SLAAEF5 March   2024 MSPM0G1505 , MSPM0G1505 , MSPM0G1506 , MSPM0G1506 , MSPM0G1507 , MSPM0G1507 , MSPM0L1303 , MSPM0L1303 , MSPM0L1304 , MSPM0L1304 , MSPM0L1304-Q1 , MSPM0L1304-Q1 , MSPM0L1305 , MSPM0L1305 , MSPM0L1305-Q1 , MSPM0L1305-Q1 , MSPM0L1306 , MSPM0L1306 , MSPM0L1306-Q1 , 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 Equations
      1. 2.2.1 NomAbsSoc Calculation
        1. 2.2.1.1 Coulometer With OCV Calibration
        2. 2.2.1.2 Battery Model Filter
      2. 2.2.2 CusRltSoc Calculation
      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 Step1: Hardware Preparation
    2. 4.2 Step2: Get Battery Model
      1. 4.2.1 Battery Test Pattern
      2. 4.2.2 Battery Model Generation
    3. 4.3 Step3: Input Customized Configuration
    4. 4.4 Step4: Evaluation
      1. 4.4.1 Detection Data Input Mode
      2. 4.4.2 Communication Data Input Mode
  8. 5MSPM0 Gauge Solutions
    1. 5.1 MSPM0L1306 + 1 LiCO2 Battery
      1. 5.1.1 Hardware Setup Introduction
      2. 5.1.2 Software and Evaluation Introduction
      3. 5.1.3 Battery Testcases
        1. 5.1.3.1 Performance Test
        2. 5.1.3.2 Current Consumption Test
    2. 5.2 MSPM0G3507 + BQ76952 + 4 LiFePO4 Batteries
      1. 5.2.1 Hardware Setup Introduction
      2. 5.2.2 Software and Evaluation Introduction
      3. 5.2.3 Battery Testcases
        1. 5.2.3.1 Performance Test1 (Pulse Discharge)
        2. 5.2.3.2 Performance Test2 (Load Change)
  9. 6References

2.2.1.2 Battery Model Filter

In Section 2.2.1.1, NomAbsSoc is evaluated based on purely one battery parameter (Voltage or current accumulation). One method is to use the relationship between OCV (positive and negative electrodes balance) and NomAbsSoc (different lithium ion concentrations). Another method is to use the relationship between coulometer (Electron numbers) and capacity (Movable Lithium ion numbers). This kind of strategy requires less computing resources, as only coulometer is needed to work in every cycle. However, it needs to wait until the NomFullCap is generated for 1-2 battery cycles.

Another strategy is used to create a model or a filter to evaluate the NomAbsSoc or even the CusRltSoc based on all the input parameters, like current, voltage, time and temperature. The common methods are equivalent-circuit model, Kalman-filter, neural network and so on. The accuracy of the SOC output mostly lies on the model accuracy. However, more complex model means more MCU computing resources.

An economic method is to use a simplest equivalent-circuit model (a first order RC model), shown in Figure 2-5, to output NomAbsSoc with only voltage input.

GUID-337215D2-6B13-4CB4-B838-663C4295C057-low.png Figure 2-5 Battery Model

Figure 2-6 shows the software flow chart of VGauge. However, in this solution, the SOC lookup table function only needs to be used to search the wanted parameters in this battery model. For the SOC part, it is purely come out from IGauge.

GUID-FE29B8CE-10AB-4A98-9015-9CF3D723C633-low.png Figure 2-6 VGauge Software Flow

For more about the NomAbsSoc accuracy outputted from VGauge, see MSPM0 Gauge L1 Solution Guide.