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Artificial Intelligence (AI) Load Management Controlled Electric Vehicle Charging System

Overview

The existing power supply of a building may not support a number of EV chargers; or it may not fulfil some client's requirement, such as payment on demand, even though there is a simple load management scheme. Our system incorporated with A.I. can provide a sophisticated load control, while optimizing the demand of end-user in terms of battery charging capacity, and the supply of facility management in terms of energy reserve.

  • Artificial Intelligence (AI) Load Management Controlled Electric Vehicle Charging System 0
  • Artificial Intelligence (AI) Load Management Controlled Electric Vehicle Charging System 1
  • Artificial Intelligence (AI) Load Management Controlled Electric Vehicle Charging System 2
Research completion
2015
Commercialisation opportunities
IP licensing, Collaboration for product development, technology development in various application segments; Product distribution
Problem addressed

Lack of power supply is a common issue for some old buildings, but the residents or tenants are still expecting some EV charging facilities; meanwhile, there is an economic concern for commerical buildings, that is the balance between realtime energy consumption against supply. We, therefore, develop an AI load management system to solve both problems.

Innovation
  • An artificial neural network is used to model the charging system, including power supply, demand of EV charging, user habit, seasonal weather, holiday, etc, then work out a best charging scheme for the system.
  • A high power matrix charging system is developed to cater the battery charging for six EVs simultaneouly.
  • 3-phase automatic changing allows load balancing at client's side, this will not only improve the power quality, but also increase the number of charging point.
Key impact
  • Significantly increase the no. of charging point without upgrading the existing infrastructure
  • Efficiently optimizing the energy utilization
  • Capable of predicting the load condition (i.e. usage of charging system)
Application
  • Electric vehicle
  • EV Charger
  • Load management system
The Hong Kong Polytechnic University (PolyU)

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