Energy Requirement Modeling for Automated Guided Vehicles Considering Material Flow and Layout Data

Abstract

Saving energy and resources has become increasingly important for industrial applications. Foremost, this requires knowledge about the energy requirement. For this purpose, this paper presents a state-based energy requirement model for mobile robots, e.g., automated guided vehicles or autonomous mobile robots, that determines the energy requirement by integrating the linearized power requirement parameters within each system state of the vehicle. The model and their respective system states were verified using a qualitative process analysis of 25 mobile robots from different manufacturers and validated by comparing simulated data with experimental data. For this purpose, power consumption measurements over 461 operating hours were performed in experiments with two different industrial mobile robots. System components of a mobile robot, which require energy, were classified and their power consumptions were measured individually. The parameters in the study consist of vehicle speed, load-handling duration, load, utilization, material flow and layout data, and charging infrastructure system frequency, yet these varied throughout the experiments. Validation of the model through real experiments shows that, in a 99% confidence interval, the relative deviation in the modeled power requirement for a small-scale vehicle is [−1.86%,−1.14%], whereas, for a mid-scale vehicle, it is [−0.73%,−0.31%]. This sets a benchmark for modeling the energy requirement of mobile robots with multiple influencing factors, allowing for an accurate estimation of the energy requirement of mobile robots.