A Driver Guidance System to Support the Stationary Wireless Charging of Electric Vehicles

Nejad, Bijan Shahbaz; Roch, Peter; Handte, Marcus; Marrón, Pedro José

doi:10.1007/978-3-030-64559-5_25

Cited by 6 publications

(6 citation statements)

References 15 publications

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“…Some of the solutions related to pricing and billing, as well as communication and FOD, have been previously discussed in Sections 2.7 and 3.4, respectively. Another paper that explores a guidance system for static charging systems [113] presents a prototype that uses a phone app to display the routing and alignment information.…”

Section: Other Practical Perspectivesmentioning

confidence: 99%

Wireless Charging for Electric Vehicles: A Survey and Comprehensive Guide

Rabih,

Takruri,

Al-Hattab

et al. 2024

WEVJ

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This study compiles, reviews, and discusses the relevant history, present status, and growing trends in wireless electric vehicle charging. Various reported concepts, technologies, and available literature are discussed in this paper. The literature can be divided into two main groups: those that discuss the technical aspects and those that discuss the operations and systems involved in wireless electric vehicle charging systems. There may be an overlap of discussion in some studies. However, there is no single study that combines all the relevant topics into a guide for researchers, policymakers, and government entities. With the growing interest in wireless charging in the electric vehicle industry, this study aims to promote efforts to realize wireless power transfer in electric vehicles.

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Section: Other Practical Perspectivesmentioning

confidence: 99%

Wireless Charging for Electric Vehicles: A Survey and Comprehensive Guide

Rabih,

Takruri,

Al-Hattab

et al. 2024

WEVJ

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“…Since wireless charging requires a precise alignment of the transmitter and receiver coil, we designed a camerabased driver guidance system that assists the driver to precisely maneuver the vehicle to the charging zone. The driver guidance system, which we describe more detailed in another article [55], is composed of mobile and stationary components. Figure 1 illustrates the charging station and camera-based positioning system.…”

Section: Application Contextmentioning

confidence: 99%

“…In this section, we give an overview of foreign object detection techniques in the context of wireless charging, which typically rely on field characteristics [20], sensors [59] or system parameters [30]. While cameras are less expensive than many other sensor types, they are also used to position electric vehicles before initiating the charging process [18,55]. Thus, charging systems could increase their safety by incorporating the existing cameras for foreign object detection.…”

Section: Related Workmentioning

confidence: 99%

“…Cameras are less expensive than many other sensor types and can be used for various tasks such as image classification [39] and object detection [70] using computer vision algorithms. Positioning systems can include a single camera that observes the transmitting coil as well as the surrounding area [55]. Charging stations incorporating the aforementioned type of positioning system could cost-effectively increase their safety by utilizing the existing positioning camera for foreign object detection instead of integrating additional sensors.…”

Section: Computer Visionmentioning

confidence: 99%

“…There are several techniques to reduce misalignment of charging components, such as mechanical [26], RFID [38], or wireless sensor-based methods [47]. Furthermore, there are camera-based positioning systems that rely on a camera integrated into the vehicle [28] or statically attached to the charging station [55].…”

Section: Introductionmentioning

confidence: 99%

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A visual foreign object detection system for wireless charging of electric vehicles

Shahbaz Nejad,

Roch,

Handte

et al. 2024

Machine Vision and Applications

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Wireless charging of electric vehicles can be achieved by installing a transmitter coil into the ground and a receiver coil at the underbody of a vehicle. In order to charge efficiently, accurate alignment of the charging components must be accomplished, which can be achieved with a camera-based positioning system. Due to an air gap between both charging components, foreign objects can interfere with the charging process and pose potential hazards to the environment. Various foreign object detection systems have been developed with the motivation to increase the safety of wireless charging. In this paper, we propose a foreign object detection technique that utilizes the integrated camera of an embedded positioning system. Due to operation in an outdoor environment, we cannot determine the types of objects that may occur in advance. Accordingly, our approach achieves object-type independence by learning the features of the charging surface, to then classify anomalous regions as foreign objects. To examine the capability of detecting foreign objects, we evaluate our approach by conducting experiments with images depicting known and unknown object types. For the experiments, we use an image dataset recorded by a positioning camera of an operating wireless charging station in an outdoor environment, which we published alongside our research. As a benchmark system, we employ YOLOv8 (Jocher et al. in Ultralytics YOLO, 2023), a state-of-the-art neural network that has been used in various contexts for foreign object detection. While we acknowledge the performance of YOLOv8 for known object types, our approach achieves up to 18% higher precision and 46% higher detection success for unknown objects.

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