Foreign Object Debris Detection and Automatic Elimination for Autonomous Electric Vehicles Wireless Charging Application

2020 ◽  
Vol 9 (2) ◽  
pp. 93-110
Author(s):  
Aqueel Ahmad ◽  
◽  
Mohammad Saad Alam ◽  
Yasser Rafat ◽  
◽  
...  
Keyword(s):  
Electric Vehicles ◽  
Wireless Charging ◽  
Foreign Object ◽  
Element Analysis ◽  
Power Circuit ◽  
Modeling And Analysis ◽  
Detection Techniques ◽  
Foreign Objects ◽  
Living Objects ◽  
Automatic Elimination

Power pad designing, misalignment reduction, safety, automation, living object detection (LOD), and foreign object debris (FOD) detection are the key challenges in the commercialization of the high voltage wireless charging of Electric Vehicles (EV). The interruption from unwanted and sensitive foreign objects such as metal objects and living objects over the charging pads is an immense challenge for the static wireless charging of EV. In this manuscript, the problem of interference due to foreign objects and living objects has been analyzed, and an innovative laser- and sensor-based FOD detection method is proposed and verified by developing a prototype setup. Modeling and analysis of the effects of foreign objects have been performed using Finite Element Analysis (FEA) in Ansys Maxwell® environment. The analysis compares the consequence of the presence of foreign objects on the wireless charging power pad. The proposed method utilizes laser light and sensor for the detection and two-dimensional signal processing for the elimination of FOD. The proposed method is compatible with all types of static wireless charging systems without interrupting the power transfer and power circuit. The proposed system has been analyzed and compared with the various available FOD detection techniques. The feasibility of the proposed system has been assessed with the help of an on the bench hardware prototype implementation in the lab environment.

Foreign Object Debris Detection and Automatic Elimination for Autonomous EV Wireless Charging Application

2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Aqueel Ahmad ◽  
Mohammad Saad Alam ◽  
Yasser Rafat ◽  
Samir M. Shariff ◽  
Ibrahim S. Al-Saidan ◽  
...  
Keyword(s):  
Wireless Charging ◽  
Foreign Object ◽  
Automatic Elimination

Switch-On Modeling and Analysis of Dynamic Wireless Charging System Used for Electric Vehicles

2016 ◽  
Vol 63 (10) ◽  
pp. 6568-6579 ◽  
Author(s):  
Yanjie Guo ◽  
Lifang Wang ◽  
Qingwei Zhu ◽  
Chenglin Liao ◽  
Fang Li
Keyword(s):  
Electric Vehicles ◽  
Wireless Charging ◽  
Modeling And Analysis ◽  
Charging System

Modeling and analysis of dynamic wireless charging for electric vehicles under different working scenarios

2020 ◽  
pp. 002072092092854
Author(s):  
Ning Wang ◽  
Qingxin Yang ◽  
Hengjun Zhang
Keyword(s):  
Electric Vehicle ◽  
Electric Vehicles ◽  
Storage System ◽  
Energy Storage System ◽  
Wireless Charging ◽  
Wireless Power ◽  
Energy Usage ◽  
Modeling And Analysis ◽  
Vehicle System ◽  
Driving Range

Dynamic wireless charging technology can solve the charging problem of electric vehicle. There is little research on the influence of dynamic wireless charging on electric vehicle. This paper establishes the energy model of the vehicle system by using Advisor and MATLAB. An energy control strategy for dynamic wireless charging of electric vehicles is designed. The influence of dynamic wireless power transfer on energy storage system loss and electric vehicle range under different operating scenarios and different minimum battery charge states is studied. The variation of state of charge, energy usage and the overall system efficiency are compared and analyzed. This paper analyzes the influence of SOC by vehicle parameters and external parameters in dynamic wireless charging, and the influence on electric vehicle driving range further.

scholarly journals Rapid Foreign Object Detection System on Seaweed Using VNIR Hyperspectral Imaging

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5279
Author(s):  
Dong-Hoon Kwak ◽  
Guk-Jin Son ◽  
Mi-Kyung Park ◽  
Young-Duk Kim
Keyword(s):  
Object Detection ◽  
Real Time ◽  
Hyperspectral Imaging ◽  
High Speed ◽  
Detection System ◽  
Imaging Techniques ◽  
Foreign Object ◽  
Subtraction Method ◽  
Foreign Objects ◽  
Time Operation

The consumption of seaweed is increasing year by year worldwide. Therefore, the foreign object inspection of seaweed is becoming increasingly important. Seaweed is mixed with various materials such as laver and sargassum fusiforme. So it has various colors even in the same seaweed. In addition, the surface is uneven and greasy, causing diffuse reflections frequently. For these reasons, it is difficult to detect foreign objects in seaweed, so the accuracy of conventional foreign object detectors used in real manufacturing sites is less than 80%. Supporting real-time inspection should also be considered when inspecting foreign objects. Since seaweed requires mass production, rapid inspection is essential. However, hyperspectral imaging techniques are generally not suitable for high-speed inspection. In this study, we overcome this limitation by using dimensionality reduction and using simplified operations. For accuracy improvement, the proposed algorithm is carried out in 2 stages. Firstly, the subtraction method is used to clearly distinguish seaweed and conveyor belts, and also detect some relatively easy to detect foreign objects. Secondly, a standardization inspection is performed based on the result of the subtraction method. During this process, the proposed scheme adopts simplified and burdenless calculations such as subtraction, division, and one-by-one matching, which achieves both accuracy and low latency performance. In the experiment to evaluate the performance, 60 normal seaweeds and 60 seaweeds containing foreign objects were used, and the accuracy of the proposed algorithm is 95%. Finally, by implementing the proposed algorithm as a foreign object detection platform, it was confirmed that real-time operation in rapid inspection was possible, and the possibility of deployment in real manufacturing sites was confirmed.

scholarly journals Unsupervised Foreign Object Detection Based on Dual-Energy Absorptiometry in the Food Industry

2021 ◽  
Vol 7 (7) ◽  
pp. 104
Author(s):  
Vladyslav Andriiashen ◽  
Robert van Liere ◽  
Tristan van Leeuwen ◽  
Kees Joost Batenburg
Keyword(s):  
Object Detection ◽  
Meat Products ◽  
Food Product ◽  
Processing Technique ◽  
Dual Energy ◽  
Foreign Object ◽  
Metal Debris ◽  
X Ray ◽  
Foreign Objects ◽  
X Ray Imaging

X-ray imaging is a widely used technique for non-destructive inspection of agricultural food products. One application of X-ray imaging is the autonomous, in-line detection of foreign objects in food samples. Examples of such inclusions are bone fragments in meat products, plastic and metal debris in fish, and fruit infestations. This article presents a processing methodology for unsupervised foreign object detection based on dual-energy X-ray absorptiometry (DEXA). A novel thickness correction model is introduced as a pre-processing technique for DEXA data. The aim of the model is to homogenize regions in the image that belong to the food product and to enhance contrast where the foreign object is present. In this way, the segmentation of the foreign object is more robust to noise and lack of contrast. The proposed methodology was applied to a dataset of 488 samples of meat products acquired from a conveyor belt. Approximately 60% of the samples contain foreign objects of different types and sizes, while the rest of the samples are void of foreign objects. The results show that samples without foreign objects are correctly identified in 97% of cases and that the overall accuracy of foreign object detection reaches 95%.

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