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Choose the right battery fuel-gauge for smartphones, tablets

23 Jul 2012  | Ming Yu, David Maxwell

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A true battery fuel-gauge accurately measures the battery voltage, charge and discharge current, and battery temperature. It then uses its own sophisticated gauging algorithm to calculate the battery SOC, available capacity, and other useful information. Some advanced battery fuel-gauges can learn the actual battery capacity and impedance as they change over time and usage. For optimal accuracy the learning is critical since battery cells from the same production line do not have identical capacities and resistance profiles. The profile also changes as the cell ages. The gauges with profile statically configured only for a new pack cannot provide accurate results after some time in the field.

A Lithium-Ion (Li-Ion) or Lithium-Polymer (Li-Poly) battery is an electrochemical system with complex behavior. This presents challenges to simplistic concepts of fuel gauging. The battery SOC is no longer a simple function of battery voltage. It is a function of battery voltage, load, temperature and internal impedance (equation 1).

SOC = f (V, I, T, R) Equation 1

A battery's behavior depends on its chemical solution, anode and cathode materials. However, the open circuit voltage (OCV) curve of the same type of battery is very similar. A fuel-gauge can use the OCV to determine the initial SOC of a battery. A "fuel-gauge" that only uses coulomb-counting cannot determine the initial SOC due to lack of OCV information. These gauges require a full cycle (charge to full then discharge to empty) to get accurate results and are best used when embedded in the battery pack. For host-side coulomb counters, this becomes an issue since once the battery pack is removed.

Traditional voltage-based gauges can no longer be used for smartphone or tablet applications (figure 1). The only condition under which the voltage can reliably be used as an OCV measurement is when the battery is relaxed.

Figure 1: Even under normal operation the load profiles for high-end smartphones are so dynamic that battery voltage and SOC no longer directly correspond.

There are several ways to compensate for battery temperature and aging. One traditional method is to test the battery extensively and get the battery discharge characteristics under various temperatures and load conditions. The data is analyzed and a fixed compensation factor used for the gauging algorithm is generated. This method is very time-consuming and the results are not optimized because the battery chemical reaction is very dynamic and a fixed factor cannot correctly compensate in actual use cases. Additionally, aging compensation factors inevitably will be wrong because every battery ages at a different rate depending on the currents, voltages, temperatures, and number of cycles to which they are exposed. For applications with short expected lifetimes, battery aging may not be of concern. However, as non-removable batteries become more common in smartphones and tablets, it becomes critical for the gauge to maintain accuracy by learning the batteries' aged characteristics.

A highly accurate battery fuel-gauge can dynamically track the battery impedance and use it to compensate for the battery temperature and aging. Because the impedance-learning process is real-time when the smartphone or tablet is in use, the learned data is stored in flash and updated. This algorithm combines the voltage-based traditional gauging method to get very accurate initial SOC through OCV readings and also count the coulombs when a charge or load is applied.

Moreover, there are additional modeling features that can be used to increase the gauging accuracy. These include transient modeling and thermal modeling to allow the gauge to provide accurate gauging results without any need from the host processor. This is critical for today's smartphone or tablet design when power consumption is the major concern.

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