scholarly journals Energy Consumption Modeling of a Turning Table and Standardized Integration into Virtual Commissioning

2017 ◽  
Vol 11 ◽  
pp. 256-264 ◽  
Author(s):  
Dominik Hauf ◽  
Julian Kruck ◽  
Paryanto ◽  
Jörg Franke
Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang

The four-wheeled Mecanum robot is widely used in various industries due to its maneuverability and strong load capacity, which is suitable for performing precise transportation tasks in a narrow environment. While the Mecanum wheel robot has mobility, it also consumes more energy than ordinary robots. The power consumed by the Mecanum wheel mobile robot varies enormously depending on their operating regimes and environments. Therefore, only knowing the working environment of the robot and the accurate power consumption model can we accurately predict the power consumption of the robot. In order to increase the applicable scenarios of energy consumption modeling for Mecanum wheel robots and improve the accuracy of energy consumption modeling, this paper focuses on various factors that affect the energy consumption of the Mecanum wheel robot, such as motor temperature, terrain, the center of gravity position, etc. The model is derived from the kinematic and kinetic model combined with electrical engineering and energy flow principles. The model has been simulated in MATLAB and experimentally validated with the four-wheeled Mecanum robot platform in our lab. Experimental results show that the accuracy of the model reached 95%. The results of energy consumption modeling can help robots save energy by helping them to perform rational path planning and task planning.


2019 ◽  
Vol 10 (2) ◽  
pp. 22 ◽  
Author(s):  
Siriorn Pitanuwat ◽  
Hirofumi Aoki ◽  
Satoru IIzuka ◽  
Takayuki Morikawa

In the transportation sector, the fuel consumption model is a fundamental tool for vehicles’ energy consumption and emission analysis. Over the past decades, vehicle-specific power (VSP) has been enormously adopted in a number of studies to estimate vehicles’ instantaneous driving power. Then, the relationship between the driving power and fuel consumption is established as a fuel consumption model based on statistical approaches. This study proposes a new methodology to improve the conventional energy consumption modeling methods for hybrid vehicles. The content is organized into a two-paper series. Part I captures the driving power equation development and the coefficient calibration for a specific vehicle model or fleet. Part II focuses on hybrid vehicles’ energy consumption modeling, and utilizes the equation obtained in Part I to estimate the driving power. Also, this paper has discovered that driving power is not the only primary factor that influences hybrid vehicles’ energy consumption. This study introduces a new approach by applying the fundamental of hybrid powertrain operation to reduce the errors and drawbacks of the conventional modeling methods. This study employs a new driving power estimation equation calibrated for the third generation Toyota Prius from Part I. Then, the Traction Force-Speed Based Fuel Consumption Model (TFS model) is proposed. The combination of these two processes provides a significant improvement in fuel consumption prediction error compared to the conventional VSP prediction method. The absolute maximum error was reduced from 57% to 23%, and more than 90% of the predictions fell inside the 95% confidential interval. These validation results were conducted based on real-world driving data. Furthermore, the results show that the proposed model captures the efficiency variation of the hybrid powertrain well due to the multi-operation mode transition throughout the variation of the driving conditions. This study also provides a supporting analysis indicating that the driving mode transition in hybrid vehicles significantly affects the energy consumption. Thus, it is necessary to consider these unique characteristics to the modeling process.


2017 ◽  
Vol 871 ◽  
pp. 36-43 ◽  
Author(s):  
Elisabeth Zizler ◽  
Matthias Wenk ◽  
Benedikt Bräutigam

This paper presents a method to support the development of energy management concepts for machine and plant construction. The energy management concepts are required to put the plant components into an energy saving mode during unproductive phases. These concepts then have to be implemented in the control software. Different dependencies in the production and process flow have to be considered when developing the concepts. Due to the complexity of production plants, a supporting simulation tool is planned to be implemented. With the aid of this tool, different energy management concepts and their derived control software can already be validated virtually in the planning and development phase. This presents an energetic extension of the so-called virtual commissioning concept. Conventional virtual commissioning involves only the process operation functionality in a virtual simulation model of the plant. Now, however, energetic functionalities are assigned to the different model components. Thus, a simulation of the energy consumption in different operation modes can be created for each component. Energy management concepts can only be developed if the components’ energy consumption is known in the different scenarios.


Author(s):  
Lujia Feng ◽  
Laine Mears

Manufacturing plants energy consumption accounts for a large share in world energy usage. Energy consumption modeling and analyses are widely studied to understand how and where the energy is used inside of the plants. However, a systematic energy modeling approach is seldom studied to describe the holistic energy in the plants. Especially using layers of models to share information and guide the next step modeling is rarely studied. In this paper, a manufacturing system temporal and organizational framework was used to guide the systematic energy modeling approach. Various levels of models were established and tested in an automotive manufacturing plant to illustrate how the approach can be implemented. A detail paint spray booth air unit was described to demonstrate how to investigate the most sensitive variables in affecting energy consumption. While considering the current plant metering status, the proposed approach is advanced in information sharing and improvement suggestion determination.


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