Predictive Battery Management Technology from TI Delivers Up to 30% Longer Run Time in Battery-Powered Electronics

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Texas Instruments (TI) introduced new single-chip battery fuel gauges with first-of-its-kind adaptive Dynamic Z-Track™ technology for more efficient, reliable operation in battery-powered devices. Compared to traditional gauging methods, the predictive modeling algorithm in TI’s BQ41Z90 and BQ41Z50 gauges achieve industry-leading state-of-charge and state-of-health accuracy within 1% error, helping extend battery run time by up to 30%.

As users demand more power from electronics, such as laptops, e-bikes and portable medical devices, battery management systems (BMSs) must provide precise, accurate, real-time monitoring. The BQ41Z90 and BQ41Z50 fuel gauges with Dynamic Z-Track technology help engineers design electronic devices with accurate battery capacity readings, even under unpredictable loads. With this increased accuracy, engineers can select a battery size with confidence, eliminating the need for oversized batteries.

“Whether you’re finishing a project on your laptop or riding home on an e-bike, accurate battery capacity estimates and reliability are critical,” said Yevgen Barsukov, Ph.D., TI Fellow and head of BMS algorithm development. “Traditional battery monitoring methods often struggle with accuracy under erratic use conditions, leading to unreliable predictions. However, our new Dynamic Z-Track technology is a predictive battery model that can self-update across dynamic load conditions, like those created by AI applications, ensuring the most accurate run-time prediction. Evolving from 20 years of reactive monitoring, this innovation enables users to experience dependable function, safer operation, and precise tracking of battery age and run time.”