research-article

MixMax: Leveraging Heterogeneous Batteries to Alleviate Low Battery Experience for Mobile Users

Authors:

Insik ShinAuthors Info & Claims

MobiSys '23: Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services

Pages 247 - 260

https://doi.org/10.1145/3581791.3596843

Published: 18 June 2023 Publication History

Abstract

Despite the physical advance of an existing single-cell battery system, mobile users are still suffering from low battery anxiety. With a careful analysis of users' battery usage behavior collected for 19,855 hours, we propose a heterogeneous battery system, MixMax, consisting of three complementary battery types tailored to minimizing the low battery time. While composing a heterogeneous battery system opens up a chance to simultaneously improve the capacity and the charging speed, one must face non-trivial challenges to determine the ratio of enclosed batteries and charge/discharge policies during the run-time. They are highly dependent on each other, which entails almost infinite candidates for the choice. MixMax gracefully unwinds the dependencies as it formulates the decision-making problem into an optimization problem and decomposes it into multiple sub-problems instead. To evaluate MixMax, we fabricate coin-cell batteries and experiment with them to model an accurate battery emulator which sophisticatedly reproduces the dynamics of battery systems. Our experimental results demonstrate that MixMax can reduce the low battery time by up to 24.6% without compromising capacity, volume, weight, and more importantly, users' battery usage behavior. In addition, we prototype MixMax on a smartphone, presenting the practicality of MixMax on mobile systems.

References

[1]

LG Electronics. "low battery anxiety" grips 9 out of ten people. https://www.lg.com/us/PDF/press-release/LG_Mobile_Low_Battery_Anxiety_Press_Release_FINAL_05_19_2016.pdf, May 2016.

[2]

Guoming Tang, Kui Wu, Deke Guo, Yi Wang, and Huan Wang. Alleviating low-battery anxiety of mobile users via low-power video streaming. In 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), pages 998--1008. IEEE, 2020.

[3]

George E Blomgren. The development and future of lithium ion batteries. Journal of The Electrochemical Society, 164(1):A5019, 2016.

[4]

Digibites. Accubattery research and methodology, 2022. https://accubattery.zendesk.com/hc/en-us/sections/202397985-AccuBattery-Research-and-Methodology.

[5]

Xiaomeng Chen, Ning Ding, Abhilash Jindal, Y Charlie Hu, Maruti Gupta, and Rath Vannithamby. Smartphone energy drain in the wild: Analysis and implications. ACM SIGMETRICS Performance Evaluation Review, 43(1):151--164, 2015.

Digital Library

[6]

Pranab Dash and Y Charlie Hu. How much battery does dark mode save? an accurate oled display power profiler for modern smartphones. In Proceedings of the 19th Annual International Conference on Mobile Systems, Applications, and Services, pages 323--335, 2021.

Digital Library

[7]

Abhilash Jindal and Y Charlie Hu. Differential energy profiling: energy optimization via diffing similar apps. In 13th USENIX Symposium on Operating Systems Design and Implementation, 2018.

[8]

Jiayi Meng, Qiang Xu, and Y Charlie Hu. Proactive energy-aware adaptive video streaming on mobile devices. In 2021 USENIX Annual Technical Conference (USENIX ATC 21), pages 303--316, 2021.

[9]

Niranjan Balasubramanian, Aruna Balasubramanian, and Arun Venkataramani. Energy consumption in mobile phones: a measurement study and implications for network applications. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement, pages 280--293, 2009.

Digital Library

[10]

Aaron Carroll, Gernot Heiser, et al. An analysis of power consumption in a smartphone. In USENIX annual technical conference, volume 14, pages 21--21. Boston, MA, 2010.

Digital Library

[11]

Alex Shye, Benjamin Scholbrock, and Gokhan Memik. Into the wild: studying real user activity patterns to guide power optimizations for mobile architectures. In Proceedings of the 42nd annual IEEE/ACM international symposium on microarchitecture, pages 168--178, 2009.

