ANN-based algorithm for estimation and compensation of lateral misalignment in dynamic wireless power transfer systems for EV charging
Abstract
In this paper, an Artificial Neural Network (ANN) is employed for the estimation of LaTeral Misalignment (LTM) as well as compensation of its effect on Dynamic Wireless Power Transfer (DWPT) systems for Electric Vehicles (EVs) charging. In a DWPT system, energy efficiency and energy transfer capability are significantly affected by the degree of LTM. Therefore, the real-time estimation of LTM, followed by certain remedial actions, could result in higher energy efficiency and energy transfer capability of the system. To this aim, an ANN-based algorithm is proposed to estimate the LTM value. The controller samples the DC-link current and based on the changes in the current profile and the vehicle speed, the ANN estimates the LTM value. Finally, the controller sets a modified reference value for the primary coil current which compensates the reduction in energy transfer capability caused by LTM. Using the suggested method, without any extra equipment in the DWPT system, the expected value of transferred energy is increased by 32%. The proposed ANN is trained for 9 different speeds in the range of 10 to 50 km/h and 11 different degrees of LTM in the range from 0 to 60%. The inputs to the proposed ANN are the DC-link current, the integral of DC-link current, and the vehicle speed.
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ML methods have been applied to battery energy management and to detect faults and lateral misalignment in wireless charging of EVs.
“ML methods have also been applied to battery energy management (for example charge estimation [330] or optimization in hybrid EVs [15]), and to detect faults and lateral misalignment in wireless charging of EVs [780].”
From Tackling climate change with machine learning (2023) · cites this paper as [780]
Cites
Development of a Single-Sided Flux Magnetic Coupler for Electric Vehicle IPT Charging Systems
Budhia, M., Boys, J. T., Covic, G. A., & Huang, C.-Y. (2011) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2011.2179274 · Cited by 1,278 · see citing works
Modern Trends in Inductive Power Transfer for Transportation Applications
Covic, G. A., & Boys, J. T. (2013) · IEEE Journal of Emerging and Selected Topics in Power Electronics · doi:10.1109/jestpe.2013.2264473 · Cited by 1,263 · see citing works
A Double-Sided LCC Compensation Network and Its Tuning Method for Wireless Power Transfer
Li, S., Li, W., Deng, J., Nguyen, T. D., & Mi, C. C. (2014) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2014.2347006 · Cited by 1,093 · see citing works
Design and Optimization of Circular Magnetic Structures for Lumped Inductive Power Transfer Systems
Budhia, M., Covic, G. A., & Boys, J. T. (2011) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2011.2143730 · Cited by 1,042 · see citing works
Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective
Bose, B. K. (2007) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2006.888683 · Cited by 523 · see citing works
A High Efficiency 5 kW Inductive Charger for EVs Using Dual Side Control
Wu, H. H., Gilchrist, A., Sealy, K., & Bronson, D. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2192283 · Cited by 516 · see citing works
Velocity Predictors for Predictive Energy Management in Hybrid Electric Vehicles
Sun, C., Hu, X., Moura, S. J., & Sun, F. (2014) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2014.2359176 · Cited by 515 · see citing works
Analysis and Design of an LCL-T Resonant Converter as a Constant-Current Power Supply
Borage, M., Tiwari, S., & Kotaiah, S. (2005) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2005.858729 · Cited by 273 · see citing works
Modeling and Control of Series–Series Compensated Inductive Power Transfer System
Zahid, Z. U., Dalala, Z. M., Zheng, C., et al. (2014) · IEEE Journal of Emerging and Selected Topics in Power Electronics · doi:10.1109/jestpe.2014.2327959 · Cited by 238 · see citing works
An Efficiency Optimization Scheme for Bidirectional Inductive Power Transfer Systems
Nguyen, B. X., Vilathgamuwa, D. M., Foo, G. H. B., et al. (2014) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2014.2379676 · Cited by 231 · see citing works
An Approximate Dynamic Model of LCL- $T$ -Based Inductive Power Transfer Power Supplies
Hao, H., Covic, G. A., & Boys, J. T. (2014) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2013.2293138 · Cited by 209 · see citing works
A Direct AC–AC Converter for Inductive Power-Transfer Systems
Li, H. L., Hu, A. P., & Covic, G. A. (2011) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2011.2159397 · Cited by 189 · see citing works
Capacity Fade Estimation in Electric Vehicle Li-Ion Batteries Using Artificial Neural Networks
Hussein, A. A.-H. (2014) · IEEE Transactions on Industry Applications · doi:10.1109/tia.2014.2365152 · Cited by 176 · see citing works
Innovative 5-m-Off-Distance Inductive Power Transfer Systems With Optimally Shaped Dipole Coils
Park, C., Lee, S., Cho, G., et al. (2014) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2014.2310232 · Cited by 148 · see citing works
A voltage balancing strategy with extended operating region for cascaded H-bridge converters
Moosavi, M., Farivar, G. G., Iman‐Eini, H., et al. (2013) · IEEE Transactions on Power Electronics · doi:10.1109/tpel.2013.2286270 · Cited by 134 · see citing works
Single-Stage Three-Phase AC–AC Matrix Converter for Inductive Power Transfer Systems
Moghaddami, M., Anzalchi, A., & Sarwat, A. I. (2016) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2016.2563408 · Cited by 84 · see citing works
Moosavi, S. S., Djerdir, A., Ait‐Amirat, Y., Khaburi, D. A., & N’Diaye, A. (2015) · IET Electrical Systems in Transportation · doi:10.1049/iet-est.2014.0055 · Cited by 52 · see citing works
Hasan, N., Wang, H., Saha, T., et al. (2015) · IEEE Energy Conversion Congress and Exposition (ECCE) · doi:10.1109/ecce.2015.7309742 · Cited by 43 · see citing works
Design of a dual-loop controller for in-motion wireless charging of an electric bus
Tavakoli, R., Jovičić, A., Niranjan, C., et al. (2016) · IEEE Energy Conversion Congress and Exposition (ECCE) · doi:10.1109/ecce.2016.7855021 · Cited by 23 · see citing works
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Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
Azad, A. N., Echols, A., Kulyukin, V. A., Zane, R., & Pantic, Z. (2019) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2018.2870339 · Cited by 125 · see citing works
Self-citation
- Authors
- Tavakoli, R., & Pantic, Z.
- Affiliations
- Utah State University (US)
- Venue
- 2017 IEEE Energy Conversion Congress and Exposition (ECCE)
- Publisher
- IEEE
- Published
- 2017-10
- Pages
- 2602-2609
- OpenAlex
- W2768102478
- Cited by
- 21
- References
- 19
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 3 · 2021: 3 · 2019: 1 · 2018: 2
- FWCI
- 1.16
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Energy Conversion Congress and Exposition (ECCE) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Wireless Power Transfer Systems
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced DC-DC Converters
- Physical Sciences › Engineering › Mechanical Engineering › Induction Heating and Inverter Technology
- Keywords
- dynamic wireless power transfer, misalignment compensation, electric vehicle charging, artificial neural networks, DC link current, vehicle speed, energy efficiency
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