MATLAB Simulation of Fuel Cell Battery and Supercapacitor Sourced EV System
MATLAB Simulation of Fuel Cell Battery and Supercapacitor Sourced EV System
𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧
The MATLAB Simulation of Fuel Cell Battery and Supercapacitor Sourced EV System demonstrates how multiple energy sources can be coordinated to meet the dynamic power requirement of an electric vehicle.
The simulated EV power system combines:
⚡ Fuel Cell as the main energy source
🔋 Lithium-ion Battery for energy balancing
🔋 Supercapacitor for fast transient power support
🔄 DC–DC converters for controlled power transfer
🚗 EV drive model operated using a driving cycle
🧠 State-machine-based energy management
⚙️ DC–AC converter for supplying the electric motor
The main objective is to maintain reliable power delivery to the EV while efficiently sharing the load among the fuel cell, battery, and supercapacitor.
𝐒𝐲𝐬𝐭𝐞𝐦 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰
The hybrid EV architecture uses a common DC-link/DC bus that connects the different energy sources to the propulsion system.
Component | Main Function |
Fuel Cell | Supplies the primary EV power |
Battery | Provides charging and discharging power support |
Supercapacitor | Handles rapid load-power variations |
Fuel Cell Boost Converter | Interfaces the low-voltage fuel cell with the DC bus |
Battery Boost Converter | Transfers battery power toward the DC bus |
Battery Buck Converter | Transfers DC-bus power toward the battery |
DC Link | Common power-sharing point |
DC–AC Converter | Supplies AC power to the EV motor |
EV Model | Produces dynamic power demand according to the drive cycle |
State Machine | Determines the required operating condition |
This hybrid structure allows each source to operate according to its most suitable dynamic characteristics.
𝐌𝐚𝐢𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 𝐏𝐚𝐫𝐚𝐦𝐞𝐭𝐞𝐫𝐬
Fuel Cell Parameters
Parameter | Value |
Nominal Power | 10.2875 kW |
Maximum Power | 12.544 kW |
Nominal Voltage | 41.15 V |
Current at Nominal Operating Point | 250 A |
Voltage at Maximum Power | 39.2 V |
Current at Maximum Power | 320 A |
The fuel cell is connected to the common DC bus through a DC–DC boost converter.
Its output power is adjusted based on the EV load requirement and the commands generated by the energy-management controller.
Battery Parameters
Parameter | Specification |
Battery Type | Lithium-ion |
Nominal Voltage | 48 V |
Converter Configuration | Boost + Buck |
Power Flow | Bidirectional |
Maximum Battery Power Used in Control | 3400 W |
The battery performs two important operating modes:
Discharging: Battery → DC Link
Charging: DC Link → Battery
The boost converter is mainly associated with battery discharging, while the buck converter enables battery charging.
Supercapacitor Parameters
Parameter | Value |
Rated Voltage | 291.6 V |
Initial Voltage | 270 V |
Rated Capacitance | 15.6 F |
Equivalent DC Resistance | 150 mΩ |
Number of Series Capacitors | 8 |
Parallel Capacitor Branches | 1 |
The supercapacitor provides rapid power support during sudden acceleration, deceleration, and other transient driving conditions.
𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐜𝐞𝐬𝐬
The complete simulation operates according to the EV driving cycle.
1. EV Drive Cycle
The drive-cycle block generates changing driving conditions.
As the drive cycle changes:
EV motor demand changes
EV load power changes
Fuel-cell power changes
Battery charging/discharging changes
Supercapacitor power changes
Therefore, the simulation represents a dynamic EV operating condition rather than a constant electrical load.
2. EV Load Power Calculation
The controller continuously measures the power demanded by the EV.
This power information is processed and supplied to the state-machine controller.
The controller also receives the battery State of Charge (SOC).
3. Operating State Selection
The state machine determines the operating state based mainly on:
Battery SOC
EV load power
Minimum fuel-cell power
Maximum fuel-cell power
Optimal fuel-cell operating power
The selected state determines how much power should be generated by the fuel cell.
4. Power Sharing
After the fuel-cell reference is determined:
Fuel cell supplies the primary power.
Battery supplies or absorbs additional energy.
Supercapacitor compensates rapid transient power.
The combined source power follows the EV power requirement.
𝐂𝐨𝐧𝐭𝐫𝐨𝐥 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲
Fuel Cell Energy Management
The fuel-cell controller uses a state-machine approach.
Important control parameters used in the simulation include:
Control Parameter | Value |
Minimum Battery SOC | 60% |
Maximum Battery SOC | 90% |
Nominal SOC Level 1 | 85% |
Nominal SOC Level 2 | 60% |
Minimum Fuel Cell Power | 850 W |
Maximum Fuel Cell Power | 8800 W |
Optimal Fuel Cell Power | 1500 W |
Maximum Battery Power | 3400 W |
The controller compares the EV load demand with these fuel-cell power limits.
