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PV Battery powered SRM motor based electric Vehicle in MATLAB

PV Battery powered SRM motor based electric Vehicle in MATLAB


In this article, we explore a simulation model that illustrates the functioning of a solar photovoltaic (PV) battery-powered electric vehicle equipped with a Switched Reluctance Motor (SRM). This simulation demonstrates the integration of renewable energy sources, power management, and the control of an electric vehicle propulsion system.

Key Components of the Simulation Model

Solar PV System: The simulation model features a solar PV system that generates electrical power from sunlight. The PV system is connected to a common DC bus via a boost converter. The goal is to harness maximum power from the PV panels efficiently. To achieve this, the simulation employs an Incremental Conductance Maximum Power Point Tracking (MPPT) algorithm.

Incremental Conductance MPPT Algorithm: This algorithm continuously adjusts the duty cycle of the boost converter based on PV voltage and current. It involves parameters like initial duty cycle, maximum duty cycle, minimum duty cycle, and a step change in duty cycle. The algorithm aims to keep the PV system operating at its maximum power point by tracking changes in voltage and current.

  1. Battery System: A 240-volt battery with a rated capacity of 48 Ah is integrated into the system. The battery plays a crucial role in storing excess energy from the PV system and supplying power to the electric vehicle when needed. The battery's state of charge is initially set at 50%.

  2. Electric Vehicle with SRM Motor: The electric vehicle is equipped with an 8-volt SRM motor. The SRM motor operates under the control of a converter, which adjusts its speed and power output. The simulation includes a load profile for the vehicle, representing various driving conditions.

  • Speed Control: The SRM motor's speed is controlled using a reference speed profile, which simulates acceleration, constant speed, and deceleration phases. A PI controller adjusts the motor's current reference based on the speed error.

  • Power Management: The power balance in the system is maintained by the battery, which either charges or discharges depending on the PV power output. This ensures a continuous supply of power to the electric vehicle, allowing it to follow the speed profile.

Simulation Results and Insights

  1. PV Power Generation: The simulation demonstrates how the PV system generates power dynamically based on changing irradiation levels. The Incremental Conductance MPPT algorithm efficiently tracks these changes and extracts maximum power.

  2. Battery Operation: The battery's state of charge varies as it alternates between charging and discharging modes. When the PV system generates surplus power, the battery charges. When the PV power decreases, the battery discharges to provide power to the vehicle.

  3. Electric Vehicle Propulsion: The SRM motor responds to the speed reference profile, providing the necessary torque and power to propel the electric vehicle. The motor's speed closely follows the reference speed.

  4. Power Balance: The simulation illustrates how the system maintains a power balance. When the PV system produces excess power, it charges the battery. Conversely, when PV power is insufficient, the battery supplies power to the vehicle, ensuring a smooth and continuous operation.


The simulation model showcased in this article demonstrates the efficient integration of solar PV power, battery energy storage, and an SRM motor in an electric vehicle. This technology holds promise for sustainable transportation solutions, reducing reliance on fossil fuels and minimizing environmental impact.

The combination of an MPPT algorithm, battery management, and motor control ensures that the electric vehicle operates optimally under varying conditions. This simulation provides valuable insights into the potential of solar PV battery-powered electric vehicles with SRM motors and their role in clean and green transportation.

As the world shifts toward sustainable energy solutions, such simulations pave the way for innovative developments in electric vehicle technology, making eco-friendly transportation more accessible and efficient.

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