunlight is more, more power is generated and vice versa [3]. Solar
panels generate DC electrical power. To make this solar energy usable, it must first be converted
International Conference on Emerging Technologies: AI, IoT, and CPS for Science & Technology Applications, September 06–07, 2021,
NITTTR Chandigarh, India
EMAIL: aminpasha35@gmail.com (A. 1); sulata.bhandari@gmail.com (A. 2)
ORCID: 0000-0002-1548-2650 (A. 1); 0000-0002-9653-671X(A. 2)
©2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
fromDirect Current to Alternating Current with the help of an inverter. The AC electrical energy thus
generated can be used to operate local electronics or sent to the electrical grid to be used elsewhere. The
major drawback of using solar power generation systems is its dependency of atmospheric factors such as
solar irradiance and temperature. This leads to inefficiency as the solar panels are unable to extract
maximum power [4]. Owing to their dynamic design, solar power faces difficulties in interacting with
automotive systems too. As a result, it is important to have a battery in EVs in order to address the
issue.Different MPPT (Maximum Power Point Tracking) techniques are used, toimprove system
efficiency and to obtain maximum power from the panels, Some commonly used techniques are: Fuzzy
logic, Perturb and Observe (hill climbing method), Neural Network, Fractional open circuit voltage,
Incremental Conductance method, Fractional short circuit current.To extract maximum power from the
solar PV panels, many techniques have been proposed by several researchers in this field [5-12].
This paper proposes an electric vehicle battery charger using PV array with FOPID(fractional order
PID)controller.Experiments were performed in MATLAB platform and a comparative performance
analysis with the results obtained by using PI and PID controller is done to illustrate the effectiveness of
the proposed method. It uses controller having two stages using a FOPID witha MPPT algorithm to
extract maximum power from the PV system. The FOPID controller is used to vary the duty cycle of
boost converter.
2. FOPID controller
Fractional-order calculus is amathematical tool fordealing with derivatives and integrals from non-
integer orders. In recent times lots of research have been done both by the academicians andindustrialists
dealing with Fractional-order proportional-integral-derivative (FOPID) controllers. Fractional system
provides a better understanding of system characteristic like system response, rejection of disturbance ,
better and improved capability of handling model uncertainties in nonlinear as well as real time
applications.
The ‘s’ domain representation of PID controller is:
C(s)= (Kp +sKd + (Ki/s)) E(s) (1)
Where ‘C(s)’ represents the output of the system, ‘E(s)’is error and Kp,Kdand Kirepresent theproportional,
derivate and integral parameters of the control system.
And the ‘s’ domain representation of FOPID controller is:
C(s)= (Kp +sμKd + (Ki/sλ)) E(s) (2)
Thus, in case of FOPID the power of ‘s’ is fraction compared to PID controller where it is integer. The
aim thus is to optimize the value of the two additional parameters ‘μ’ and ‘λ’ in addition to the three Kp
,Kdand Ki parameters. Thus, they have additional flexibility in the controller design, compared to the
standard PID controller, because they have five degrees-of-freedom (DOF), compared to three DOFs of
its integer-order counterpart. Higher DOF provides better time and frequency responses of the control
system.
3. The proposed system with FOPID controller
The proposed model consists of solar PV panels, sepic dc-dc boost converter, MPPT charging with
FOPID controller, alternate battery bank. The proposed model works in following three modes, Thesepic
converter is used to regulate the voltage and current supply. The MPPT technique is thus used to obtain
maximum power from solar panels by usingthe FOPID controller.
Mode 1: When the sunlight is at peak, the sunlight falls on the solar panel which converts it into the
electrical energy that is capable of charging the battery bank as well as the battery of electric vehicle.
Mode 2: In the next mode, when the input irradiance of sun is very low in such case, the supply of solar
panel is cut off and the battery bank is used as a charging source for EV. The battery bank starts getting
discharged slowly.
Mode 3: In the 3rd mode of operation, the irradiance is increased so that EV is charged by the solar panel
but the battery bank is not charged in this case.
3.1 Design of Converters
(i) Sepicconverter,
Figure1. shows the block diagram of the SEPIC dc-dc boost converter. The main job of FOPID
controller is to pass duty ratio cycle(D1) to the sepic converter in order to pass a consistent output voltage
to the EV regardless of the input PV voltage.
Another major advantage of using the Sepic converter is that it can operate in boost and buck modes
depending on the duty ratio cycle.
Figure 1:SEPIC dc-dc boost converter
The output voltage produced by the sepic dc-dc boost converter[13]can be calculated by the equation 3.
