Sliding-mode energy management strategy for dual-source electric vehicles handling battery rate of change of current
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Bibliographic record
Abstract
For years, developing energy management strategies (EMS) for hybrid energy storage systems (HESS) of electric vehicles (EV) has been a topic of great interest thanks to the mutual support of energy sources. In this paper, we approach the energy management problems from the control point of view to exploit the remarkable advantages of control techniques in treating state constraints, system stability , and optimality . By that, we propose a sliding-mode strategy for the EMS of the battery–supercapacitor HESS on EVs. In order to prolong the lifespan of the battery , the rate of change in battery reference current is directly handled as the control input of the management system which is, to our best knowledge, novel in literature. Control parameters of the proposed EMS are optimally tuned by using Particle Swarm Optimization . The performance of the proposed EMS is validated by off-line simulation as well as real-time experiments on a Signal Hardware-in-the-Loop system with various comparisons, testing scenarios, and quality indices. The results and the approach of the paper illustrate the effectiveness and feasibility of the management system that can be applied not only to EVs but also to larger-scale energy networks in further research.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it