9November 2021 Table 1: MPF42790 State-of-Charge PerformanceFigure 1 shows an example of the MPF42790 pack's state-of-charge estimation performance, achieving 0.64 percent state-of-charge root-mean-square error and 1.46 percent maximum state-of-charge error. The test consists of a complete 1C constant-current and constant-voltage charge, which terminates when the charge current drops to 0.1C, followed by a 1C constant-current discharge on a multi-cell battery pack at 15°C (ambient temperature).Figure 1:The MPF42790's Performance for a Complete 1C Charge/Discharge CycleMPS's fuel gauge algorithm relies on high-fidelity electrical cell models generated from a proprietary characterization sequence, proprietary analysis, and optimization tools. This system allows users to easily load any one of these models into the fuel gauge (see Figure).Figure 2: Cell Mathematical Model GenerationSimple Fuel Gauge System IntegrationFuel gauges must provide accurate battery state estimates in real time. Because the fuel gauge relies on periodic cell parameter measurements (e.g., voltage, current, and temperature), the accuracy and reliability of a fuel gauge is limited to the accuracy and reliability of the measurements.For example, the distribution of cells within the battery pack leads to a temperature gradient due to non-uniform thermal dissipation (see Figure 3). Therefore, a fuel gauge must enable reading multiple temperature sensors to obtain a highly accurate cell-level thermal reading. Otherwise, the state estimation might be less accurate, regardless of the cell model accuracy.This novel architecture approach receives high-resolution, calibrated measurement data from the analog frontend (AFE). This architecture is compatible with any AFE on the market, and is simple to integrate into new or existing electronic designs (see Figure 3). Additionally, users benefit from unprecedented visibility of the cell stack's internal voltage, which provides key insight into the individual operation of each cell and its influence on the battery pack dynamics. Figure 3: Battery Management System (BMS) Fuel Gauge ArchitectureAs battery cells become unbalanced or operate at different temperatures, the chemical impedance of each cell diverges, shortening the battery's runtime and range. The battery pack's usable state-of-charge is limited by the weakest cell, so monitoring the individual cells' voltage allows the fuel gauge to deliver a more accurate estimate of the pack's state-of-charge in real time.The fuel gauge can accurately estimate the actual state of every cell (or group of parallel cells) in the stack while estimating the battery full and empty conditions (i.e., when the pack is at a 100 percentor0 percent state-of-charge, respectively). These fuel gauge solutions provide full and empty points that reflect both application-specific limits on the battery pack voltage and industry standards, such as IEC62133, that mandate safe operating voltages.Tomas Hudson
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