PV Grid Based EV Charging Station in MATLAB

PV Grid Based EV Charging Station in MATLAB

𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧

The PV Grid Based EV Charging Station in MATLAB demonstrates how a solar photovoltaic system and utility grid can work together to provide continuous charging power to an electric vehicle battery.

PV Grid Based EV Charging Station

PV Grid Based EV Charging Station in MATLAB

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The complete system is developed in MATLAB/Simulink and includes:

• Solar PV array

• Boost converter

• Incremental Conductance MPPT

• EV battery

• Bidirectional DC–DC converter

• 400 V DC bus

• Single-phase grid

• Grid-connected full-bridge inverter

• Filter

• DC-bus voltage controller

• Grid current controller

• PWM generation

• Voltage, current, power, and SOC measurements

The main objective is simple: use maximum available solar power for EV charging and automatically obtain the remaining required charging power from the grid.

𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

The Simulink model can be divided into three major sections.

Section	Main Components	Purpose
Power Section	PV array, EV battery, converters, inverter, grid	Handles electrical power conversion and transfer
Control Section	MPPT, voltage controller, grid current controller, PWM	Controls PV, battery converter, and grid inverter
Measurement Section	PV, battery, DC bus, grid, combined power measurements	Monitors complete system performance

This structure makes the model easy to understand and suitable for studying renewable-energy-based EV charging.

𝐏𝐕 𝐒𝐲𝐬𝐭𝐞𝐦

The solar PV array is the primary renewable energy source of the charging station.

PV Array Parameters

Parameter	Value
Single PV panel rated power	250 W
Modules connected in series	8
Parallel strings	1
Maximum PV array power	2000 W
Voltage at maximum power point per module	30.7 V
Current at maximum power point per module	≈8.1 A
Approximate array MPP voltage	≈245 V
Standard irradiance	1000 W/m²
Standard temperature	25°C

Eight PV modules connected in series provide an operating voltage of approximately 245 V around the maximum power point.

The PV voltage changes slightly when:

• Solar irradiance changes

• PV temperature changes

• Operating conditions vary

For this model, the PV-side converter is therefore designed around an input voltage of approximately 245 V and a DC-bus voltage of 400 V.

𝐏𝐕 𝐏𝐨𝐰𝐞𝐫 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐢𝐨𝐧

The PV array is connected to the common DC bus through a boost converter.

Boost Converter Operating Requirement

Parameter	Approximate Value
PV-side input voltage	245 V
DC-bus voltage	400 V
Maximum PV power	2000 W
Converter type	Boost converter

The boost converter performs two important functions:

• Increases the PV voltage from approximately 245 V to 400 V

• Allows the MPPT controller to adjust the PV operating point

𝐈𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 𝐂𝐨𝐧𝐝𝐮𝐜𝐭𝐚𝐧𝐜𝐞 𝐌𝐏𝐏𝐓

An Incremental Conductance MPPT algorithm is used to extract the maximum available power from the PV array.

MPPT Inputs and Output

Signal	Description
PV Voltage	Measured PV terminal voltage
PV Current	Measured PV output current
Duty Cycle	Output of the MPPT controller

The MPPT algorithm continuously observes changes in:

• PV voltage

• PV current

• PV power

Based on these changes, the controller decides whether the operating voltage should be increased or decreased.

The calculated duty cycle is supplied to a PWM generator, which produces the switching pulse for the boost converter.

Main MPPT Process

1. Measure the PV voltage and current.

2. Calculate the present operating condition.

3. Compare it with the previous operating condition.

4. Determine whether the PV operating point is below, above, or near the maximum power point.

5. Increase or decrease the duty cycle accordingly.

6. Generate the PWM pulse.

7. Control the boost converter.

8. Continue the process for every control sampling interval.

This enables the PV system to track the available maximum power even when irradiance changes.

𝐄𝐕 𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐒𝐲𝐬𝐭𝐞𝐦

The EV battery is connected to the 400 V DC bus through a bidirectional DC–DC converter.

EV Battery Parameters

Parameter	Value
Battery nominal voltage	240 V
Battery capacity	40 Ah
Initial SOC	50%
Maximum charging power considered	≈2000 W
DC-bus voltage	400 V
Converter type	Bidirectional DC–DC converter

The battery-side converter is designed to interface the 240 V battery with the 400 V DC bus.

𝐁𝐢𝐝𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐚𝐥 𝐃𝐂–𝐃𝐂 𝐂𝐨𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐂𝐨𝐧𝐭𝐫𝐨𝐥

The bidirectional converter is controlled using a DC-bus voltage control strategy.

The reference DC-bus voltage is set to:

400 V

The actual DC-bus voltage is continuously measured and compared with this reference.

The resulting error is processed through a controller to generate the required duty cycle.

