This high accuracy should be retained as the battery

July 23 [Tue], 2013, 10:22
Battery voltage, current and temperature alone are not sufficient to provide accurate SoC estimations, much less state-of-health (SoH). Early Li-ion correlated the rising internal resistance with SoH. This no longer works because bright A32-N71 most modern Li-ion batteries maintain low resistance as the battery ages.

When designing a BMS, one also must consider how the battery serves the host. In an iPhone and most EVs, for example, the battery is “married” to the host. This enables collecting data for learning. The battery and device co-habitat in a similar way to partners in a good marriage. Batteries for two-way radio, on the other hand, are picked from a common charger and returned to a pool for recharging after use. Learning is difficult and a different method must be used to track battery health.

Cadex Electronics is making critical progress in measuring battery SoC with magnetism. Quantum magnetism (Q-Mag?) could provide the most accurate battery SoC readings ever achieved. Q-Mag? makes use of the magnetic property relating to SoC, which changes as much as three-fold between empty and full charge on some battery systems. A coil generates an AC field and a sensor reads the magnetic susceptibility, which is linear to SoC.

There are several choices of sensors and because of availability and low price Cadex conducts the research with the GMR (Giant Magnetoresistance) sensor. It consists of ferromagnetic alloys that are sandwiched on an ultrathin nonmagnetic conducting layer. Applying a magnetic field lowers the resistance; removing the force increases it. The principle is known as electron scattering, which is also used on hard drive read/write heads. Figure 2 illustrates the function of a GMR sensor.

Q-Mag? has successfully been tested with Li-ion-cobalt, NMC, lithium iron phosphate, as well as several types of lead acid batteries. The system is immune to most outside interference and does not rely on voltage for SoC estimations. This allows reading SoC while the battery is on charge or a load. Q-Mag? works with prismatic and cylindrical cells in aluminum and stainless steel casings, but not in ferrous material. The accuracy on lithium-based chemistries is +/-5%, lead acid is +/-7%. This high accuracy should be retained as the battery ages. Calibration occurs by applying a full charge.

With voltage and current references, Q-Mag? is able to calculate SoC and SoH. The BMS can also detect micro-shorts by observing the self-discharge of a faulty cell, a feature that enhances battery safety. Furthermore, Q-Mag? can be used for load leveling. This eliminates the rubber-band effect that complicates SoC estimations through voltage. Figure 3 shows Q-Mag as key contributor to BMS.

Q-Mag can be made small and sandwiched between cells. A multi-cell battery may have one sensor for an overall assessment or several to enable diagnostics to cell level. An ASIC containing Q-Mag? could also include bright A32-U80 temperature sensing and digital processing. At high volume, low price would make this technology available for big and small batteries, including consumer products. Displaying precise energy reserve, as is possible with a liquid fuel system, may be closer than we think.
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