Modeling and Simulation of a Series Parallel Hybrid Electric Vehicle Using REVS
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper discusses a simulation and modeling package developed at University of Manitoba, REVS: renewable energy vehicle simulator. REVS assists in detail studies of hybrid electric vehicles (HEV) and plug in HEV (PHEV) configurations or energy management strategies through visual programming by creating components as hierarchical subsystems. REVS is composed of detailed models of seven major types of components: electric motors, internal combustion engines, batteries, chemical reactions, fuzzy control strategies, renewable energy resources and support components that can be integrated to model and simulate hybrid drive trains in different configurations. REVS was developed in the Matlab/Simulink graphical simulation language as well as IDEAS package and is portable to most computer platforms. A series parallel hybrid electric vehicle (HEV) with a conventional internal combustion engine (ICE) and a power split device have been designed using the simulation package. Fuzzy controllers have been developed to track the desired vehicle velocity and manage the energy flow of the vehicle. Simulation results of the energy management system and dynamic responses of the system are discussed for proposed vehicle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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 it