Smart Charging Standards for Plug-In Electric Vehicles
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">This paper is the fifth in the series of documents designed to identify the progress on the SAE Plug-in Electric Vehicle (PEV) communication task force that follows 2010-01-0837, 2011-01-0866, 2012-01-1036 and 2013-01-1475.</div><div class="htmlview paragraph">The primary focus of this paper is to discuss the most recent revision of J2847/1 [<span class="xref">1</span>], which deals with Smart Charging applications, plus the initial release of J2847/3 [<span class="xref">2</span>], which can be thought of as dealing with “Smart Discharging” applications. Both documents are based on the use of the Smart Energy Profile 2.0 (SEP2) Application Protocol Standard (V1.0) which was completed by the ZigBee Alliance in April 2013. The standard was then accepted by the IEEE and subsequently released as IEEE 2030.5 [<span class="xref">3</span>].</div><div class="htmlview paragraph">SEP2 started with a Marketing Requirements Document (MRD) that J2836/1™ [<span class="xref">4</span>]expanded for the automotive Use Cases for Smart Charging, The MRD was then used to generate the SEP2 Technical Requirements Document (TRD) that set the automotive requirements in J2931/1 [<span class="xref">5</span>]. The TRD was used to generate a SEP2 Application Spec where the specific automotive sequence diagrams, signals and messages are contained in J2847/1. From the SAE progression, J2836/1™ Use Cases set the requirements for the signals and messages in J2847/1. J2836/3™ [<span class="xref">6</span>] contains the Distributed Energy Resource (DER) Use Cases for J2847/3 signals and messages, and J2931/1 contains the protocol requirements for all the SAE Plug-in Electric Vehicle communication documents.</div></div>
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".