MétaCan
Menu
Back to cohort
Record W7093301836 · doi:10.17632/562fxrn7js

Citroen C Zero Traction Currents

2025· dataset· W7093301836 on OpenAlexaff

Bibliographic record

VenueMendeley Data · 2025
Typedataset
Language
FieldEngineering
TopicElectric and Hybrid Vehicle Technologies
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsTraction motorTraction (geology)VoltageAccelerationOscilloscopeAmplitudeInverterRangingBattery (electricity)

Abstract

fetched live from OpenAlex

This research investigates the characteristics of traction currents of a Citroën C-Zero. The battery pack consists of 88 cells connected in series with a nominal cell capacity of 50Ah. We characterized the amplitude variations, the frequency content, and temporal patterns of traction currents during six driving scenarios: 1. Parking mode: Vehicle stationary with auxiliary systems active 2. Acceleration: High acceleration from standstill to approximately 50km/h 3. Regenerative braking: Controlled deceleration from approximately 50km/h to standstill 4. Constant velocity: Steady--state driving at approximately 25km/h 5. Urban driving: Moderate acceleration and deceleration patterns 6. Dynamic driving: High-performance driving with rapid acceleration and deceleration A Hioki 3275 current clamp, featuring a bandwidth of 2MHz, was connected to the high-voltage cable near to the traction inverter input to record the current. The output signal from the current clamp was measured using a PicoScope 5444D oscilloscope at sample frequencies ranging from 50kHz to 20MHz. Positive currents indicate battery discharge (acceleration), while negative currents represent battery charge (recuperation). Battery-powered traction applications convert electrical energy into mechanical energy for propulsion, e.g. electric vehicles (EVs). A critical component of this systems is the traction inverter, which converts the dc battery voltage into an ac control signal, generating the rotating magnetic field into the electric motor. In EVs, traction inverters operate at switching frequencies ranging from 5 to 20kHz. The frequency of the electric motor control signal depends on the velocity of the EV. As the velocity increases, the motor's mechanical rotational frequency also increases, requiring a higher motor control frequency. Short-time Fourier transform (STFT) analysis revealed the temporal evolution of electrical frequencies below 1 kHz, corresponding to motor control signals that vary with vehicle velocity. The fundamental pulse width modulation (PWM) switching frequency was identified at 7.1 kHz, with associated harmonics and intermodulation products clearly visible in the frequency spectra. For detailed information about data structure, experimental protocols, and data processing methodologies, refer to the README.md file included with the dataset.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.117
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0060.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.299
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMendeley DataSame topicElectric and Hybrid Vehicle TechnologiesFrench-language works237,207