The project aims in designing a computationally efficient energy management approach based on a model predictive control (MPC) framework is proposed to obtain the optimal torque split and gearshift for a parallel Hybrid electric vehicles. This study aims to develop and implement a computationally efficient energy management strategy (EMS) for Hybrid Electric Vehicles (HEVs). The EMS plays a crucial role in determining how power is split between the internal combustion engine (ICE) and the electric motor to optimize fuel consumption, battery life, and emissions. This work explores rule-based and optimization-based control strategies, emphasizing low-complexity algorithms that are suitable for real-time implementation in embedded automotive systems. The system was designed such that the energy management of multiple engine motors for Hybrid Electric vehicle using wireless communication modules. This project demonstrates a dual-MOSFET control system using a potentiometer input received via serial communication. The system is built on the Arduino Nano platform and features a 16x2 LCD display for real-time feedback. A single potentiometer value, transmitted from another microcontroller over serial (via SoftwareSerial), is used to proportionally control two MOSFETs representing an engine (EM) and a motor (MO) based on predefined percentage ranges:

• 0–30%: EM is controlled from 0–255 PWM, MO remains off.
• 30–60%: EM decreases from 255–0, MO increases from 0–180 PWM.
• 60–100%: EM turns off, MO increases from 180–255 PWM.

The LCD displays the mapped velocity and power percentage on the first row, and the current status of EM and MO on the second row (e.g., "ENG CONNECTED", "MOT CONNECTED"). The project showcases smooth transition control using a single input source and efficient serial communication between microcontrollers, useful in electric vehicle hybrid systems or automation applications. The controller unit forms the intellectual part of the device. The future works include giving intelligence to the whole system like if any of the motor senses any fault, the whole system will shutdown.    

The major building blocks of this project are:

1. Adapter Power Supply.
2. Arduino Nano.
3. Potentiometer.
4. LCD with driver.
5. Wireless communication modules
6. MOSFET with drivers
7. DC motors with driver.
8. LED indicators.

    Software’s used:

1. Embedded C programming.
2. Arduino ide programmer for dumping code into Micro controller.
3. Express SCH for Circuit design.

      Block Diagram:

             

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