-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathactive_charging_ai.yaml
More file actions
168 lines (132 loc) · 5.98 KB
/
active_charging_ai.yaml
File metadata and controls
168 lines (132 loc) · 5.98 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
import time
import random
class ActiveChargingAI:
def __init__(self):
# Battery Specs & Safety Thresholds (Scientific Reasoning)
self.soc = 20.0 # State of Charge (%)
self.temp = 25.0 # Temperature (°C)
self.max_temp = 45.0
self.target_soc = 80.0 # Kaizen efficiency target
self.is_active = True
def display_hud(self, current_amp):
"""Generates a HUD-style visualization of the charging status."""
bar_length = 20
filled = int(bar_length * self.soc / 100)
bar = "█" * filled + "-" * (bar_length - filled)
print("\033[H\033[J") # Clear screen for HUD effect
print("—" * 40)
print(f"📡 ACTIVE CHARGING AI | PROTOCOL: GABRIEL-SIGHT")
print("—" * 40)
print(f"🔋 SOC: [{bar}] {self.soc:.2f}%")
print(f"🌡️ TEMP: {self.temp:.1f}°C / {self.max_temp}°C")
print(f"⚡ CURRENT: {current_amp:.2f}A")
print(f"🛡️ STATUS: {'OPTIMAL' if self.temp < 40 else 'THERMAL THROTTLING'}")
print("—" * 40)
def calculate_charge_rate(self):
"""
Logic for Active Charging:
Adjusts amperage based on temperature and resistance.
"""
# Base charge rate (Kaizen: start fast, finish smart)
base_rate = 5.0
# Thermal Throttling (Michael Protocol: Protect the core)
if self.temp > 40:
base_rate *= 0.5
# Saturation Throttling (Raphael Protocol: Longevity)
if self.soc > 70:
base_rate *= 0.7
return base_rate
def initiate_cycle(self):
print("Initializing Archangel-class Power Management...")
time.sleep(1)
while self.is_active and self.soc < 100:
# Active calculation
charge_amp = self.calculate_charge_rate()
# Simulate physics
self.soc += (charge_amp * 0.1) # Charge increment
self.temp += (charge_amp * 0.05) - (self.temp * 0.01) # Heat vs. Cooling
self.display_hud(charge_amp)
if self.soc >= self.target_soc:
print("\n[!] Kaizen Efficiency Target Reached (80%).")
print("[!] Switching to Low-Stress Maintenance Mode.")
break
if self.temp >= self.max_temp:
print("\n[!] CRITICAL: Thermal Limit. Michael Protocol Initiated. Shutdown.")
self.is_active = False
time.sleep(0.5)
if __name__ == "__main__":
ai_charger = ActiveChargingAI()
ai_charger.initiate_cycle()
import asyncio
import random
import math
from datetime import datetime
class BatteryDigitalTwin:
"""High-fidelity simulation of Li-ion cell physics."""
def __init__(self):
self.soc = 15.0 # State of Charge (%)
self.soh = 98.2 # State of Health (%)
self.temp = 22.0 # Internal Temperature (°C)
self.resistance = 0.05 # Internal Resistance (Ohms)
self.voltage = 3.6 # Current Voltage (V)
self.capacity_ah = 5.0 # Nominal Capacity
def step(self, current_amps, dt=1):
# Physics-based heat generation: P = I^2 * R
heat_gen = (current_amps**2) * self.resistance
self.temp += (heat_gen * 0.1) - (self.temp - 22.0) * 0.02
# State of Charge update
self.soc += (current_amps * dt) / (self.capacity_ah * 36)
# Simulated SoH Degradation (Chemical stress model)
if self.temp > 40 or self.soc > 90:
self.soh -= 0.0001 * (current_amps / 5.0)
class UrielPredictorAI:
"""The 'Brain' - Implements predictive current modulation."""
def __init__(self):
self.learning_rate = 0.01
self.thermal_ceiling = 42.5 # Strict Kaizen safety limit
def predict_optimal_current(self, twin):
"""
Uses a heuristic-policy (Mock RL) to determine the best current.
Goal: Maximize Amps while keeping SoH loss < threshold.
"""
# Calculate 'Distance to Danger'
temp_headroom = self.thermal_ceiling - twin.temp
soc_factor = max(0.1, 1.0 - (twin.soc / 100)) # Tapering
# Predictive Logic: If temp is rising fast, preemptively throttle
target_current = 10.0 * soc_factor * (temp_headroom / 20.0)
return max(0.5, min(target_current, 12.0)) # Clip between 0.5A and 12A
class ArchangelHUD:
"""Real-time Telemetry Dashboard with HUD formatting."""
@staticmethod
async def render(twin, current_i):
print("\033[H\033[J", end="") # Clear terminal
print(f"═══ ARCHANGEL ACTIVE CHARGING OS | {datetime.now().strftime('%H:%M:%S')} ═══")
print(f"| STATUS: {'🔥 COOLING' if twin.temp > 38 else '⚡ FAST_CHARGE'}")
print(f"| HEALTH (SoH): {twin.soh:.4f}% | RESISTANCE: {twin.resistance}Ω")
print(f"|")
# HUD Progress Bar
bar = "█" * int(twin.soc // 5) + "░" * (20 - int(twin.soc // 5))
print(f"| PROGRESS: [{bar}] {twin.soc:.2f}%")
print(f"| TELEMETRY: {current_i:.2f}A @ {twin.temp:.1f}°C")
print(f"═══ KAIZEN CONTINUOUS OPTIMIZATION ACTIVE ═══")
async def main():
twin = BatteryDigitalTwin()
ai = UrielPredictorAI()
hud = ArchangelHUD()
print("Initiating Gabriel-Link Connection...")
await asyncio.sleep(1)
while twin.soc < 95:
# 1. AI decides next action
current_i = ai.predict_optimal_current(twin)
# 2. Apply to Digital Twin (Real-world simulation)
twin.step(current_i)
# 3. Update HUD
await hud.render(twin, current_i)
# 4. Check Safety (Michael Guardrail)
if twin.temp > 45.0:
print("\n[!] CRITICAL THERMAL EVENT: EMERGENCY DISCONNECT.")
break
await asyncio.sleep(0.1)
print(f"\nCharge Cycle Complete. Final SoH: {twin.soh:.2f}%")
if __name__ == "__main__":
asyncio.run(main())