saltylab-firmware/jetson/docs/power-budget.md

Jetson Orin Nano Super Power Budget Analysis

Self-Balancing Robot — 25W Envelope

Last updated: 2026-02-28 Target: Operate within 25W SoC power envelope (MAXN 25W mode)

---

Power Modes

Jetson Orin Nano Super supports multiple NVPModel power modes:

Mode	ID	CPU	GPU	TDP
MAXN	0	6× A78AE @ 1.5GHz	1024-core Ampere	25W
15W	1	6× A78AE @ 1.2GHz	1024-core Ampere	15W
10W	2	4× A78AE @ 1.2GHz	1024-core Ampere	10W
7W	3	4× A78AE @ 0.8GHz	1024-core Ampere	7W

For this robot, we target MAXN 25W mode — a significant upgrade from the previous Nano 10W budget.

# Check current mode
sudo nvpmodel -q

# Set 25W MAXN mode
sudo nvpmodel -m 0

# Set 15W mode (thermal / battery save)
sudo nvpmodel -m 1

# Monitor power in real time
sudo tegrastats
# or via jtop
sudo jtop

---

Component Power Budget

SoC (Jetson Orin Nano Super Module)

Component	Idle (W)	Load (W)	Peak (W)	Notes
CPU (6× A78AE)	1.5	6.0	8.0	ROS2, SLAM, Nav2
GPU (1024-core Ampere)	0.8	5.0	7.0	Depth processing, DNN inference
LPDDR5 RAM (8GB)	0.4	0.8	1.0
NVMe SSD (M.2)	0.2	0.5	0.8	Map storage, rosbags
Video encoder / ISP	0.0	1.5	2.5	4× IMX219 ISP processing
SoC Subtotal	2.9	13.8	19.3

Peripherals

Peripheral	Idle (W)	Active (W)	Peak (W)	Interface	Notes
RealSense D435i	0.3	1.5	3.5	USB 3.1	Peak during boot/init
RPLIDAR A1M8	0.4	2.6	3.0	USB (UART adapter)	Motor spinning
ESP32-S3 bridge	0.0	0.0	0.0	USB Serial (CH343)	Self-powered from robot 5V
Peripheral Subtotal	0.9	6.1	8.9

Total System (from Jetson 5V barrel jack)

Scenario	SoC (W)	Peripherals (W)	Total (W)	Margin vs 25W
Idle	2.9	0.9	3.8	+21.2W
Nominal (SLAM + cameras)	13.8	6.1	19.9	+5.1W ✅
Peak (DNN + all sensors)	19.3	8.9	28.2	-3.2W ⚠️

---

Budget Analysis vs Previous Platform

Metric	Jetson Orin Nano Super	Jetson Orin Nano Super
TDP	10W	25W
CPU	4× Cortex-A57 @ 1.43GHz	6× A78AE @ 1.5GHz
GPU	128-core Maxwell	1024-core Ampere
RAM	4GB LPDDR4	8GB LPDDR5
AI TOPS	~0.5	67
Nominal load	11.4W (over budget)	19.9W (5W headroom)
Cameras	0 CSI	4× IMX219 CSI
Storage	microSD	NVMe M.2

The Orin Nano Super has 2.5× more thermal headroom at nominal load. No aggressive power-gating needed for normal operation.

---

Power Compliance Strategy

Nominal Operation (SLAM + cameras) — ✅ Within 25W

At 19.9W nominal, we have 5W headroom. No mitigation required for normal robot operation.

Peak Operation (DNN inference) — ⚠️ Briefly exceeds 25W

When running DNN inference (e.g., object detection) simultaneously with full sensor suite:

Mitigation 1: Thermal throttling (automatic) The Orin's DVFS will automatically throttle CPU/GPU when temperature exceeds threshold. No explicit action needed — the Orin handles this gracefully.

Mitigation 2: Switch to 15W mode during high-load phases

sudo nvpmodel -m 1   # 15W mode: reduces peak to ~22W
sudo nvpmodel -m 0   # return to MAXN when cooling

Mitigation 3: RPLIDAR motor gating Stop RPLIDAR motor between scan cycles: saves ~2.2W average. Handled automatically by rplidar_ros driver via DTR line control.

Mitigation 4: Camera resolution reduction For compute-heavy phases, drop from 640×480 to 424×240 per camera: saves ~0.6W.

---

CSI Camera Bandwidth

4× IMX219 cameras at 640×480@30fps:

Parameter	Value
Per-camera raw bandwidth	640×480×30×10bpp = 92.16 Mb/s
Total 4 cameras	~369 Mb/s
MIPI CSI-2 capacity (Orin)	40 Gb/s total (2× 4-lane)
ISP processing overhead	~1.5W (all 4 cameras active)

CSI bandwidth is well within capacity. The Orin Nano Super's ISP handles 4 cameras simultaneously.

---

Input Power Requirements

Jetson Orin Nano Super Power Input

Spec	Value
Input connector	5.5mm / 2.5mm barrel jack
Input voltage	5V DC
Recommended current	≥6A (30W supply for headroom)
Absolute max	5.25V

Use a 5V 6A supply minimum. A 4A supply may brownout under DNN peak load.

Robot Power Architecture (Recommended)

LiPo 4S (16.8V max)
       │
       ├─► DC-DC Buck → 5V 6A ──► Jetson Orin barrel jack (30W)
       │   (e.g., XL4016E1)
       │
       ├─► DC-DC Buck → 5V 3A ──► ESP32-S3 + logic 5V rail       │
       └─► Hoverboard ESC ──► Hub motors (48V loop)

Using a 4S LiPo (vs 3S previously) gives better efficiency for the 5V buck converter at Orin's higher power draw.

---

Real-Time Monitoring

# Live power telemetry (tegrastats)
sudo tegrastats --interval 500

# Key fields:
# POM_5V_IN X/Y   — total input power (current mW / average mW)
# POM_5V_GPU X/Y  — GPU power
# POM_5V_CPU X/Y  — CPU power

# Interactive monitoring (jtop — recommended)
sudo pip3 install jetson-stats
sudo jtop

# Log power to file
sudo tegrastats --interval 1000 --logfile /tmp/power_log.txt &

# Parse log
grep "POM_5V_IN" /tmp/power_log.txt | \
  awk '{for(i=1;i<=NF;i++) if($i=="POM_5V_IN") print $(i+1)}' | \
  awk -F'/' '{sum+=$1; count++} END {print "Avg:", sum/count/1000, "W"}'

---

Summary

Metric	Value
Target envelope	25W (MAXN)
Nominal (SLAM + 4 cameras)	~19.9W
Peak (DNN inference)	~28.2W (briefly)
Compliant scenario	All sensors + SLAM (no DNN)
Recommended PSU	5V 6A (30W)
Power mode	nvpmodel MAXN (Mode 0)
Upgrade from Nano	+150% TDP, +13,300% AI TOPS