SLVSMB0 June   2026

 

  1.   1
  2.   Description
  3.   Features
  4.   4
  5. 1 Evaluation Module Overview
    1. 1.1 Introduction
    2. 1.2 Kit Contents
    3. 1.3 Specifications
    4. 1.4 Device Information
  6. 2 Hardware
    1. 2.1 Hardware Requirements
    2. 2.2 Connecting the BQ27Z855 Circuit Module to a Battery Pack
    3. 2.3 EVM Jumpers and Terminal Block Description
  7. 3 Software
    1. 3.1 System Requirements
    2. 3.2 Software Installation
    3. 3.3 Updating Firmware
    4. 3.4 Troubleshooting Unexpected Dialog Boxes
  8. 4 Using bqStudio
    1. 4.1 Starting the Program
    2. 4.2 Setting Programmable BQ27Z855 Options
    3. 4.3 Configuring the Integrated Linear Battery Charger
  9. 5 Calibrating Gauge Measurements
    1. 5.1 Voltage Calibration
    2. 5.2 Current Calibration
  10. 6 Chemical ID
    1. 6.1 Chemical ID Selection Process
    2. 6.2 Hardware Requirements and Setup
    3. 6.3 Logging Data in bqStudio
    4. 6.4 GPCChem Tool
    5. 6.5 Programming a Chemical ID
    6. 6.6 Further Resources for Chemical ID Process
  11. 7 Learning Cycle and Golden Image
    1. 7.1 Learning Cycle Process Description
    2. 7.2 Data Memory Configuration
    3. 7.3 Learning Cycle Steps
    4. 7.4 Low Temperature Optimization
    5. 7.5 Creating the Golden Image File
    6. 7.6 Programming the Golden Image File
  12. 8 Gauge Communication
    1. 8.1 Advanced Communication in bqStudio
    2. 8.2 Standard Data Commands
    3. 8.3 Manufacturer Access Commands
    4. 8.4 Further Resources on Gauge Communication
  13. 9 BQ27Z855-Based Circuit Module
    1. 9.1 Circuit Module Connections
    2. 9.2 Pin Descriptions
  14. 10Hardware Design Files
    1. 10.1 Schematic
    2. 10.2 Bill of Materials (BOM)
    3. 10.3 PCB Layouts
  15. 11Additional Information
    1.     Trademarks

7 Learning Cycle and Golden Image

The learning cycle process is the initial optimization that Impedance Track gauges perform in order to ensure accuracy of the gauge in reporting state of charge. The learning cycle allows the gauge to learn a specific battery’s resistance and maximum chemical capacity, ensuring accuracy as the cell ages. It is necessary that a correct ChemID, with less than 3% of error, has been identified and programmed into the gauge before attempting a learning cycle.