Pneumatic Regenerative Braking System for Vehicle
Bibliographic record
Abstract
ABSTRACT\nThroughout the later years there has been an increasing focus on the development of\ntechnologies which can reduce the need for fossil fuel without limiting the yielding capacity.\nCars have a great deal of the focus about the use of oil. With 10% of the world's populations\nowning a car and expectation of the world car park tripled in 20501 it is crucial to limit the use\nof fuel for vehicles. The efficiency improvement of vehicles is how to limit the losing of\nenergy (e.g. braking, idle and external energy demanding utilisation) and especially the loss\nof energy while braking and idling is staked to 40% of the total energy use. Several of these\nhybrid techniques are continuously under development and they "competes" against each\nother with the purpose of limiting the need of fossil fuel and to run a vehicle with best overall\nefficiency. Equal for all hybrid technologies are that they avoid the loss of energy.\nPneumatic hybrid vehicle (PHV) is a technique that could work without adding advanced and\nexpensive materials or components – thereby it would be simpler and cheaper. The option\nto use air as thrust giving fuel has no pollution and letting a compressor inverting brake\nenergy into compressed air stored in air tank - it would be free to run. With automakers\ndownsizing their engines to reduce engine friction, the kinetic regenerated compressed air\nhas better circumstances as thrust giving fuel. To store compressed air and use it in e.g.\nfour-stroked ICE, it won't have any combustion gasses while running on compressed air.\nTherefore, to achieve higher efficiency the engine would have to run as two-stroke. To\ncontrol this, the valve control is a complex matter [4] duo to the shift from combustion and\npneumatic mode. Research by L. Guzella et al.2 has shown fuel improvements up to 35% on\ngasoline engine approximately the same efficiency as electric hybrid but by far less cost and\nless complex technique. By implementing the pneumatic technique in the ICE the interaction\nwould be smooth and less complex and costly as with flywheel, electric and fuel cell -\nthereby improves the driveability for the hybrid vehicle.\nDownsizing improves fuel consumption 12-17%3 and lowers emissions by basically fitting a\nsmaller engine with a turbocharger. A side effect from turbocharged downsized ICE's is\nturbo lag at lower revs. With storage of compressed air, turbo lag can be minimized thus,\ndownsizing and pneumatic hybrid shows promising.\nThe result of pneumatic hybrid is: No external implementation exept pressure tank, made by\neasy recyclable materials as: cast iron and aluminium, low costs.\n1 http://www.fiafoundation.org/50by50/documents/50BY50_report.pdf page 5.\n2 Amir Fazeli, Amir Khajepour, Cecile Devaud. Department of Mechanical and Mechatronic Engineering,\nUniversity of Waterloo, Waterloo, Canada. Applied Energy 88 (2011) 2955-2966\n3 Development of a 4-Cylinder Gasoline Engine with a Variable Flow Turbo-charger" SAE TECHNICAL\nPAPER SERIES 2007-01-0263\nNobuhiro Ito, Tohru Ohta, Ryuji Kono, Satoshi Arikawa and Takaki Matsumoto
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.043 | 0.015 |
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".