scholarly journals Energy Consumption Modeling of 4D Printing Thermal-responsive Polymers with Integrated Compositional Design for Material

2020 ◽  
Vol 34 ◽  
pp. 101223
Author(s):  
Muyue Han ◽  
Yiran Yang ◽  
Lin Li
Keyword(s):  
Energy Consumption ◽  
4D Printing ◽  
Responsive Polymers ◽  
Compositional Design ◽  
Energy Consumption Modeling

scholarly journals Practical Model for Energy Consumption Analysis of Omnidirectional Mobile Robot

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1800
Author(s):  
Linfei Hou ◽  
Fengyu Zhou ◽  
Kiwan Kim ◽  
Liang Zhang
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Mobile Robot ◽  
Load Capacity ◽  
Working Environment ◽  
Energy Consumption Analysis ◽  
Mecanum Wheel ◽  
Save Energy ◽  
Energy Consumption Modeling ◽  
Robot Platform

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.

scholarly journals Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling

2019 ◽  
Vol 10 (2) ◽  
pp. 22 ◽  
Author(s):  
Siriorn Pitanuwat ◽  
Hirofumi Aoki ◽  
Satoru IIzuka ◽  
Takayuki Morikawa
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Traction Force ◽  
Hybrid Vehicles ◽  
Specific Power ◽  
Mode Transition ◽  
Hybrid Powertrain ◽  
Modeling Methods ◽  
Consumption Model ◽  
Energy Consumption Modeling

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.

scholarly journals Energy Consumption Modeling and Analyses in Automotive Manufacturing Plant

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Lujia Feng ◽  
Laine Mears
Keyword(s):  
Energy Consumption ◽  
Energy Modeling ◽  
Manufacturing Plant ◽  
Automotive Manufacturing ◽  
Manufacturing Plants ◽  
Modeling Approach ◽  
Paint Spray ◽  
World Energy ◽  
Spray Booth ◽  
Energy Consumption Modeling

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.

scholarly journals Refined Node Energy Consumption Modeling in a LoRaWAN Network

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6398
Author(s):  
Sébastien Maudet ◽  
Guillaume Andrieux ◽  
Romain Chevillon ◽  
Jean-François Diouris
Keyword(s):  
Energy Consumption ◽  
Collision Probability ◽  
Maintenance Cost ◽  
Important Research Topic ◽  
Energy Consumption Model ◽  
Probability Of Collision ◽  
Consumption Model ◽  
Improved Model ◽  
Energy Consumption Modeling

LPWAN technologies such as LoRa are widely used for the deployment of IoT applications, in particular for use cases requiring wide coverage and low energy consumption. To minimize the maintenance cost, which can become significant when the number of sensors deployed is large, it is essential to optimize the lifetime of nodes, which remains an important research topic. For this reason, it is necessary that it is based on a fine energy consumption model. Unfortunately, many existing consumption models do not take into account the specifications of the LoRaWAN protocol. In this paper, a refined energy consumption model based on in-situ measurements is provided for a LoRaWAN node. This improved model takes into account the number of nodes in the network, the collision probability that depends on the density of sensors, and the number of retransmissions. Results show the influence of the number of nodes in a LoRaWAN network on the energy consumption of a node and demonstrate that the number of sensors that can be integrated into a LoRaWAN network is limited due to the probability of collision.

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