Receiver Position Estimation Method for Multitransmitter WPT System Based on Machine Learning

Shen, Huanfeng; Tan, Pingan; Song, Bowen; Gao, Xieping; Zhang, Bo

doi:10.1109/tia.2021.3103489

Cited by 19 publications

(11 citation statements)

References 30 publications

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“…There have been a few proposed approaches to estimate WPT system parameters only from Tx-side measurements [10]- [17], and a brief comparison of these methods is presented in Table 1. These approaches can be broadly classified to analytical methods [10]- [15], hardware-based synchronization approaches [16], [17] and machine learning assisted methods [18], [19].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the characterization of the WPT system using only Tx-side measurements by considering higher-order harmonics still remains an important but unsolved problem. Some machine learning techniques have been employed in recent literature [18], [19] to identify WPT characteristics. In [18], the authors proposed to use online and offline estimation of receiver position by using the knowledge of transmitter coils impedance and optimal activation pattern for known receiver position.…”

Section: Introductionmentioning

confidence: 99%

“…This approach requires to know the transmitter parameters and some known position of receiver beforehand so that it is possible to calculate the impedance. Additionally, the method proposed in [19] calculates the efficiency of the system and feed it in the ML estimators. To know the efficiency of the system, one should calculate/measure the parasitic losses of the inductor and capacitors which can be inaccurate.…”

Section: Introductionmentioning

confidence: 99%

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Machine Learning Assisted Characteristics Prediction for Wireless Power Transfer Systems

2022

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One of the main challenges in wireless power transfer (WPT) devices is performance degradation when the receiver's position and characteristics vary. Therefore, the load resistance and receiver position must be monitored to ensure proper optimization of power transfer. This study proposes a machine learning (ML) assisted method that estimates the power delivered to the receiver by only using measurements at the transmitter side. Based on the delivered power estimation, we also propose a method to identify if the system efficiency is too low, so that the transmitter should be turned off. This activation control method can be useful in multi-transmitter WPT systems. In addition, we propose an ML method to estimate the load resistance and the coupling coefficient. Using the proposed method, the characteristics of an inductorcapacitor-capacitor (LCC)-Series tuned WPT system are successfully predicted only using the measured root-mean-square and the harmonic contents of the input current. The proposed approach is experimentally validated using a laboratory prototype.INDEX TERMS Wireless power transfer, machine learning, coupling strength estimation, load resistance estimation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Machine Learning Assisted Characteristics Prediction for Wireless Power Transfer Systems

2022

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“…For example, an approximate solution for the arrangement of coils to achieve maximum efficiency in a multi-coil coupling system is proposed and experiments have verified its properties . The anti-misalignment performance of the WPT system can be improved with a multi-coil structure Shen et al, 2022). In , a neural network method to model the propagation of magnetic resonance in multiple-input-multiple-output (MIMO) is proposed and used to reduce the impact of the offset problem.…”

Section: Introductionmentioning

confidence: 99%

“…In , a neural network method to model the propagation of magnetic resonance in multiple-input-multiple-output (MIMO) is proposed and used to reduce the impact of the offset problem. Additionally, a receiver position estimation method for multi-transmitter WPT systems using the machine learning method is proposed, and it is verified in an experiment that the system efficiency maintains around 90% even with the misalignment (Shen et al, 2022). Moreover, the geometrical design of the coils has also received attention in recent years.…”

Section: Introductionmentioning

confidence: 99%

Design and optimization of a modular wireless power system based on multiple transmitters and multiple receivers architecture

Liu

Yang²,

Gao

et al. 2022

Front. Energy Res.

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Wireless Power Transfer (WPT) technology has been applied to electric vehicles (EVs), for its convenience, safety, and high reliability. However, for the traditional single-transmitter-single-receiver WPT system, due to its uneven electromagnetic field distribution, the power transfer capability and the anti-offset performance are always insufficient. The multi-transmitter-multi-receiver (MTMR) WPT system based on modular inverters with coils can not only improve the transmission power of the system but also boost the system’s anti-offset ability due to its more uniform magnetic field distribution. In this study, the topology and transmission characteristics of the MTMR WPT system are discussed accordingly: 1) A decoupling method of transmitting coil based on capacitance compensation is proposed, and the particle swarm optimization algorithm is used to derive the optimal design scheme of magnetic coupling coil. 2) A phase-shifting control strategy is proposed to realize the phase synchronization and current sharing control of coil current at each transmitter. Finally, the simulation and experimental results show that the modular wireless power transfer system with multiple transmitters and multiple receivers has strong power transmission capability and anti-offset performance.

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A comprehensive review of wireless power transfer methods, applications, and challenges

Rahman,

Shanto,

Sarker

et al. 2024

Engineering Reports

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Wireless power transfer (WPT) is a promising technology that has the potential to revolutionize the present methods of power transmission. This paper aims to provide an overview of WPT, including its history, a comparative review of methods, and a review of recent papers about WPT. We discussed different methods of WPT, such as inductive power transmission, capacitive power transmission, optical power transmission, and microwave power transmission. The research briefly discusses the applications, challenges, and opportunities of WPT. The study's findings suggest that WPT can serve as a feasible substitute for traditional wired power transmission. This technology has the potential to offer several advantages, including enhanced convenience, decreased expenses, and heightened safety.

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Receiver Position Estimation Method for Multitransmitter WPT System Based on Machine Learning

Cited by 19 publications

References 30 publications

Machine Learning Assisted Characteristics Prediction for Wireless Power Transfer Systems

Machine Learning Assisted Characteristics Prediction for Wireless Power Transfer Systems

Design and optimization of a modular wireless power system based on multiple transmitters and multiple receivers architecture

A comprehensive review of wireless power transfer methods, applications, and challenges

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