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A题/AAA常用/AI交互所需文件/论文结构2.md

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+Below is an updated **paper blueprint** that cleanly integrates the three gap patches **without breaking your frozen MODEL_SPEC logic** (except the explicit, minimal power-mapping extension for GPS). I’ll show **(i) where each patch lands**, **(ii) what each section must now contain**, and **(iii) what new data/evidence is required** so the added content is rigorous (not “text-only fluff”).
+
+---
+
+# Updated Paper Blueprint (with GPS + Monte Carlo UQ + Multi-cycle aging)
+
+## Summary Sheet (1 page)
+
+### Logical progression (updated)
+
+1. Model: continuous-time ODE + CPL closure + **extended power mapping including GPS**.
+2. Core outputs: SOC(t), V_term(t), Δ(t), TTE.
+3. Key findings:
+
+   * Baseline TTE
+   * **Navigation/GPS drain impact**
+   * **Uncertainty band** (MC distribution + survival curve)
+   * **TTE degradation across cycles** (aging trajectory)
+4. Recommendations: user + OS + lifecycle-aware battery management.
+
+### Must include (new evidence)
+
+* A **one-line quantification** of GPS impact on TTE (ΔTTE from turning GPS “on” vs “off” in a navigation segment).
+* UQ: mean/CI and at least one survival milestone (e.g., 90% survival time).
+* Aging: a mini table/plot of TTE vs cycle index (e.g., cycles 0, 50, 100, 200).
+
+---
+
+## 1) Introduction and framing
+
+### Logical progression (updated)
+
+* “Unpredictability” arises from time-varying usage and environment; **navigation/location services** are a common drain source.
+* We address both **short-horizon discharge** and **long-horizon degradation**.
+* Outline three analyses:
+
+  1. Mechanistic model with GPS term
+  2. Monte Carlo UQ for stochastic usage
+  3. Multi-cycle aging forecast for TTE decline
+
+### Must include
+
+* Motivation sentence tying GPS to the real-world “navigation drains phone quickly” phenomenon.
+* A roadmap paragraph mapping to sections: baseline → scenario drivers (including GPS) → global sensitivity → UQ → aging forecast → recommendations.
+
+---
+
+## 2) Model overview: states/inputs/outputs/assumptions (minor extension)
+
+### What changes
+
+* Add **one new input**: GPS duty variable (G(t)\in[0,1]).
+  (This is the minimal extension implied by your patch: add (P_{\text{gps}}(G)) to (P_{\text{tot}}).)
+
+### Must include (new items)
+
+* **Table updates**
+
+  * Inputs now include (G(t)) (unitless, [0,1], “GPS duty / navigation intensity”)
+  * Parameters now include (P_{\text{gps},0}), (k_{\text{gps}})
+* Assumption: (G(t)) is an externally specified scenario signal (like (L,C,N,\Psi,T_a)), not a new state.
+
+### Evidence required
+
+* A short justification for treating GPS drain as linear in duty cycle (first-order approximation).
+* A stated range for (P_{\text{gps},0}), (k_{\text{gps}}) (even if “calibrated / assumed”; must be declared).
+
+---
+
+## 3) Governing equations (PATCH P10 + P11)
+
+### 3.1 Power mapping (UPDATED)
+
+#### Logical progression
+
+1. Screen + CPU + Network + background (existing)
+2. **GPS term** added additively
+3. Total power drives CPL current through quadratic closure
+
+#### Must include (specific equations)
+
+* Replace total power line exactly as patch indicates:
+  [
+  P_{\mathrm{tot}}(t)=P_{\mathrm{bg}}+P_{\mathrm{scr}}(L)+P_{\mathrm{cpu}}(C)+P_{\mathrm{net}}(N,\Psi,w)+P_{\mathrm{gps}}(G).
+  ]
+* GPS submodel (BLOCK_A):
+  [
+  P_{\mathrm{gps}}(G) = P_{\mathrm{gps},0}+k_{\mathrm{gps}},G(t).
+  ]
+
+#### Evidence/data required to make this rigorous
+
+* Provide either:
+
+  * (Preferred) a citation/value range from a source (your placeholder [REF-GPS-POWER]) **or**
+  * (If no citation) a **calibration protocol**: “Set (P_{\text{gps},0},k_{\text{gps}}) so that navigation scenario reproduces observed drain factor X,” and report the chosen values.
