SLAAEF5B March   2024  – June 2025 MSPM0G1505 , MSPM0G1506 , MSPM0G1507 , MSPM0G3506 , MSPM0G3507 , MSPM0H3216 , MSPM0L1303 , MSPM0L1304 , MSPM0L1304-Q1 , MSPM0L1305 , MSPM0L1305-Q1 , MSPM0L1306 , MSPM0L1306-Q1

 

  1.   1
  2.   Abstract
  3.   Trademarks
  4. 1Introduction
  5. 2Algorithm Introduction
    1. 2.1 Battery Basic Knowledge Introduction
    2. 2.2 Different SOCs and Used Technologies
      1. 2.2.1 NomAbsSoc Calculation
        1. 2.2.1.1 Coulometer With OCV Calibration
        2. 2.2.1.2 Data Fusion
        3. 2.2.1.3 Battery Model Filter
      2. 2.2.2 CusRltSoc Calculation
        1. 2.2.2.1 EmptySoc and FullSoc
        2. 2.2.2.2 Core Temperature Evaluation
      3. 2.2.3 SmoothRltSoc Calculation
    3. 2.3 Algorithm Overview
      1. 2.3.1 Voltage Gauge Introduction
      2. 2.3.2 Current Gauge Introduction
      3. 2.3.3 Capacity Learn Introduction
      4. 2.3.4 Mixing Introduction
  6. 3Gauge GUI Introduction
    1. 3.1 MCU COM Tool
    2. 3.2 SM COM Tool
    3. 3.3 Data Analysis Tool
  7. 4MSPM0 Gauge Evaluation Steps
    1. 4.1 Step 1: Hardware Preparation
    2. 4.2 Step 2: Get a Battery Model
      1. 4.2.1 Battery Test Pattern
      2. 4.2.2 Battery Model Generation
    3. 4.3 Step 3: Input Customized Configuration
    4. 4.4 Step 4: Evaluation
      1. 4.4.1 Detection Data Input Mode
      2. 4.4.2 Communication Data Input Mode
    5. 4.5 Step 5: Gauge Performance Check
      1. 4.5.1 Learning Cycles
      2. 4.5.2 SOC and SOH Accuracy Evaluation
  8. 5MSPM0 Gauge Solutions
    1. 5.1 MSPM0L1306 and 1 LiCO2 Battery
      1. 5.1.1 Hardware Setup Introduction
      2. 5.1.2 Software and Evaluation Introduction
      3. 5.1.3 Battery Test Cases
        1. 5.1.3.1 Performance Test
        2. 5.1.3.2 Current Consumption Test
    2. 5.2 MSPM0G3507, BQ76952 and 4 LiFePO4 Batteries
      1. 5.2.1 Hardware Setup Introduction
      2. 5.2.2 Software and Evaluation Introduction
      3. 5.2.3 Battery Test Cases
        1. 5.2.3.1 Performance Test 1 (Pulse Discharge)
        2. 5.2.3.2 Performance Test 2 (Load Change)
    3. 5.3 MSPM0L1306 and BQ76905
  9. 6Summary
  10. 7References
  11. 8Revision History

Algorithm Overview

This section provides an overview of the introduced gauge algorithm as shown in Figure 2-13. This is only for the battery cell algorithm. Battery pack algorithms are just a combination of battery cell algorithms.

This algorithm is based on the coulometer, paired with other methods described before to solve the limitation. This is a combination of four parts. The Capacity Learn part is used to detect the battery rest, do OCV calibration and calculate SOH. The VGauge part is used to output the related parameters from the saved class-one battery model. IGauge is a coulometer used to accumulate the capacity. Mixing part is used to calculate and output NomAbsSoc, CusRltSoc and SmoothRltSoc to customers.

 Algorithm OverviewFigure 2-13 Algorithm Overview

In the following section, a description for every algorithm part and the key parameters outputted to GUI or other functions are provided.