𝑉𝑉𝑑𝑑𝑑𝑑 𝐷𝐷
= (3)
𝑉𝑉𝑃𝑃𝑃𝑃 1−𝐷𝐷
Where Vdc represent dc link voltage, Vpv represent the voltage produced by the solar PV array and D is
the duty cycle ratio to the sepic converter. The value of capacitors and inductors that are present in the
sepic converter can be calculated by equation 4,5 and 6.
𝑉𝑉𝑃𝑃𝑃𝑃 𝑚𝑚𝑚𝑚𝑚𝑚 𝐷𝐷 𝑚𝑚𝑚𝑚𝑚𝑚
La = Lb= (4)
2∆𝑖𝑖 𝑃𝑃𝑃𝑃 𝑓𝑓 𝑆𝑆𝑆𝑆
𝐼𝐼𝑑𝑑𝑑𝑑 𝐷𝐷𝑚𝑚𝑚𝑚𝑚𝑚
C1 = (5)
∆𝑉𝑉𝑐𝑐1 𝑓𝑓 𝑆𝑆𝑆𝑆
𝐼𝐼𝑑𝑑𝑑𝑑 𝐷𝐷𝑚𝑚𝑚𝑚𝑚𝑚
C2 = (6)
∆𝑉𝑉𝑑𝑑𝑑𝑑 𝑓𝑓 𝑆𝑆𝑆𝑆
Where 𝑉𝑉𝑃𝑃𝑃𝑃 𝑚𝑚𝑚𝑚𝑚𝑚 represents the minimum voltage generated by PV panels, ΔiPVrepresents the input current
ripple, fSWrepresent the switching frequency, Idcrepresents the dc link current, ΔVC1represents the voltage
ripple of capacitor C1, ΔVdc represents the output voltage ripple, and Dmax represents the maximum duty
ratio which can be calculated by the equation 7.
𝑉𝑉𝑑𝑑𝑑𝑑 +𝑉𝑉𝐷𝐷
Dmax = (7)
𝑉𝑉𝑃𝑃𝑃𝑃 𝑚𝑚𝑚𝑚𝑚𝑚 + 𝑉𝑉𝑑𝑑𝑑𝑑 +𝑉𝑉𝐷𝐷
where VD represents the voltage drop in diode.
(ii) Bidirectional dc-dc converter
Figure 2. below presents the circuit for bidirectional charging circuit.
The diagram of the proposed model is shown in Figure 3, along with its basic components which include
PV panel, battery bank, EV battery, switches, MPPT algorithm etc.When the rays of sunlight fall on the
solar PV panels, these are converted into the electrical energy in order to provide sufficient amount of
voltage and current for charging the EV and battery bank.
Figure 2: Bidirectionalcharging circuit
Figure 3: The Proposed Model
To maximize the poweroutput from the solar PV panels, the proposed model utilized the FOPID
MPPT controller.
The FOPID controller block diagram is as shown in figure 4.
Figure 4: Block Diagram of FOPID Controller
4. Methodology and Results
The process opted by the proposed FOPID system to charge electric vehicles by using solar PV panels are
explained briefly here;
1. Initially, when the sunlight falls on the PV panels that are converted to the electrical energy in order
to charge the batteries of EVs. As the proposed model is working in three modes, the first mode is
when battery bank and EV battery are getting charged by the solar PV panel. A number of
parameters are defined such as input solar irradiance, temperature, open circuit voltage etc. Other
than this there are some other important parameters which are given in table1.
2. Once the voltage is generated, DC-DC converter requires a duty cycle to perform effective
operations. For this a MPPT technique is designed which would assist the converter to produce duty
cycle, whichin this case is generated using the FOPID converter (taking λ= 0.0675 and μ= 0.5).
Table 1.
Solar PV panel parameters
Solar Panel Parameter Value
Input Irridaince (w/m2) [850,500,100]
Input Tempearture(deg.C) 25
Parallel strings 4
Series-connected modules per string 1
Maximum Power (W) 175.062
Open circuit voltage Voc (V) 44.3
Cells per module (Ncell) 72
Short-circuit current Isc (A) 5.29
Current at maximum power point Imp (A) 4.89
Voltage at maximum power point Vmp (V) 35.8
Temperature coefficient of Voc (%/deg.C) -0.374
Temperature coefficient of Isc (%/deg.C) 0.088998
3. In the second mode, the battery of EV is getting charged by the battery bank and solar PV supply is
switched off. The different parameters of the battery bank are defined which are shown in table 2
along with their values[8].
Table2.Table 3.
Battery bank parameters EV battery parameters
The third mode of the proposed system is when alternate charging source i.e., battery bank is turned off
and battery of EV is getting charged by the solar PV panels. Table 3. below represents the different EV
parameters along with their configurational values.
