Improved models of vehicle differential mechanisms using various approaches
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Bibliographic record
Abstract
The mathematical modelling of the branched automotive drivetrain is mainly based on various configurations of differential mechanisms (DM). This paper proposes variant math approaches for modelling DM's dynamics. The symmetric (open) DM is considered first. Two mathematical methods based on ordinary differential equation (ODE) and differential-algebraic equation (DEA) problems are applied. The asymmetric self-locking inter-axle differential with proportional friction moments is then considered. Three variants of the mathematical models for this DM type are represented. The linearised model uses the shortest description based on a previous step solution. Two other nonlinear models are formed by mixing with ODE and DAE approaches. The Simulink blocks for implementing developments were composed. The models were validated by comparing the results under the same conditions to prove their math coherence. The analysis of the proposed variants was carried out regarding structural complexity, usability, computational speed, and relative accuracy. Conclusions about their usability in drivetrain dynamics and active control were made.
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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) | 0.000 | 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 it