Davis Meike

Enhanced approach for energy-efficient trajectory generation of industrial robots

This paper proposes a novel cost function formulation for minimization of the energy consumption of industrial robots by trajectory optimization. Besides the dynamics of the robot including friction losses, the model especially takes into account the losses of servo drives and inverters. Furthermore, the ability of energy exchange between the robot axes via the coupled DC-bus is included, since the servo drives support generator mode during deceleration. The utilized energy-based robot model is applicable to different manipulator types. For the energy-efficient motion planning, point-to-point trajectories are defined by B-spline functions. The given nonlinear optimization problem is solved using gradient-based methods, considering kinematic and dynamic constraints. Several simulation results are presented, demonstrating the intense effect of energy exchange in the robot controllers power electronics. Furthermore, a comparative study is given showing that the proposed method is able to outperform existing torque-based approaches.

AREUS — Innovative hardware and software for sustainable industrial robotics

Industrial Robotics (IR) may be envisaged as the key technology to keep the manufacturing industry at the leading edge. Unfortunately, at the current state-of-the-art, IR is intrinsically energy intensive, thus compromising factories sustainability in terms of ecological footprint and economic costs. Within this scenario, this paper presents a new framework called AREUS, focusing on eco-design, eco-programming and Life Cycle Assessment (LCA) of robotized factories. The objective is to overcome current IR energetic limitations by providing a set of integrated technologies and engineering platforms. In particular, novel energy-saving hardware is firstly introduced, which aim at exchanging/storing/recovering energy at factory level. In parallel, innovative engineering methods and software tools for energy-focused simulation are developed, as well as energy-optimal scheduling of multi-robot stations. At last, LCA methods are briefly described, which are capable to assess both environmental and economic costs, linked to the flows of Material, Energy and Waste (MEW). A selected list of industrially-driven demonstration case studies is finally presented, along with future directions of improvement.

Power smoothing approach within industrial DC microgrid with supercapacitor storage for robotic manufacturing application

This research paper cover optimization process a converting conventional AC supply system towards DC based industrial power distribution system with supercapacitor storage based power balancing functionality. Electrical power consumption reference data is based on 4 industrial robot manufacturing area with automotive industry specific production processes and respective electrical load examples. Improvement in energy efficiency by interconnection and energy exchange process of production equipment as well as peak loading reduction on supplying AC power grid infrastructure is demonstrated.

Power converter for DC bus sharing to increase the energy efficiency in drive systems

It is state of the art for many drive systems like those used in industrial robotics, conveyor systems or diverse numerical control machinery to have a common DC bus power system architecture. Due to regenerative braking, the DC bus voltage increases until a certain limit, which is limited means of a balancing resistor (brake chopper). Systems that require rapid cyclic starts and stops are subject to significant energy waste due to extensive use of the brake chopper. In this article, a novel power converter for drive systems is proposed that allows the brake chopper to be omitted and enables the exchange of regenerative energy among multiple drive systems within an independent DC subgrid with one centralized energy storage element. The solution does not require identical hardware or exact synchronization between the drive rectifiers, therefore it is applicable to both existing and new production equipment alike. Experimental results in industrial robot drives show savings of up to 20%.

Energy consumption modeling within the virtual commissioning tool chain

In this paper an energy modeling approach within the virtual commissioning tool chain is presented. Virtual commissioning (VCom) today is a de facto methodology for programmable logic controller (PLC) software design and validation for automatic production systems. Energy consumption has never been an optimization criterion in VCom. Concepts of energy consumption modeling for any production unit have been investigated for measuring, visualization and optimization of control strategies. The hardware-in-the-loop simulation includes logical behavior models, the respective energy models and 3D-kinematic models of the production units, which are connected over common industrial bus network with a hardware-PLC. The concept has been developed for use with commercially available software tools so that the research results are implementation-oriented. An example from the automotive industry has been used.

On designing optimal trajectories for servo-actuated mechanisms through highly detailed virtual prototypes

Servo-actuated mechanisms are increasingly substituting fully mechanical drives in order to increase flexibility and reconfigurability of modern automatic machines. The overall servomechanism performance, especially in the case of high-dynamic motions, is the direct consequence of several interacting factors, namely electric motor and linkage dynamics, controller efficacy, and requested motion law. In particular, Point-To-Point (PTP) trajectories are usually designed in order to comply with technological constraints, imposed by the required interaction with the handled product, and to maximize some optimality criterion such as, for instance, energy efficiency or limited actuation torques. In this context, the present paper proposes a novel method for generating either energy-optimal or torque-optimal PTP motions described by piecewise fifth-order polynomials. The optimization cost functions are based on a virtual prototype of the system, which comprises behavioral models of power converter, controller and electric motor coupled with the mechanical system. Results are then compared with experimental data obtained on a physical prototype. The comparison quantitatively shows that better-behaved PTP trajectories can be designed by including the dynamic contribution of each sub-system component.