Mobile Battery Management Systems

Environment-Aware Estimation of Battery State-of-Charge:

Reliable operation of mobile devices, such as smartphones and tablets, has become essential for a great many users around the globe. Mobile devices, however, have been reported to suffer from frequent, unexpected shutoffs — e.g., shutting off even when their batteries were shown to have up to 60% remaining state-of-charge (SoC) — especially in cold environments. Their main cause is found to be the inability of commodity mobile devices to account for the strong dependency between battery SoC and the environment temperature. To remedy this problem, we design, implement, and evaluate EA-SoC, a real-time Environment-Aware battery SoC estimation service for mobile devices. EA-SoC estimates the battery SoC with a cyber-physical approach, based on (1) a thermal circuit model in the cyber space capturing the physical interactions among the battery discharge current, temperature, and the environment, and (2) an empirically validated data-driven (i.e., cyber) model for the physical relations between battery temperature and battery resistance.
Battery-aware Power Management:

Many users of mobile devices, such as smartphones and tablets, have experienced unexpected shutoffs of their devices, even when their battery is shown to have greater than 30% of the maximum capacity. Our close scrutiny of the power consumption & supply of mobile devices uncovers the cause of such unexpected shutoffs to be the large voltage drop across the device battery’s internal impedance: (i) bursty discharge current of mobile devices, together with the battery’s dynamic internal impedance which varies with battery state-of-charge (SoC) and age, cause the drop of device battery voltage to fluctuate; (ii) these voltage drops, if too large, shut the device off even before the battery is fully drained. To mitigate such unexpected device shutoffs, we design a novel Battery-aware Power Management (BPM) middleware for mobile devices that captures the dynamically-changing battery impedance and adaptively controls the device’s runtime discharge current, thus regulating the battery’s voltage drop and achieving reliable and extended device operation. Specifically, BPM (i) profiles the battery impedance at different SoC levels using a novel duty-cycled charging method, and then (ii) regulates, at runtime, the maximum discharge current based on the thus-constructed battery profile.


  • Kang G. Shin

Graduate Students

  • Youngmoon Lee

External Collaborators

  • Liang He (University of Colorado @ Denver)
  • Eugene Kim (Apple, Inc.)

Funding Sources

  • NSF
  • National Research Foundation of Korea


  • Liang He, Youngmoon Lee, Eugene Kim, and Kang G. Shin, Environment-Aware Estimation of Battery State-of-Charge for Mobile Devices, in the ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS '19), Montreal, Canada, April 2019.