Control Sequence

• Measure DC-bus voltage

• Compare it with 400 V

• Process the voltage error through the controller

• Generate duty cycle

• Send duty cycle to the PWM generator

• Generate converter switching pulse

• Regulate the energy transfer between the DC bus and EV battery

The main purpose is to keep the common DC bus close to its desired value during changing PV generation conditions.

𝐆𝐫𝐢𝐝 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧

The charging system also includes a single-phase utility grid.

Grid Parameters

Parameter	Value
Grid voltage	230 V RMS
Grid frequency	50 Hz
Interface	Full-bridge inverter
DC-side voltage	400 V
Control method	Current control
Application	Supplementary EV charging power

The grid is connected through:

• Grid-side filter

• Full-bridge converter

• Current measurement

• Grid voltage measurement

• Synchronization and current control

𝐆𝐫𝐢𝐝 𝐏𝐨𝐰𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

The grid supplies the power that cannot be provided by the PV system.

The EV charging demand is approximately 2 kW.

Typical Power-Sharing Conditions

PV Power	Approximate Grid Contribution	Charging Condition
2000 W	Very small / near zero	PV supplies almost all charging power
1000 W	Approximately 1000 W	PV and grid share charging demand
0 W	Approximately 2000 W	Grid supplies almost all charging power

This creates an automatic PV-priority charging strategy.

When more solar energy is available, grid dependence decreases.

When solar energy decreases, the grid compensates for the power shortage.

𝐈𝐧𝐯𝐞𝐫𝐭𝐞𝐫 𝐂𝐨𝐧𝐭𝐫𝐨𝐥

The grid-connected inverter is controlled using a current control strategy.

The controller determines how much grid current is required based on:

• Desired EV charging power

• Available PV power

• Grid voltage

• Measured inverter current

The required charging power is compared with the available PV power.

The resulting power requirement determines the necessary grid current reference.

𝐆𝐫𝐢𝐝 𝐒𝐲𝐧𝐜𝐡𝐫𝐨𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧

The measured grid voltage is used to obtain synchronization information.

The control system generates:

• Grid phase information

• Sine signal

• Cosine signal

These signals are used by the current controller to synchronize the inverter current with the utility grid.

Proper synchronization is necessary for controlled power transfer between the grid and DC charging system.

𝐂𝐮𝐫𝐫𝐞𝐧𝐭 𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

The inverter controller processes the current reference in a transformed reference frame.

The main control flow is:

Charging Power Reference → PV Power Measurement → Required Grid Power → Current Reference → Current Controller → Inverter Voltage Command → PWM Generator → Inverter

The measured inverter current is compared with the generated reference current.

The controller then produces the required voltage-control signal.

This signal is finally processed by the PWM generator to operate the inverter switches.

𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬

The complete EV charging operation can be summarized as follows:

1. The PV array generates DC power according to solar irradiance.

2. The Incremental Conductance MPPT tracks the maximum available PV power.

3. The boost converter increases the PV voltage to the common 400 V DC bus.

4. The EV battery is connected through a bidirectional DC–DC converter.

5. The battery-side controller regulates the DC-bus voltage.

6. The required EV charging power is determined.

7. Available PV power is measured.

8. If PV power is sufficient, most of the charging power comes from solar energy.

9. If PV power decreases, the grid automatically supplies the deficit.

10. The inverter current controller regulates the required grid power.

11. The EV battery therefore receives relatively continuous charging power despite changes in solar irradiance.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬

To verify system operation, the PV irradiance is varied during simulation.

Irradiance Profile

Operating Stage	Solar Irradiance
Stage 1	1000 W/m²
Stage 2	500 W/m²
Stage 3	Very low / near zero generation condition
Stage 4	500 W/m²
Stage 5	1000 W/m²

This allows the system response to be studied under both high and low solar-energy availability.

𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬

The results clearly demonstrate coordinated operation between the PV system, EV battery, and utility grid.

PV Power Response

At high irradiance:

• PV output approaches 2 kW

• Maximum available solar energy is extracted

• Grid power requirement becomes very small

At reduced irradiance:

• PV power decreases to approximately 1 kW

• The grid supplies the remaining charging requirement

At very low PV generation:

• PV power approaches zero

• The grid provides approximately the full EV charging requirement

When irradiance increases again:

• PV generation recovers

• Grid contribution automatically decreases

𝐏𝐕 𝐕𝐨𝐥𝐭𝐚𝐠𝐞 𝐚𝐧𝐝 𝐂𝐮𝐫𝐫𝐞𝐧𝐭

The simulation displays:

• PV voltage

• PV current

• PV power

The current changes significantly with irradiance, while the MPPT controller continuously adjusts the PV operating condition to extract the available maximum power.

𝐄𝐕 𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞

The EV battery results include:

• Battery voltage

• Battery charging current

• Battery power

• Battery SOC

The simulation shows continuous charging operation even when PV generation varies because the utility grid compensates for insufficient solar power.

