Success Case

Ultra-Low-Power Wireless Design for 10+ Year Battery Life

Ultra-Low-Power Wireless Design for 10+ Year Battery Life缩略图

Introduction

With industrial IoT deployments requiring 15+ year operational lifetimes (2024 McKinsey analysis), traditional wireless approaches fail to meet critical benchmarks:

  • 90% of power often wasted in idle states
  • Radio consumes 70% of total system energy
  • Mesh networks cut range by 40% while doubling power

Briltech’s RF lab tested 18 protocol stacks to identify these breakthrough strategies.


Section 1: Protocol Optimization Strategies

1.1 Sub-GHz vs. BLE Energy Tradeoffs

Parameter868MHz LoRa2.4GHz BLE 5.2
TX Current (@0dBm)14mA5.3mA
RX Current8mA4.2mA
Range (Urban)2.3km120m
Air Time (100B)450ms2.5ms

Case Study: Water meter using our hybrid protocol:

  • 3.2μA average current (1 report/hour)
  • Calculated 27-year lifespan on 2xAA batteries

1.2 Advanced Sleep Scheduling

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Optimal Wakeup Intervals:  
Environmental Monitoring: 60-300s  
Asset Tracking: 15-30min  
Predictive Maintenance: 1x/week  

Section 2: Hardware-Level Power Reduction

2.1 Radio Frontend Optimization

  • Low-loss RF switches (0.3dB insertion loss)
  • Adaptive output power (0-20dBm in 1dB steps)
  • DC-DC bypass during TX bursts

Briltech Reference Design:

void tx_power_management() {  
  if (link_quality > 20dB) {  
    set_power(max(0, last_rssi + 5dB));  
  }  
}  

2.2 Antenna Efficiency Improvements

Antenna TypeEfficiencySizeCost
PCB Trace35-50%Compact$
Ceramic SMD60-70%6x3mm$$
External Wire80-90%Large$

Section 3: Network Architecture Choices

3.1 Star vs. Mesh Power Consumption

500-node network simulation:

MetricStarMesh
Avg. Current8μA19μA
Max Hop Latency1s8s
Battery Life14y6y

3.2 Data Compression Techniques

  • Delta encoding (reduces payloads by 70%)
  • Sparse data packing (3.6:1 compression ratio)
  • Adaptive sampling rates