+
+### 3.2–3.5 Constitutive + CPL + ODEs (unchanged)
+
+* No new dynamics are needed; GPS affects (P_{\text{tot}}) only.
+
+---
+
+## 4) Time-to-Empty (TTE) and event logic (unchanged structure, stronger interpretation)
+
+### Logical progression (unchanged)
+
+* Event functions (g_V,g_z,g_\Delta)
+* earliest crossing via interpolation
+* termination reason recorded
+
+### New content to add (one paragraph)
+
+* Explain how GPS affects TTE *indirectly*:
+
+  * (G(t)\uparrow \Rightarrow P_{\text{tot}}\uparrow \Rightarrow I\uparrow) via CPL, accelerating SOC decay and potentially increasing the risk of Δ collapse / voltage cutoff earlier.
+
+### Evidence required
+
+* A navigation/GPS scenario result showing:
+
+  * higher avg (P_{\text{tot}}), higher max (I), and reduced TTE relative to baseline.
+
+---
+
+## 5) Parameterization and data support (must now include GPS + aging-law parameters)
+
+### Logical progression (expanded)
+
+1. Parameter groups: power mapping, battery ECM, thermal, radio tail
+2. **GPS parameters** included in power mapping
+3. **Aging parameters** (from Section 3.5 SOH law) clearly listed and sourced/assumed
+4. Plausibility checks (energy, bounds, monotonicity)
+
+### Must include (new items)
+
+* GPS parameter table entries: (P_{\text{gps},0},k_{\text{gps}})
+* Aging-law parameter table entries (whatever Section 3.5 uses; must be explicit)
+* Clear labeling:
+
+  * “Measured / literature”
+  * “Calibrated”
+  * “Assumed for demonstration”
+
+### Evidence required
+
+* For aging: at least one **reference point** like “capacity drops to 80% after N cycles” OR cite your [REF-LIION-AGING].
+* If no empirical anchor, you must add a limitation note: aging trajectory is qualitative.
+
+---
+
+## 6) Numerical method and reproducibility (minor add)
+
+### Logical progression
+
+* RK4 nested CPL unchanged.
+* Add that (G(t)) is treated identically to other inputs in scenario function.
+
+### Must include
+
+* Updated trajectory column list to include:
+
+  * (G(t)) and (P_{\text{gps}}(t)) (optional but recommended for clarity)
+* Reproducibility: seed fixed for MC; dt fixed; step-halving.
+
+---
+
+## 7) Baseline results (update: add one GPS/navigation stress baseline)
+
+### Logical progression (updated)
+
+1. Baseline scenario plots and TTE table (existing)
+2. **Navigation with GPS “high duty”** as an extended baseline variant
+3. Compare TTE and identify mechanism (P_tot, I, Δ)
+
+### Must include (new evidence)
+
+* A small 2-row comparison:
+
+  * Baseline (G=0 or low)
+  * Navigation/GPS-active (G high during navigation segment)
+* Plot overlay or table:
+
+  * ΔTTE, avg (P_{\text{tot}}), avg (P_{\text{gps}})
+
+---
+
+## 8) Scenario analysis: drivers of rapid drain (expand the matrix to include GPS)
+
+### Logical progression (updated)
+
+* The scenario matrix should now include a GPS-focused scenario explicitly.
+
+### Must include
+
+* Add scenario like:
+
+  * **S8: “Navigation + GPS high duty”** (or fold into your existing navigation_poor_signal segment by setting G(t)=1 there)
+* Keep the ranking output but ensure GPS is represented in driver comparisons.
+
+### Evidence required
+
+* Quantified ΔTTE for GPS scenario.
+* Mechanistic signature entries include avg (P_{\text{gps}}) and show how it shifts current draw.
+
+---
+
+## 9) Sensitivity analysis (optional: include GPS parameters)
+
+### Logical progression
+
+* Your current Sobol set is fine; but the blueprint should specify a choice:
+
+  * Either keep the 6-parameter set unchanged **or**
+  * Replace the weakest contributor with (k_{\text{gps}}) to test GPS importance.
