A Battery Remaining Time Prediction Model Considering Battery Decay for Smartphones

• Main Authors: Liu, Jaan-Chun, 劉展均
• Other Authors: Huang, Yu-Lun
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/6amcm8

碩士 === 國立交通大學 === 電控工程研究所 === 102 === A majority of the existing smartphones lack an impressive battery. The battery life limits the use of a smartphone. Applications are forced to be terminated due to the shortage of battery. Therefore, knowing the remaining battery life becomes an important concern for smartphone users. Many researchers and developers intend to measure the remaining battery life and design battery applications for smartphone users. The researchers face several challenges, including providing remaining battery life in real time and providing accurate measurement after battery decay.In this thesis, we propose a model named Battery Remaining Time Prediction Model (BRTPM) to estimate remaining battery life in real time and to improve the measurement accuracy by considering battery decay. We first obtain the battery discharge curve to estimate the percentage of battery. Then, we use this percentage to estimate the remaining battery life. Second, we update BRTPM to keep the accuracy of BRTPM after battery decay. We conduct two experiments to evaluate the accuracy of BRTPM and to demonstrate the impact on accuracy caused by the battery decay. The first experiment we shows that the erroneous measurement can be limited within 0~10 (mins) or within 0~10(%). The second experiment demonstrates the impact of battery decay on the accuracy of measurement. We also show that the accuracy can be improved for 8.94% - 15.1% after applying the updated discharge curve in our experiments.