Battery gas gauges using Impedance TrackTM technology use a blend of coulomb counting and voltage based algorithms to provide the most accurate state of charge indication for a wide variety of secondary batteries available today.
One thing we have noticed in the Battery Management Gas Gauge forum is that sometimes it is hard to know where to start when designing a fuel gauge into a battery management system. We see questions about the gauge parameter calculator (GPC) tool, learning cycle, cold temperature performance tweak (RbTweak), thermal modeling golden-file generation and more.
In this post, I’ll explain the terms and tools introduced in the previous paragraph . By the time you’ve finished reading, I hope you’ll be able to order an evaluation module (EVM) from the TI store, complete a successful learning cycle, and create a golden file optimized for your battery.
Let’s start with a brief introduction to the battery. Electrical engineers often regard lithium-ion (Li-ion) batteries as a direct current (DC) source – or in complex models, a DC source with some internal impedance. Often that is as advanced as the model gets. In my undergraduate studies, I remember learning about batteries, but before starting work at Texas Instruments, I also regarded them as just a simple DC model. However, a battery is much more than just a DC power supply. A battery is actually a complex electrochemical device with complex aging properties.
The EVM for any Impedance Track device will help you characterize and learn the characteristics of your battery cell within the ecosystem of tools surrounding it. To learn your battery’s characteristics, you will need to gather some basic data: crucial parameters include the voltage, current and temperature of the cell, and how they change with respect to time as the battery charges, discharges or just sits there. The gas-gauge IC on the EVM contains an analog front end (AFE) that takes and updates measurements at least once every second.
The bqStudio’s Registers tab interfaces with the product’s corresponding EVM via the EV2300 or EV2400’s inter-integrated circuit (I2C)/ high-speed data queue(HDQ)/ smart management bus (SMBus) connector to extract these measurements from the gas gauge. BqStudio has a Start Logging button for supported devices that will save the extracted measurements every four seconds (configurable in the Preferences menu) to a .log text file. With bqStudio’s logging capability, you can gather data from a charge cycle, discharge cycle, relaxation periods or any mixture of the three. Gauging application engineers typically refer to the log file as the IVT log.
To start using an Impedance Track gas gauge, you will first need to identify the battery’s chemistry type. In bqStudio, the Chemistry plug-in contains a giant database with names/numbers/text. The numbers represent a battery-chemistry ID (chemID).
Once you have the chemID, which should be a number between 100 to 9,000, you can program that particular chemID into your gas gauge IC. This step is required before a learning cycle and the generation of a production-ready golden file. If you are not able to find the particular chemID in the bqStudio Chemistry plug-in, you can download the latest bqStudio Chemistry Updater file.
To generate a golden file, you will need to have completed the previous steps of obtaining and programming in the chemID. The Impedance Track gas gauge updates the total available chemical capacity and impedances of the battery throughout the discharge. For optimal out-of-the-box accuracy, I highly recommend running a learning cycle once during your development flow, as it adapts the gas-gauge internal parameters closely track the battery’s impedance profile and chemical capacity. The chemical capacity and resistance values of a battery is referred to as Qmax and Ra tables in Texas Instruments literature. In order to run the learning cycle, the GPC “goldenizer” tool can help you find the Qmax and Ra tables after you’ve gathered the required IVT logs. The blog post, How to run an Impedance Track gas gauge learning cycle goes into detail on learning cycles for a particular class of Read Only Memory (ROM)-based gas gauges.
The golden file is the final production file used to program the Impedance Track gas gauge. This file has both optimized battery and system settings. Think of the gas gauge as a marriage between the system and the battery. It has a lot of features to provide the system with the most accurate battery conditions based on system behavior such as load dynamics, system hardware, trace resistance and temperature transients. The technical reference manual documents many of these features and associated dataflash parameters to tweak them. Once you have the golden file, you can mass-produce systems or battery packs.
Impedance Track gas gauges can achieve the highest state of charge (SOC) accuracy for your application when configured properly. There is a large ecosystem surrounding the tuning/tweaking of gas gauges to optimize them for your system. My intention with this post was to explain the ecosystem in a way that would alleviate confusion when it comes to tying different parts of the ecosystem together.
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