Development and Performance Evaluation of an Autonomous Electric Generator With Automatic Control System

Nigeria faces persistent power challenges, including frequent blackouts and an unreliable electricity supply, leading to a high dependence on conventional fuel-based generators that are expensive to operate, require frequent maintenance, and contribute to environmental pollution. To address these issues, this project focuses on the design and implementation of an autonomous electric generator integrated with an Artificial Neural Network (ANN) control system for optimized electric vehicle (EV) charging. The system comprises a 3HP DC motor, a 3KVA alternator, a 24V battery, and a charging unit, where the DC motor drives the alternator to generate electrical power while the battery supplies the initial startup energy and sustains the system. A rectifier circuit and charge controller regulate the battery’s charging process, ensuring continuous operation. To enhance charging efficiency and power management, an ANN-based control system dynamically optimizes voltage, current, and power distribution, learning from historical data to predict the best charging parameters based on battery state-of-charge (SoC), load demand, and power availability. This intelligent control minimizes power losses, prevents overcharging or deep discharge, and ensures stable power delivery to the EV while maintaining the efficiency of the generator. Performance evaluation was conducted by varying load conditions, monitoring voltage stability, and assessing the EV charging rate compared to conventional charging stations. The results demonstrate that ANN-based optimization significantly improves charging efficiency, reduces energy losses, and extends battery lifespan, making the autonomous generator a viable and intelligent alternative to traditional power solutions. By providing a cost-effective, eco-friendly, and self-sustaining energy source, this project offers a promising solution to Nigeria’s electricity challenges while supporting the transition to sustainable EV adoption.