Understanding Battery Voltage Measurement in BMS

1. Understanding Battery Voltage Measurement in BMS Battery Management Systems (BMS) need accurate battery voltage measurements. Many lithium-ion battery manufacturing equipment suppliers overlook this. This accuracy is crucial for estimating the battery's State of Charge (SoC). But what is SoC, and why does it matter? Let’s take lithium iron phosphate batteries as an example. These batteries show a specific relationship between their Open Circuit Voltage (OCV) and SoC. The OCV- SoC curve shows how OCV changes with SoC. When the battery discharges, its OCV drops. When it charges, the OCV rises. The curve is steep between SoC values of 0- 20% and 80-100%, but gradual between 20-80%. The OCV method estimates SoC by measuring the battery's OCV. This estimation depends on voltage measurement accuracy. A tiny 1-millivolt (1mV) change in OCV can lead to a 5% change in SoC. Figure 2 shows how different millivolt changes affect SoC in a typical lithium iron phosphate battery. So, if your voltage measurement is accurate to 1mV, your SoC estimation will be about 5% accurate. The rate of voltage change per millivolt varies with different charge states, impacting SoC estimation accuracy.

2. This discussion focuses on voltage measurement accuracy with the OCV method. Other factors like discharge rate and temperature also affect SoC accuracy. To improve accuracy, methods like the ampere integral method, Kalman filtering, or deep learning AI are used. As battery technology advances, precise voltage measurement remains key for accurate SoC estimation. This helps optimize battery performance in devices from phones to electric cars and renewable energy systems. Accurate measurements enable smart BMS to improve battery performance and system reliability.