Neuro-fuzzy energy management system in elevator drive applications for maximum braking energy regenerative capability

In this presentation, an energy management system based on an adaptive neuro-fuzzy control technique is developed, that is applied to an elevator motor drive with regenerative capability of the braking energy. The aim of the developed energy management system is to adjust the elevator acceleration/deceleration rate and speed in order to maximize the regenerative capability of the motor drive and therefore to increase the efficiency of the whole elevator system. The braking energy can be temporarily stored in a battery or supercapacitor bank during the generator operation of the elevator machine and it can be recovered when the elevator machine turns to motoring operation. The energy management system is implemented through an adaptive neuro-fuzzy controller that adjusts the acceleration/deceleration and rotational speed of the motor according to a fuzzy rule set governed by the travel distance of the elevator and the load. In this work, supercapacitors are used for energy storage; however, a battery can be used as well. Several simulation results are presented in order to verify the effectiveness of the developed energy management system and demonstrate the resulting operational improvements.