4. The waveforms of the energy produced by the solar PV panels for voltage, current and total power
in three modes of operation are evaluated and are shown in figure5 (a) and (b)and Fig.
6respectively.
35
30
25
20
Volatge(V)
15
10
5
0
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Time(sec)
Figure 5:(a)Voltage ofSolar PV panels(b)Currentof Solar PV panelsFigure 6:total power generated
Furthermore, in order to track the MPPT in the system duty ratio is passed to the sepic dc-dc boost
converter by the FOPID controller. The regulated voltage and current generated by the sepic dc-dc boost
converter is as shown in figure 7.
600
500
400
Power(Watts)
300
200
100
0
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Time(sec)
Figure 7: (a)Powerby Sepic converter(b)Current waveform by Sepic converter
5. Moreover, the charging and discharging waveform forthe three operating modesfor battery bank
is obtained along with its voltage and current waveforms and are shown in figure below.
70.018 180
70.016 160
70.014 140
70.012 120
70.01 100
Battery Bank Current(A)
Battery Bank SOC(%)
70.008 80
70.006 60
70.004 40
70.002 20
70 0
69.998 -20
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Time(sec) Time(sec)
Figure 8: (a)SOC(b) current and (c)voltage waveforms by battery bank
Figure 8(a) shows the battery bank SOC diagram.From the graph, it is observed that initially the battery
is getting charged by the solar PV panel in mode 1. But as soon as the next mode starts the battery
starts to discharge slowly up to 1.3 sec. After 1.3 sec, the third mode starts in which the battery is
neither getting charged nor discharged i.e., it remains constant.
6. Likewise, the SOC of EVs battery is obtained along with its current and voltage waveform which are
shown in figure 9 below.
Figure represents the state of charge of the EV batteries. From the graph, it is analyzed that the EV is
getting charged in all the three modes. In the first mode, EV battery is getting charged by the Solar PV
panel and battery bank, in the second mode, it’s getting charged by the battery bank and in the third
mode, the battery of EV is getting charged by the PV panel.
20
50.009
0
50.008
-20
50.007
-40
50.006
-60
EV Battery Current(A)
EV Battery SOC(%)
50.005
-80
50.004
-100
50.003
-120
50.002 -140
50.001 -160
50 -180
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
Time(sec) Time(sec)
Figure 9: (a) SOCfor EV battery(b) currentfor EV battery(c) voltage graph for EV battery
The performance of the proposed FOPID model is tested and compared with the PI and PID controller
models in the MATLAB simulation software in terms of their voltage and current readings. The
simulation outcomes obtained are described in detail in this section.
5. Comparison with PIand PID models
The performance of the proposed FOPID model is analyzed and compared with the conventional PI
and PID models in terms of the voltage generated by solar PV panels.
70.0016
PI
PID
70.00155
FOPID
70.0015
70.00145
Battery Bank SOC(%)
70.0014
70.00135
70.0013
70.00125
70.0012
0.086 0.088 0.09 0.092 0.094 0.096 0.098 0.1 0.102
Time(sec)
Figure10.SOC of Battery bankFigure 11. SOC of EV battery
Figure 10. depicts the comparison graph of the proposed FOPID model and traditional PI and PID
models in terms of the battery bank SOC.The performance of the conventional PI and PID model is
represented by the blue- and orange-colored lines. On the other hand, the performance of the proposed
FOPID model is represented by the yellow-colored line.
From the graph, it is observed that the battery bank SOC in the proposed model is higher than the
traditional two approaches which lasts more than 70.00155%, thus making it long lasting and efficient .
Lastly, the performance of the proposed model is also determined in terms of the state of charge of EV
battery. Figure 11. demonstrates the comparison graph of the proposed FOPID model and traditional PI
and PID models in terms of the EV battery SOC. The performance of the traditional PI and PID model is
represented by the blue- and orange-colored lines and the performance of the proposed FOPID model is
represented by the yellow-colored line. From the graph, it is observed that in all the three modes of
operation the EV is getting charged constantly. However, after analyzing the graph closely it is observed
that the EV battery of the proposed FOPID model lasts longer than the conventional two approaches.
From the graphs, it is observed that the proposed FOPID model outperforms the classical PI and PID
model in all the factors and is more effective and efficient in charging EV through solar panels.
