Development of Real-Time Digital twin model of Autonomous Field Robot for Prediction of Vehicle Stability

2021 ◽  
Vol 27 (3) ◽  
pp. 190-196
Author(s):  
Jong-Boo Han ◽  
Sung-Soo Kim ◽  
Ha-Jun Song
Keyword(s):  
Real Time ◽  
Vehicle Stability ◽  
Digital Twin ◽  
Twin Model ◽  
Field Robot

scholarly journals Construction of Intelligent Integrated Model Framework for the Workshop Manufacturing System Via Digital Twin

2021 ◽  
Author(s):  
Zhongyu Zhang ◽  
Zhenjie Zhu ◽  
Jinsheng Zhang ◽  
Jingkun Wang
Keyword(s):  
Real Time ◽  
Production System ◽  
Manufacturing System ◽  
System Optimization ◽  
Production Cycle ◽  
Model Framework ◽  
The Real ◽  
Digital Twin ◽  
Twin Model ◽  
Information Layer

Abstract With the drastic development of the globally advanced manufacturing industry, transition of the original production pattern from traditional industries to advanced intelligence is completed with the least delay possible, which are still facing new challenges. Because the timeliness, stability and reliability of them is significantly restricted due to lack of the real-time communication. Therefore, an intelligent workshop manufacturing system model framework based on digital twin is proposed in this paper, driving the deep inform integration among the physical entity, data collection, and information decision-making. The conceptual and obscure of the traditional digital twin is refined, optimized, and upgraded on the basis of the four-dimension collaborative model thinking. A refined nine-layer intelligent digital twin model framework is established. Firstly, the physical evaluation is refined into entity layer, auxiliary layer and interface layer, scientifically managing the physical resources as well as the operation and maintenance of the instrument, and coordinating the overall system. Secondly, dividing the data evaluation into the data layer and the processing layer can greatly improve the flexible response-ability and ensure the synchronization of the real-time data. Finally, the system evaluation is subdivided into information layer, algorithm layer, scheduling layer, and functional layer, developing flexible manufacturing plan more reasonably, shortening production cycle, and reducing logistics cost. Simultaneously, combining SLP and artificial bee colony are applied to investigate the production system optimization of the textile workshop. The results indicate that the production efficiency of the optimized production system is increased by 34.46%.

Real Time Prediction of Li-Ion Battery Pack Temperatures in EV Vehicles

2020 ◽  
Author(s):  
Azita Soleymani ◽  
William Maltz
Keyword(s):  
Real Time ◽  
Heat Generation ◽  
Equivalent Circuit Model ◽  
Battery Pack ◽  
Generation Rate ◽  
Li Ion Battery ◽  
Heat Generation Rate ◽  
Digital Twin ◽  
Twin Model ◽  
Li Ion

Abstract A semi-analytical digital twin model of a 90 kW.h li-ion battery pack was developed to capture thermal behavior of the pack in a real-time environment. The solution uses reduced-order models that minimize compute cost/time yet are accurate in predicting real-world operation. The real-time heat generation rate in the battery pack is calculated using 2RC equivalent circuit model. A series of HPPC tests were conducted to calibrate the equivalent circuit model in order to accurately calculate heat generation rate as a function of SOC, temperature, current, charge/discharge mode and pulse duration. In the paper, live-sensor data was integrated into the digital twin system level model of the battery pack to create a real-time environment. The generated tool was utilized to monitor the real-time temperature of the battery pack remotely and have a predictive maintenance solution. The model results for heat generation rate, terminal voltage, and temperature were found to be consistent with the test data across a wide range of conditions. The generated model was used to accelerate battery pack design and development by enabling the evaluation of design feasibility and to conduct in-depth root causes analyses for various inputs and operating conditions, including initial SOC, temperature, coolant flow rate, different charge and discharge profiles. The resulting digital twin model provides additional data that cannot be measured offering the EV industry an opportunity to improve its safety record.

scholarly journals Energy Consumption Prediction of Electric Vehicles Based on Digital Twin Technology

2021 ◽  
Vol 12 (4) ◽  
pp. 160
Author(s):  
Zhaolong Zhang ◽  
Yuan Zou ◽  
Teng Zhou ◽  
Xudong Zhang ◽  
Zhifeng Xu
Keyword(s):  
Energy Consumption ◽  
Real Time ◽  
Electric Vehicle ◽  
Digital Twin ◽  
Twin Model ◽  
Consumption Data ◽  
Energy Consumption Model ◽  
Energy Consumption Prediction ◽  
Consumption Prediction ◽  
Monitoring Platform

Digital twinning technology originated in the field of aerospace. The real-time and bidirectional feature of data interaction guarantees its advantages of high accuracy, real-time performance and scalability. In this paper the digital twin technology was introduced to electric vehicle energy consumption research. First, an energy consumption model of an electric vehicle of BAIC BJEV was established, then the model was optimized and verified through the energy consumption data of the drum test. Based on the data of the vehicle real-time monitoring platform, a digital twin model was built, and it was trained and updated by daily new data. Eventually it can be used to predict and verify the data of vehicle. In this way the prediction of energy consumption of vehicles can be achieved.

scholarly journals Process Modelling of Geothermal Drilling System Using Digital Twin for Real-Time Monitoring and Control

Designs ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 45 ◽  
Author(s):  
Nahashon O. Osinde ◽  
Jean B. Byiringiro ◽  
Michael M. Gichane ◽  
Hasan Smajic
Keyword(s):  
Real Time ◽  
Energy Demand ◽  
Assembly System ◽  
Monitoring And Control ◽  
Real Time Monitoring ◽  
Drilling Tool ◽  
Digital Twin ◽  
Twin Model ◽  
Study Results ◽  
Geothermal Drilling

Currently, Kenya supplies its energy demand predominantly through hydroelectric power, which fluctuates due to poor and unpredictable rainfall in particular years. Geothermal energy is proposed as a clean and reliable energy source in meeting Kenya’s increasing energy demand. During geothermal drilling operations, disruptions due to tool wear and breakages increases the cost of operation significantly. Some of these causes can be mitigated by real-time monitoring of the tool head during operations. This paper presents the design and implementation of a digital twin model of a drilling tool head, represented as a section of a mechatronic assembly system. The system was modelled in Siemens NX and programmed via the TIA portal using S7 1200 PLC. The digital model was programmed to exactly match the operations of the physical system using OPC (open platform communications) standards. These operations were verified through the motion study by simultaneous running of the assembly system and digital twin model. The study results substantiate that a digital twin model of a geothermal drilling operation can closely mimic the physical operation.

scholarly journals Development of a Digital Twin Model for Real-Time Assessment of Collision Hazards

2020 ◽  
Author(s):  
Messi Leonardo ◽  
Naticchia Berardo ◽  
Carbonari Alessandro ◽  
Ridolfi Luigi ◽  
Di Giuda Giuseppe Martino
Keyword(s):  
Real Time ◽  
Digital Twin ◽  
Twin Model ◽  
Time Assessment

scholarly journals Digital Twin: Origin to Future

2021 ◽  
Vol 4 (2) ◽  
pp. 36
Author(s):  
Maulshree Singh ◽  
Evert Fuenmayor ◽  
Eoin Hinchy ◽  
Yuansong Qiao ◽  
Niall Murray ◽  
...  
Keyword(s):  
Real Time ◽  
Remote Access ◽  
Physical Entity ◽  
Industrial Systems ◽  
Digital Twin ◽  
Planning Optimization ◽  
Different Types ◽  
Pros And Cons ◽  
Number Of Publications ◽  
Digital Shadow

Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

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