Bibliographic record
Abstract
Recently, mostly due to global warming concerns and high oil prices, electric vehicles have attracted a great deal of interest as an elegant solution to environmental and energy problems. In addition to the fact that electric vehicles have no tailpipe emissions and are more efficient than internal combustion engine vehicles, they represent more versatile platforms on which to apply advanced motion control techniques, since motor torque and speed can be generated and controlled quickly and precisely. \n\tThe chassis control systems developed today are distinguished by the way the individual subsystems work in order to provide vehicle stability and control. However, the optimum driving dynamics can only be achieved when the tire forces on all wheels and in all three directions can be influenced and controlled precisely. This level of control requires that the vehicle is equipped with various chassis control systems that are integrated and networked together. Drive-by-wire electric vehicles with in-wheel motors provide the ideal platform for developing the required control system in such a situation. \n\tThe focus of this thesis is to develop effective control strategies to improve driving dynamics and safety based on the philosophy of individually monitoring and controlling the tire forces on each wheel. A two-passenger electric all-wheel-drive urban vehicle (AUTO21EV) with four direct-drive in-wheel motors and an active steering system is designed and developed in this work. Based on this platform, an advanced fuzzy slip control system, a genetic fuzzy yaw moment controller, an advanced torque vectoring controller, and a genetic fuzzy active steering controller are developed, and the performance and effectiveness of each is evaluated using some standard test maneuvers. Finally, these control systems are integrated with each other by taking advantage of the strengths of each chassis control system and by distributing the required control effort between the in-wheel motors and the active steering system. The performance and effectiveness of the integrated control approach is evaluated and compared to the individual stability control systems, again based on some predefined standard test maneuvers.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".