6. Conclusion
The simulation outcomes are obtained in terms of the voltage and current generated. In case of the
proposed FOPID model, the voltage and current doesn’t fluctuate much and can effectively charge EVs
and battery bank of EVs. Similarly, the performance of the proposed FOPID model is compared with the
conventional PI and PID models in terms of the voltage and current generated by the sepic dc-dc
converter. The voltage generated by the sepic dc-dc converter remains constant in all three operating
modes which ultimately provides sufficient amount of current to the EV for charging. Lastly, the charging
state of the battery bank and EV battery is determined in which the proposed model outperforms the
classical PI and PID models. All these factors, make the proposed FOPID model more efficient and
effective for charging the EV.
7. Future research scope
FOPID has more number of parameters to be tuned, thus providing better and finer tuning than PID
controllers to meet the system target. In spite of the technical advantages offered by FOPID over its
integer-order counterparts the adoption of the fractional order controller in the industry is slow. The cost
of producing such controllers, the cost-benefit to the end user and the complexity of implementation of
FOPID controllers with respect to its extra tuning flexibility verses the extent of performance
improvement are certain factors which needs to be investigated to make it readily acceptable to the
industry.
8. References
[1]E. Zhou, T. Logenthiran and W. L. Woo, "Integration of a PV-battery hybrid system with the main
power grid," 2016 IEEE 6th International Conference on Power Systems (ICPS), pp. 1-5, 2016.
[2] T.Abderrahim and B. Said, "Control and management of grid connected PV-Battery hybrid system
based on three-level DCI," 2017 6th International Conference on Systems and Control (ICSC), pp. 439-
444, 2017.
[3] X. Zhou, M. Liu, Y. Ma and Z. Gao, "An Overview of Photovoltaic System," 2018 Chinese Control And
Decision Conference (CCDC), pp. 4949-4954, 2018.
[4] K. Dubey and M. T. Shah, "Design and simulation of Solar PV system," 2016 International Conference
on Automatic Control and Dynamic Optimization Techniques (ICACDOT), pp. 568-573, 2016.
[5] V. V. Joshi, N. Mishra and D. Malviya, (2018),"Solar Energy Integration with New Boost Converter for
Electric Vehicle Application," 2018 8th IEEE India International Conference on Power Electronics (IICPE),
pp. 1-6.
[6] K.Amara et al., “Improved Performance of a PV Solar Panel with Adaptive Neuro-Fuzzy Inference
System ANFIS based MPPT,” 2018 7th International Conference on Renewable Energy Research and
Applications (ICRERA), Paris, 2018, pp.1098-1101.
[7] H. K. Singh and N. Kumar, (2020), "Current Controlled Charging Scheme for off Board Electric vehicle
Batteries from Solar PV Array," 2020 7th International Conference on Signal Processing and Integrated
Networks (SPIN) pp. 935-940.
[8] Paul, Ankita& Subramanian, Krithiga& NACHINARKINIYAN, Sujitha, (2019), “PV-based off-board
electric vehicle battery charger using BIDC”, Turkish Journal of Electrical Engineering & Computer
Sciences, pp. 2850-2865.
[9] B.Revathi, A. Ramesh, S. Sivanandhan, T. B. Isha, V. Prakash and S. G., (2018),"Solar Charger for
Electric Vehicles," 2018 International Conference on Emerging Trends and Innovations in Engineering
and Technological Research (ICETIETR), Ernakulam, pp.1-4.
[10] A. KV, G. Warrier, S. Biswas and J. Peter, (2020), "Design and Analysis of a High Efficient Converter
for EV Charging Stations Integrated with PV Panels and 3 Phase Auxiliary Supply," 2020 International
Conference on Futuristic Technologies in Control Systems & Renewable Energy (ICFCR), pp. 1-6.
[11] Z.Alqarni and J. Asumadu, (2019), "Battery Charging Application Thorough PVA and MPPT Controller
with Voltage Regulation," 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile
Communication Conference (UEMCON), pp. 0523-0527.
[12] S. S. Nadkarni, S. Angadi and A. B. Raju, "Simulation and Analysis of MPPT Algorithms for Solar PV
based Charging Station, (2018)", “Electronics and Mechanical Systems (CTEMS)”, 2018 International
Conference on Computational Techniques pp. 45-50.
[13] Subramanian, K., & N, S. (2020). An Off-board Electric Vehicle Battery Charger using PV Array. IET
Electrical Systems in Transportation. doi:10.1049/iet-est.2019.0035
[14] Fatemidokht, H., Rafsanjani, M. K., Gupta, B. B., & Hsu, C. (2021), “Efficient and Secure Routing
Protocol Based on Artificial Intelligence Algorithms With UAV-Assisted for Vehicular Ad Hoc Networks in
Intelligent Transportation Systems”, IEEE Transactions on Intelligent Transportation Systems, vol22,
no.7, pp4757-4769