+
+### Must include (if you include GPS)
+
+* Ranges for (k_{\text{gps}}) and/or (P_{\text{gps},0}) (±20% around baseline).
+* Updated ranking interpretation: whether GPS is a primary driver *in navigation-dominant regimes*.
+
+---
+
+## 10) Uncertainty Quantification (PATCH P12: MC is now required, not optional)
+
+### Logical progression (updated)
+
+10.1 Define uncertainty source (usage variability)
+10.2 Deterministic solver stability/step-halving (existing)
+10.3 **Monte Carlo UQ** (BLOCK_B)
+10.4 Survival curve and uncertainty reporting
+
+### Must include (new “hard” components)
+
+* MC method statement:
+
+  * number of paths (M=300)
+  * perturbation model (OU on L,C,N; optionally also N/Ψ/G if you want)
+  * fixed seed
+* Outputs:
+
+  * mean TTE, CI, p10/p50/p90, survival curve (P(\text{TTE}>t))
+
+### Evidence required
+
+* UQ summary table + survival curve plot/table.
+* A brief comparison: deterministic baseline TTE vs MC mean vs percentile spread (to interpret “unpredictable”).
+
+---
+
+## 11) Multi-cycle aging and lifespan TTE forecasting (PATCH P13)
+
+### Logical progression
+
+1. Explain time-scale separation: discharge seconds vs aging days.
+2. Define outer-loop over cycles (j).
+3. At each cycle: run discharge simulation → compute throughput → update SOH → update (R_0,Q_{\text{eff}}) → next cycle.
+4. Produce TTE degradation trajectory.
+
+### Must include (new evidence)
+
+* A formal algorithm box for the outer loop (BLOCK_C).
+* Define (Q_{\text{thr},j}=\int |I(t)|,dt) and how it drives your SOH update (must reference Section 3.5 law).
+* A plot/table:
+
+  * cycle index (j) vs (S_j) and TTE(_j)
+* Interpretation:
+
+  * explain why TTE declines (capacity loss + resistance increase).
+
+### Evidence required
+
+* Explicit SOH update equation (from your Section 3.5).
+* At least one aging reference anchor (or clearly marked as “illustrative”).
+
+---
+
+## 12) Recommendations (updated: add GPS + lifecycle-aware policy)
+
+### Logical progression
+
+* Convert scenario rankings + Sobol + UQ + aging forecast into actions.
+
+### Must include (new recommendation types)
+
+* **GPS/location service policy**:
+
+  * adaptive duty-cycling, batching location updates, “navigation mode” warnings
+  * quantify expected gain using your GPS scenario ΔTTE
+* **Lifecycle-aware** recommendations:
+
+  * as S declines, OS should lower peak power demands to avoid V_cut/Δ collapse earlier
+  * user guidance: avoid high-drain use in cold/poor signal when battery aged
+
+### Evidence required
+
+* Each recommendation must cite a model result:
+
+  * “This action targets parameter/driver X and yields ΔTTE ≈ Y in scenario tests.”
+
+---
+
+## 13) Validation, limitations, and extensions (expanded)
+
+### Must include (new limitation + validation points)
+
+* GPS model limitation: linear duty approximation; could refine with acquisition bursts.
+* Aging limitation: if no calibrated dataset, trajectory is qualitative.
+* UQ limitation: OU is a stylized model; could use empirical traces.
+
+### Validation evidence (additions)
+
+* Show GPS inclusion doesn’t break:
+
+  * unit checks, Δ feasibility checks, step-halving convergence.
+
+---
+
+# What you should update in your appendix/tables (minimum edits)
+
+1. **Variable table**: add (G(t)).
+2. **Parameter table**: add (P_{\text{gps},0},k_{\text{gps}}) + aging-law parameters.
+3. **Scenario matrix**: add one GPS-heavy scenario (navigation).
+4. **Results**:
+
+   * Baseline + GPS variant TTE comparison
+   * MC summary + survival curve
+   * Multi-cycle TTE vs cycle plot/table
+
+---
+
+If you paste your current section headings (or your LaTeX/Word outline), I can produce a **“diff-style” outline**: exact headings to add/renumber, and exactly which existing paragraphs need one new sentence vs a full new subsection.