Dynamic Charging Scheduling Optimization for Electric Vehicles Based on Quantum SWARM Algorithm
- Resource Type
- Conference
- Authors
- Zhang, Guoyu; Dai, Mian; Zhao, Shuai; Zhao, Pengchao
- Source
- 2022 7th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS) Intelligent Robot Systems (ACIRS), 2022 7th Asia-Pacific Conference on. :154-157 Jul, 2022
- Subject
- Robotics and Control Systems
Planing
Heuristic algorithms
Roads
Charging stations
Dynamic scheduling
Real-time systems
Resource management
charging schedule
electric vehicles
quantum SWARM algorithm
autonomous driving
- Language
A dynamic scheduling method based on Quantum SWARM is proposed for electric vehicles charging in the relative disordered traffic environment. It aims to maximum the overall charging efficiency considering the realistic individual competition and group collaboration. The result of the simulation validation shows that for 100 random target power-anxiety clients, Quantum SWARM algorithm could iterate in 1 step with reduction of error comparison around 87%, which could provide a guaranteed optimal allocation planing for charging station, and a derived control logic for swarm intelligent agents such as autonomous electric vehicles.