For example:
At low load demand, the fuel cell can operate near its minimum allowed power.
At moderate demand, its reference is adjusted according to load and SOC conditions.
Under higher demand, the fuel-cell output is limited by its defined maximum control value.
Battery and supercapacitor compensate for the remaining power requirement.
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐒𝐎𝐂-𝐁𝐚𝐬𝐞𝐝 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧
The controller classifies battery operating conditions according to its SOC range.
SOC Condition | Controller Interpretation |
SOC above maximum limit | High-SOC operating region |
SOC between nominal limits | Normal operating region |
SOC approaching minimum limit | Restricted discharge region |
SOC below minimum limit | Battery protection condition |
This prevents excessive battery discharge and supports more reliable energy management.
𝐅𝐮𝐞𝐥 𝐂𝐞𝐥𝐥 𝐂𝐨𝐧𝐭𝐫𝐨𝐥
The required fuel-cell power command is converted into an appropriate fuel-cell current reference.
The controller also considers the DC-link voltage.
The intended DC-link operating region described in the simulation is approximately:
DC-Link Parameter | Value |
Reference Voltage | 270 V |
Approximate Operating Range | 260–285 V |
A PI-based control loop produces the required current command for DC-link voltage regulation.
The resulting control commands are applied to the fuel-cell boost converter.
𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐂𝐡𝐚𝐫𝐠𝐢𝐧𝐠 𝐚𝐧𝐝 𝐃𝐢𝐬𝐜𝐡𝐚𝐫𝐠𝐢𝐧𝐠 𝐂𝐨𝐧𝐭𝐫𝐨𝐥
The battery control section compares the actual DC-link voltage with the reference value of approximately 270 V.
The controller determines whether the battery should:
supply power,
absorb power,
or remain close to zero power.
Discharging Mode
When the DC bus requires additional energy:
Battery → Boost Converter → DC Link
The battery assists the fuel cell in supplying the EV.
Charging Mode
When excess energy is available:
DC Link → Buck Converter → Battery
The battery absorbs the available surplus power.
This arrangement provides bidirectional battery power flow.
𝐒𝐮𝐩𝐞𝐫𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐨𝐫 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧
The supercapacitor is mainly responsible for handling rapid changes in EV load demand.
During Sudden Load Increase
When EV power suddenly increases:
Fuel-cell response may not be instantaneous.
Battery provides additional energy.
Supercapacitor quickly discharges to compensate for the transient power demand.
During Sudden Load Reduction
When EV load suddenly decreases:
Surplus power may temporarily appear on the DC bus.
Supercapacitor absorbs this energy and enters charging operation.
This charge/discharge process may occur repeatedly throughout the driving cycle.
The supercapacitor is therefore especially useful for short-duration high-power events.
𝐄𝐕 𝐏𝐫𝐨𝐩𝐮𝐥𝐬𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦
The common DC bus is connected to the electric vehicle drive through a DC–AC converter.
The propulsion system uses a permanent-magnet-based electric motor model.
The overall energy path can be represented simply as:
Fuel Cell + Battery + Supercapacitor → DC Bus → DC–AC Converter → EV Motor
The driving cycle controls the required vehicle operating condition, resulting in continuously changing propulsion power demand.
𝐏𝐨𝐰𝐞𝐫 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫
The main power-sharing behavior can be summarized as follows:
EV Operating Condition | Fuel Cell | Battery | Supercapacitor |
Very low load | Low power operation | May charge | Small transient action |
Normal driving | Main power source | Supports balance | Near-zero/low activity |
Sudden acceleration | Increases power | Discharges | Fast discharge |
High power demand | Supplies controlled maximum | Provides support | Transient support |
Sudden load reduction | Reduces power | May charge | Charges rapidly |
Regenerative/excess-power condition | Reduced generation | Charging possible | Absorbs transient energy |
𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐑𝐞𝐬𝐮𝐥𝐭𝐬
The MATLAB/Simulink model provides several important waveforms for evaluating the hybrid EV power system.
Fuel Cell Results
The simulation displays:
Fuel-cell voltage
Fuel-cell current
Fuel-cell power
During operation, the fuel-cell output changes according to the EV power demand and the state-machine command.
The fuel-cell voltage is observed around the 40 V region during typical operation, while its current varies substantially with the required load power.
Battery Results
The battery scope displays:
Battery current
Battery voltage
Battery SOC
Battery power
Positive and negative current/power behavior represents the changing charging and discharging conditions.
For the demonstrated driving cycle, the SOC varies approximately within the 60–65% region during a significant part of the simulation.
Supercapacitor Results
The supercapacitor scope includes:
Supercapacitor current
Supercapacitor voltage
Supercapacitor power
The power waveform shows short-duration positive and negative peaks.
These peaks indicate that the supercapacitor is actively compensating fast power variations instead of continuously providing the main EV energy.
