A three-phase coil coupling wireless power transfer pad for electric vehicles battery charging systems
Bibliographic record
Abstract
• Analyses the impact of ferrite placement on a three-phase pad with a similar structure. • Examines cross-coupling effects as the coil moves away from the origin. • Compares the introduced coil design with existing three-phase pads of similar structure. • Evaluates the differences and advantages between single-phase and three-phase systems. • Conducts experimental analysis of a 7.7 kW system to validate performance and efficiency. Resonant Inductive Power Transfer (RIPT) is pivotal in advanced Electric Vehicle (EV) charging systems, offering safety, reliability, and automation ease. The magnetic pad design within RIPT-based Wireless Charging Systems (WCS) significantly influences power transfer efficiency. Three-phase magnetic couplers outshine their single-phase counterparts in energy transfer capacity, offering benefits like rotating magnetic flux and reduced ferrite mass. This article analyzes a three-phase magnetic coupler design featuring a circular geometry, characterized by enhanced angular misalignment tolerance, ferrite-friendly structure, and ease of design. Named the "Three Half Circular Coil" (3HCC) pad, it comprises three half-circular coils arranged in a circular pattern. The performance of this design is rigorously analyzed using MATLAB and Ansys Finite Element for a 7.7 kW system. The proposed model is benchmarked against a tripolar coil, a three-phase rectangular coil, and a conventional single-phase circular coil. 7.7 kW experimental models are designed and analyzed to investigate cross-coupling effects as the coil moves away from the origin. This article underscores the critical role of RIPT in EV charging systems, highlights the advantages of three-phase magnetic couplers over single-phase, and showcases the effectiveness of the proposed 3HCC design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".