SoC-Aware Adaptive Power Management for Multi-Source Energy Harvesting in Smartphone Charging

The growing energy demand of smartphones and other portable electronics has increased interest in supplementary energy-harvesting solutions that can operate when conventional charging infrastructure is limited. The integration of solar, radio-frequency, and kinetic-source based technologies can enhance energy availability; however static power-management strategies are not effective for time-varying sources. This paper proposes a state-of-charge (SoC)-aware adaptive power-management scheme which dynamically manages the three harvesting sources based on the available effective power instantaneously and the battery status. To determine source-allocation variables, a constrained Sequential Least Squares Programming (SLSQP) formulation is used to balance harvested-power utilization with consistency with respect to the prevailing source-power distribution. The framework is tested through simulations in the time domain, made with Python, using a 5000~mAh, 3.7~V battery under the same conditions, both for static and adaptive strategies. The adaptive method can shorten charging time from 13.02~h to 10.98~h, increase the average charging power from 1.13~W to 1.35~W, and reduce the unused energy from 21.15~Wh to 9.53~Wh and increase the energy utilization from 41.09\% to 60.72\%. Further simulations under cloudy, low-light and low-energy conditions indicate that the relative gain of adaptive allocation becomes more pronounced as harvested-power availability becomes more restricted. The results show that battery-aware dynamic source coordination can enhance the effective utilization of harvested energy from multiple and heterogeneous sources in time-varying operating conditions.