Digitally Controlled Misalignment-Tolerant Inductive Power Transfer System with Adaptive Hybrid Compensation for CC/CV Charging of E-Scooter
Bibliographic record
Abstract
This paper presents a digitally controlled Inductive power transfer (IPT) system for charging Electric scooters (E-scooters), utilising an adaptive hybrid compensation network design. This system ensures constant current (CC) and constant voltage (CV) charging, with misalignment. It leverages the advantages of double-sided inductor-capacitor-capacitor (DS-LCC) and LCC-series (LCC-S) topologies, which respectively provide CC and CV output. A Type-II digital anti-windup PI control method with a selectable compensation network is introduced, allowing both CC and CV modes to operate with zero voltage switching (ZVS) under misalignment conditions. This approach reduces system losses and enhances the stability and efficiency of the IPT system. A 270W/85-kHz IPT-based E-scooter charger was designed and simulated in the MATLAB/Simulink environment, and an experimental prototype was developed to evaluate the performance of the proposed charger as per SAE J2954 standards. Testing under three different coupling conditions perfect alignment, 5 cm misalignment, and 10 cm misalignment demonstrated that the output parameters remained constant across all conditions, confirming the effectiveness of the proposed control technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".