Energy-efficient battery management system for healthcare devices

Abstract Increasing demand for low-power consumer electronics and wearable medical devices calls for the means and methods to expedite improved energy efficiency, in the management of small rechargeable cells. In lithium-ion batteries, cell balancing is essential to distribute charges uniformly into the cell thus increasing its efficiency and lifespan. The motivation of this paper is to design and implement an improved battery management system for medical devices, by applying energy-efficient DC-DC converters-based cell balancing techniques, for better monitoring and management of the total energy of healthcare devices. The performance of different active and passive techniques for balancing the state of charge has been evaluated to optimize total pack energy in lithium-ion batteries present in different medical devices. An accurate battery model selection directly impacts the estimation results. In this research, we have adopted an equivalent circuit model (ECM) for battery modeling and its parameters have been estimated to identify the battery ' s state of health and its capacity in real-time. In addition, we have also prescribed the cost-benefit analysis and the optimal solution for the selection of lithium-ion cell balancing methods based on the different power requirements. Experimental setup results for four different case studies have shown that active balancing techniques outclass passive balancing techniques by saving 4.15% energy to the total battery pack, in each charge/discharge cycle. Therefore, the proposed energy-efficient battery management system improvises cell balancing and saves the cell pack energy, does real-time state identification by parameter estimation, the overall system and maintenance costs is reduced by the given cost-benefit analysis, and helps decision-making of the battery ' s energy storage systems for medical devices. Highlights • Battery model has been designed and validated to identify the battery state by estimating the battery parameters. The state of Li-ion batteries has been estimated by considering the temperature dynamics. • Energy-efficient DC/DC converter based active cell balancing techniques have been implemented to get real-time energy indication in the BMS. The implemented system results validate the safety, tracking the battery life, and better battery pack performance as compared to the commercially available BMS with passive cell balancing techniques. • On the basis of experimental results, their available energy, battery state and components cost expanded over five years life span, active cell balancing methods have been recommended for different power applications and number of cells