CONTROL STRATEGY DEVELOPMENT FOR INDEPENDENT WHEEL TORQUE DISTRIBUTION FOR MULTI-WHEELED COMBAT VEHICLE
Bibliographic record
Abstract
Multi-wheeled combat vehicles behavior depends not only on the available totaldriving torque but also on its distribution among the drive axles/wheels. In turn, thisdistribution is largely regulated by the drivetrain layout and its torque distributiondevices.In this paper, a multi-wheeled (8x4) combat vehicle bicycle model has beendeveloped and used to obtain the desired yaw rate and lateral acceleration tobecome reference for the design of the controllers. PID controllers were designed asupper and lower layers of the controllers. The upper controller develops thecorrective yaw moment, which is the input to the lower controller to manage theindependent torque distribution (torque vectoring) among the driving wheels. Severalsimulation maneuvers have been performed at different vehicle speeds usingMatlab/ Simulink-TruckSim to investigate the proposed torque vectoring controlstrategy. The simulation results with the proposed controller showed a significantimprovement over conventional driveline, especially at severe maneuvers.
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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) | 0.000 | 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 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".