Concurrent energy efficiency optimization of multi-axis positioning tasks

Positioning tasks of multi-axis servo drive mechanisms typically lead to high energy demands, especially if lossy operating points are applied and/or recuperated break energy, e. g. during deceleration phases, is not effectively reused. A trajectory optimization approach based on the particle swarm algorithm is presented for the adaption of multi-axis positioning tasks during system run-time. Established path planning methods (including the possibility of minimum time motion) are applied, that are adapted by only two parameters per axis and positioning task. In this manner, idle-times that often exist between the motion cycles and/or energy exchange via coupled inverter DC-links are utilized to reduce energy demands and improve system efficiency. In contrast to existing offline trajectory optimization procedures, the method is able to adapt changing motion tasks during system run-time within only few movement cycles. Experimental results prove that, depending on the use case and the chosen optimization constraints, energy losses are effectively reduced, brake chopper dissipation often is even completely avoidable and, hence, total energy demands are distinctly reduced. The approach is applicable to different multi-axis configurations and enables to considerable energy savings without additional hardware invest.