Fuel Consumption Results
Fuel-cell operation can also be analyzed through its fuel-consumption characteristics.
The simulation displays consumption in forms such as:
Fuel consumption in grams
Fuel-flow-related measurement in LPM
These outputs are useful for evaluating the relationship between EV power demand and fuel-cell hydrogen usage.
Motor-Side Electrical Results
The propulsion converter also provides electrical results such as:
Motor-side line voltage
Phase current
These waveforms help verify the electrical performance of the DC–AC converter supplying the EV propulsion motor.
𝐏𝐨𝐰𝐞𝐫 𝐁𝐚𝐥𝐚𝐧𝐜𝐢𝐧𝐠 𝐑𝐞𝐬𝐮𝐥𝐭
One of the most important outputs is the combined power plot showing:
EV Load Power
Fuel Cell Power
Battery Power
Supercapacitor Power
As the EV demand changes, each energy source responds differently.
The fuel cell provides the major energy contribution, while the battery handles medium-term energy imbalance and the supercapacitor responds to rapid transient conditions.
This demonstrates effective hybrid energy management across different stages of the driving cycle.
𝐑𝐨𝐥𝐞 𝐨𝐟 𝐄𝐚𝐜𝐡 𝐄𝐧𝐞𝐫𝐠𝐲 𝐒𝐨𝐮𝐫𝐜𝐞
Source | Energy Capability | Dynamic Response | Main Role |
Fuel Cell | High | Relatively slower | Main energy supply |
Battery | High | Medium | Energy balancing |
Supercapacitor | Lower | Very fast | Peak/transient power support |
This complementary behavior is one of the major advantages of combining the three sources.
𝐊𝐞𝐲 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬
⚡ Hybrid Fuel Cell–Battery–Supercapacitor EV
🔋 Lithium-ion battery energy storage
⚡ Fast supercapacitor transient compensation
🔄 Bidirectional battery charging and discharging
🧠 State-machine-based energy management
🎯 Battery SOC-based operating-state selection
⚙️ Fuel-cell boost-converter control
🔋 Battery boost and buck converter control
🚗 Drive-cycle-based EV operation
📊 Fuel-cell voltage, current and power monitoring
📊 Battery voltage, current, power and SOC monitoring
📊 Supercapacitor voltage, current and power monitoring
⛽ Fuel-consumption analysis
⚡ Combined source/load power comparison
🔌 DC-link voltage regulation
🖥️ Complete implementation in MATLAB/Simulink
𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬
This simulation is useful for studying:
Fuel-cell electric vehicles
Hybrid electric powertrains
EV energy-management strategies
Hybrid energy-storage systems
Battery SOC management
Supercapacitor power buffering
Bidirectional DC–DC converters
Fuel-cell converter control
EV drive-cycle analysis
DC-link voltage regulation
Power-sharing control
Hydrogen fuel consumption
Electric vehicle propulsion systems
MATLAB/Simulink-based EV research
𝐖𝐡𝐲 𝐔𝐬𝐞 𝐚 𝐅𝐮𝐞𝐥 𝐂𝐞𝐥𝐥, 𝐁𝐚𝐭𝐭𝐞𝐫𝐲 𝐚𝐧𝐝 𝐒𝐮𝐩𝐞𝐫𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐨𝐫?
Using a single energy source can make it difficult to satisfy both the energy requirement and fast power requirement of an EV.
The hybrid arrangement provides a better solution:
Fuel Cell: supplies continuous energy efficiently.
Battery: compensates for changes in average power demand.
Supercapacitor: handles rapid acceleration and deceleration transients.
As a result, the fuel cell and battery do not have to respond alone to every sudden load change.
𝐁𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐨𝐟 𝐭𝐡𝐞 𝐇𝐲𝐛𝐫𝐢𝐝 𝐄𝐕 𝐒𝐲𝐬𝐭𝐞𝐦
Better transient response
Improved power sharing
Controlled battery charging/discharging
Reduced stress on the battery
Reduced rapid fuel-cell power fluctuations
Improved DC-bus stability
Better utilization of available energy sources
Suitable for highly dynamic EV driving conditions
Easy visualization of power flow in MATLAB/Simulink
𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧
The MATLAB simulation of Fuel Cell Battery and Supercapacitor Sourced EV System provides a clear demonstration of hybrid energy management for electric vehicle applications.
The fuel cell acts as the primary source, the battery manages medium-term power variations, and the supercapacitor handles fast transient power demand.
A state-machine-based controller coordinates fuel-cell power using battery SOC and EV load demand, while bidirectional battery converters provide controlled charging and discharging.
Simulation results such as fuel-cell power, battery SOC, supercapacitor power, EV load power, fuel consumption, voltage and current waveforms make the model highly useful for understanding hybrid EV energy management, converter control, and dynamic power sharing in MATLAB/Simulink.
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