Randomized trial demonstrates enhanced routing efficiency and cost savings in electric vehicle charging management, indicating significant benefits for urban transport systems.
Key Points
The aim is to optimize electric vehicle routing and charging by minimizing travel distance and costs while maximizing photovoltaic energy usage.
Developed a hybrid model combining Ant Colony Optimization and Non-dominated Sorting Genetic Algorithm II.
Implemented as a Flask application with real-time communication via MQTT.
Validated in five driving scenarios across urban, suburban, and highway routes in Morocco.
Reduced travel distance by 7-10% compared to A* algorithm.
Lowered energy consumption by 10-15% compared to A*.
Achieved a reduction in charging costs by 30-40% with high renewable energy utilization (≈70-98%).