Simulation Based Trajectory Analysis for the Tilt Controlled High Speed Narrow Track Three Wheeler Vehicle
Bibliographic record
Abstract
Small sized three wheeler electric vehicles (EVs) are gaining popularity in many developing countries because of its low cost operation and excellent manoeuvrability. However, usage of such a 3Ws usage is limited to low speed application such as last mile public transport. Vehicles with such configuration are not well accepted for personal mobility. If the safe speed of such a vehicles are improved, such a vehicles can also become viable to personal transport. Active tilt control (ATC) systems are seen as one of the possible solution to improve safe speed of narrow track 3Ws.Literature indicates that many attempts have been made for establishing active tilt control system on 3W vehicles for enhancing stability of ATC vehicles and promising results were obtained. This paper presents simulation based analysis of the ATC 3W electric vehicle. This work is part of full scale experimental prototype development for the narrow track ATC 3W vehicle with one wheel in front configuration. The primarily focus of this work is to address vehicle dynamics and trajectory related issue of the tilting 3Ws. A multi-body model of ATC 3W vehicle using single track lateral dynamic model with nonlinear tire characteristics was prepared in SimMechanics. The lateral dynamic outputs in terms of the trajectory followed by vehicle were compared for the constant steering inputs given to non-tilting vehicle, tilting vehicle with direct tilt control (DTC) system and tilting vehicle with Steering direct tilt control (SDTC) system. Two critical driving scenarios of U-turn and Lane change manoeuvre are analyzed. It is observed from the results that there is certain trade-off in selecting a tilt actuator and controller so as to minimize the jerks in the perceived acceleration due to high gain and minimize the tilt angle error to ensure proper stability improvement. It is also identified that the controller must be tuned to the predictable trajectory control, in addition to the main task of reducing the load transfer across the rear wheel axle. The model presented in the paper is used to understand the performance of DTC and SDTC control strategies during potentially dangerous manoeuvres. The desired path following ability of the vehicle is the main measures considered for the analysis.
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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".