The SOC gradually increases from its initial value of approximately 50%, confirming battery charging.

𝐏𝐨𝐰𝐞𝐫 𝐒𝐡𝐚𝐫𝐢𝐧𝐠 𝐑𝐞𝐬𝐮𝐥𝐭

One of the most important results is the coordinated change between PV power and grid power.

Solar Condition	PV Contribution	Grid Contribution	EV Charging
High irradiance	High	Low	Continuous
Medium irradiance	Medium	Medium	Continuous
Very low irradiance	Very low	High	Continuous
Irradiance recovery	Increasing	Decreasing	Continuous

This confirms that the control system automatically adjusts the grid contribution according to solar power availability.

𝐌𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭 𝐒𝐞𝐜𝐭𝐢𝐨𝐧

The Simulink model contains dedicated scopes for observing important system variables.

PV Measurement

• PV voltage

• PV current

• PV power

DC-Bus Measurement

• DC-bus voltage

EV Battery Measurement

• Battery voltage

• Battery current

• Battery power

• Battery SOC

Grid Measurement

• Grid voltage

• Grid current

• Grid power

Combined Power Measurement

• PV power

• EV battery power

• Grid power

This combined power display is particularly useful for understanding real-time energy sharing between the solar PV system and grid.

𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲

Subsystem	Control Technique	Main Objective
PV system	Incremental Conductance MPPT	Extract maximum PV power
PV boost converter	PWM switching	Boost PV voltage to DC bus
EV bidirectional converter	DC-bus voltage control	Maintain approximately 400 V
Grid inverter	Current control	Regulate grid power contribution
Grid synchronization	Phase/sine-cosine generation	Synchronize inverter with grid
Inverter switching	PWM generation	Generate semiconductor gate pulses

The coordinated control of these subsystems enables stable and continuous charging operation.

𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬

• 2 kW solar PV generation system

• 240 V, 40 Ah EV battery

• 400 V common DC bus

• 230 V, 50 Hz single-phase grid

• Incremental Conductance MPPT

• Solar-priority EV charging

• Grid-assisted charging during low irradiance

• Bidirectional DC–DC converter

• Grid-connected full-bridge inverter

• DC-link voltage regulation

• Current-controlled grid interface

• PWM-based converter switching

• Variable irradiance simulation

• PV, battery, grid, and DC-bus measurements

• Combined power-flow visualization

• SOC monitoring

• Automatic adjustment of grid contribution

𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬

The proposed MATLAB/Simulink model provides several advantages:

• Improves utilization of available solar power

• Reduces dependence on utility-grid energy during high solar generation

• Maintains EV charging during low PV generation

• Demonstrates coordinated PV-grid energy management

• Provides simple visualization of system power flow

• Helps understand converter and inverter control

• Allows testing under different irradiance conditions

• Can be extended with advanced energy-management techniques

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬

This simulation concept can be useful for studying:

• Solar-powered EV charging stations

• Grid-assisted EV chargers

• Renewable-energy charging infrastructure

• Smart charging systems

• PV-grid energy management

• DC microgrids

• Bidirectional converter control

• Grid-connected inverter control

• EV battery charging analysis

• Renewable-energy integration

• Intelligent charging station development

It is particularly useful for students, researchers, engineers, and MATLAB/Simulink learners who want to understand the complete operation of a solar PV and grid-based EV charging system.

𝐅𝐮𝐭𝐮𝐫𝐞 𝐄𝐱𝐭𝐞𝐧𝐬𝐢𝐨𝐧𝐬

The model can be further expanded by adding:

• Battery charging and discharging modes

• Vehicle-to-Grid operation

• Grid-to-Vehicle operation

• Battery SOC-based energy management

• Electricity tariff-based charging

• ANN-based MPPT

• Fuzzy Logic MPPT

• ANFIS MPPT

• Optimization-based MPPT

• Stationary battery energy storage

• Wind energy integration

• Multiple EV charging ports

• Smart charging scheduling

• Load forecasting

• PV power forecasting

• Grid power quality analysis

𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧

The PV Grid Based EV Charging Station in MATLAB successfully demonstrates coordinated EV charging using solar PV energy and the utility grid.

The 2 kW PV array operates through an Incremental Conductance MPPT-controlled boost converter and supplies power to a 400 V DC bus. A 240 V, 40 Ah EV battery is connected through a bidirectional DC–DC converter.

When sufficient solar power is available, most of the charging requirement is supplied by the PV system. When irradiance decreases, the 230 V, 50 Hz utility grid automatically provides the required additional power through the controlled inverter.

The simulation clearly demonstrates how PV generation, grid support, DC-bus regulation, converter control, and EV battery charging can be integrated into a single MATLAB/Simulink model.