Neural Network Based Energy Management in Solar PV Powered EV Charging Station | MATLAB/Simulink Model
 
This premium MATLAB/Simulink model demonstrates a complete Solar PV Powered EV Charging Station integrated with Neural Network-based Energy Management, ANFIS MPPT, bidirectional converters, and single-phase grid synchronization. It offers a research-grade framework for EV charging, smart-grid interaction, and hybrid energy coordination.
 
🚗⚡ Product Description
 
This advanced simulation model showcases the full operation of a solar PV-driven EV charging station under varying irradiance and multiple battery SOC levels. The system incorporates:
 
ANFIS-based MPPT for extracting optimal PV power
Bidirectional DC–DC converters for stationary battery and EV battery
Neural Network-based Energy Management System (EMS) for intelligent current reference generation
Single-phase grid integration through inverter + LCL filter
Seamless power flow between PV, stationary battery, EV battery, and the grid
 
The model is ideal for EV system developers, renewable energy engineers, and anyone working on energy management, hybrid microgrids, or smart charging infrastructures.
 
🔧 Key Features
 
✔️ Complete Solar PV EV Charging Architecture
 
2 kW solar PV array
Boost converter with ANFIS MPPT
Standby stationary battery
EV battery subsystem
Grid-tied inverter with LCL filter
 
✔️ Smart Multi-Source Energy Management
 
Neural network EMS inputs: PV power, battery SOC
Generates smooth grid current reference
Enables hybrid PV–battery–grid coordination
 
✔️ Bidirectional Operation
 
Grid import (charging batteries when PV is low)
Grid export (sending excess PV to grid)
Battery charge/discharge control
EV charging throughout all scenarios
 
✔️ Adaptive Control Algorithms
 
ANFIS MPPT for fast MPP detection at changing irradiance
PI controllers for DC bus voltage and converter operation
PLL-based synchronization with single-phase grid
 
✔️ Dynamic Scenario Simulation
 
Three SOC scenarios simulated:
Scenario A – High stationary battery SOC (90%)
EV charging supplied by PV + stationary battery
Grid exports excess power
Scenario B – Medium SOC (40%)
PV + stationary battery supply EV and grid
Grid eventually imports as PV drops
Scenario C – Low SOC (10%)
Both batteries charge
Grid supplies majority of demand
 
📊 What’s Included in the Simulation
PV array with dynamic irradiance profile (200–1000 W/m²)
ANFIS MPPT block
Bidirectional DC–DC converters (EV battery & stationary battery)
Grid-connected inverter with LCL filter
Neural network current reference generator
Complete SOC tracking for both batteries
Grid power flow (import/export) visualization
Dynamic DC bus regulation at 500 V
 
🎯 Performance Highlights
🔹 PV Performance
ANFIS MPPT extracts maximum power across all irradiance levels
Tracks voltage at MPP with minimal error
🔹 Battery Performance
High-SOC battery supports EV charging
Low-SOC battery and EV battery charge via PV + grid
🔹 Grid Interaction
Exports energy when PV > load
Imports during low PV or low SOC
Smooth transitions using Neural Network EMS
🔹 Stability & Control
DC bus regulated around 500 V continuously
Smooth duty-cycle modulation
Synchronized grid current with PLL
 
📁 What You Get
✔️ Complete MATLAB/Simulink model (.slx)
✔️ Complete control subsystem for PV, EV battery, stationary battery, and grid
 
▶️ Video Demonstration
Watch the full simulation demo:
🔗 https://www.youtube.com/watch?v=qADJIEr2nV4