# 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.

```bash
# 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 |
| STM32F722 bridge | 0.0 | 0.0 | 0.0 | USB CDC | Self-powered from robot 5V |
| 4× IMX219 cameras | 0.2 | 2.0 | 2.4 | MIPI CSI-2 | ~0.5W per camera active |
| **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 Nano | 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**
```bash
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 ──► STM32 + 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

```bash
# 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 |
