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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. [ABSTRACT FROM AUTHOR]

With the emergence of Industry 4.0 in intralogistics, the need for flexible material handling solutions is increasing. While conventional conveyor systems are often too inflexible to meet changing requirements. Automated guided vehicles offer an answer, additional solutions are required for companies relying on already busy and crowded shop floors. This paper presents a concept for a periphery-free electrified monorail system (PEMS) that enables flexible material transport with minimal floor requirements. The PEMS is based on classic electrified monorail technology, and requires no additional peripheral devices within the rail system. Installation and maintenance costs are kept to a minimum through simplified branching elements and a battery-powered energy supply for the vehicles. The modular design of the rail elements further allows transport on standardized Euro-pallets. Moreover, a taxonomy for evaluating the passivity of branching elements of electrified monorail systems is introduced. The functionality of the PEMS was validated by conducting real experiments using a prototype, The results show that the PEMS provides high flexibility in terms of layout design and usage, allowing for fast adaption to the changing requirements of intralogistics. [ABSTRACT FROM AUTHOR]

Due to the growing number of automated guided vehicles (AGVs) in use in industry, as well as the increasing demand for limited raw materials, such as lithium for electric vehicles (EV), a more sustainable solution for mobile energy storage in AGVs is being sought. This paper presents a dual energy storage system (DESS) concept, based on a combination of an electrical (supercapacitors) and an electro-chemical energy storage system (battery), used separately depending on the required transport distance. Each energy storage unit (ESU) in this DESS is capable of supplying the AGV completely. The concept takes into account requirements for a complex material flow as well as minimizing the energy storage capacity required for the operation of the AGV. An energy flow analysis is performed and further used as a basis to derive three possible circuit concepts for the technical realization. The circuit concepts are compared to other approaches from related work, differentiating the functionality to hybrid energy storage systems (HESS). The functionality of the concepts was validated by mapping the energy flow states to active circuit components. Finally, an approach for implementing the control strategy as a state machine is given, and conclusions for further investigations are drawn. [ABSTRACT FROM AUTHOR]