Design, Analysis, and Electrification of a Solar-Powered Electric Vehicle
Bibliographic record
Abstract
Nowadays, the automobile industry is moving towards hybridized and fully electric vehicles. The industry has been slowly moving towards this future from decades. Firstly, hybrid and semi-hybrid cars became famous, and now due to the advancements in battery technology, fully electric cars are becoming increasingly popular. Due to the car manufacturers designations, the electric cars have reached the stage of mass production. Many countries such as the U.S., Germany, and France have pledged to reduce the usage of gasoline and diesel cars, and increase the use of electric vehicles due to the diminishing non-renewable resources. In this paper, electrification of an electric vehicle has been performed, in which the solar energy has been used along with the traditional plug-in energy to power the vehicle. The solar energy absorbed from the sun by the solar panel is converted into chemical energy, and stored in batteries. Therefore, the solar-powered electric car can work with an electric motor instead of an Internal Combustion Engine (ICE) to drive the car. Also, the motor can run on AC current which is converted by the inverter from DC current stored in batteries. To drive the car in electric mode, a 360 V Li-polymer battery pack with 100 kWh energy capacity has been proposed to install in the car. Thus, the approach of transforming solar energy into chemical energy, and converting chemical energy to mechanical energy have been applied in this solar-powered electric car. Moreover, the functionality of off-road driving, as well as on-road has been considered. In order to increase/decrease the ground clearance of the car, equipping the car with air suspension system has been investigated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".