Digital Library

[12]

Narendran Thiagarajan, Gaurav Aggarwal, Angela Nicoara, Dan Boneh, and Jatinder Pal Singh. Who killed my battery? analyzing mobile browser energy consumption. In Proceedings of the 21st international conference on World Wide Web, pages 41--50, 2012.

Digital Library

[13]

Youngmoon Lee, Liang He, and Kang G Shin. Causes and fixes of unexpected phone shutoffs. In Proceedings of the 18th International Conference on Mobile Systems, Applications, and Services, pages 206--219, 2020.

Digital Library

[14]

Liang He, Guozhu Meng, Yu Gu, Cong Liu, Jun Sun, Ting Zhu, Yang Liu, and Kang G Shin. Battery-aware mobile data service. IEEE Transactions on Mobile Computing, 16(6):1544--1558, 2016.

Digital Library

[15]

Duc Hoang Bui, Yunxin Liu, Hyosu Kim, Insik Shin, and Feng Zhao. Rethinking energy-performance trade-off in mobile web page loading. In Proceedings of the 21st Annual International Conference on Mobile Computing and Networking, pages 14--26, 2015.

Digital Library

[16]

Fengyuan Xu, Yunxin Liu, Thomas Moscibroda, Ranveer Chandra, Long Jin, Yongguang Zhang, and Qun Li. Optimizing background email sync on smart-phones. In Proceeding of the 11th annual international conference on Mobile systems, applications, and services, pages 55--68, 2013.

Digital Library

[17]

Radhika Mittal, Aman Kansal, and Ranveer Chandra. Empowering developers to estimate app energy consumption. In Proceedings of the 18th annual international conference on Mobile computing and networking, pages 317--328, 2012.

Digital Library

[18]

Brett D Higgins, Jason Flinn, Thomas J Giuli, Brian Noble, Christopher Peplin, and David Watson. Informed mobile prefetching. In Proceedings of the 10th international conference on Mobile systems, applications, and services, pages 155--168, 2012.

Digital Library

[19]

Sungwoo Baek, Minyoung Go, Seokjun Lee, and Hojung Cha. Exploiting multi-cell battery for mobile devices: Design, management, and performance. In Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, pages 1--13, 2017.

Digital Library

[20]

Anirudh Badam, Ranveer Chandra, Jon Dutra, Anthony Ferrese, Steve Hodges, Pan Hu, Julia Meinershagen, Thomas Moscibroda, Bodhi Priyantha, and Evangelia Skiani. Software defined batteries. In Proceedings of the 25th Symposium on Operating Systems Principles, pages 215--229, 2015.

Digital Library

[21]

Zichen Xu, Jie Zhou, Wenli Zheng, Yuhao Wang, and Minyi Guo. Exploiting big. little batteries for software defined management on mobile devices. IEEE Transactions on Mobile Computing, 2020.

[22]

Vanessa Paladini, Teresa Donateo, Arturo De Risi, and Domenico Laforgia. Super-capacitors fuel-cell hybrid electric vehicle optimization and control strategy development. Energy conversion and management, 48(11):3001--3008, 2007.

[23]

Zachary Bosire Omariba, Lijun Zhang, and Dongbai Sun. Review of battery cell balancing methodologies for optimizing battery pack performance in electric vehicles. IEEE Access, 7:129335--129352, 2019.

[24]

Google Developers. dumpsys | Android Developers. https://developer.android.com/studio/command-line/dumpsys, 2021. [Online; accessed 20-October-2021].

[25]

Yonatan Vaizman, Katherine Ellis, Gert Lanckriet, and Nadir Weibel. Extrasensory app: Data collection in-the-wild with rich user interface to self-report behavior. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, pages 1--12, 2018.

Digital Library

[26]

Yonatan Vaizman, Katherine Ellis, Gert Lanckriet, and Nadir Weibel. The ExtraSensory Dataset. http://extrasensory.ucsd.edu/, 2018. [Online; accessed 29-November-2021].

[27]

Longlong Wang, Bingbing Chen, Jun Ma, Guanglei Cui, and Liquan Chen. Reviving lithium cobalt oxide-based lithium secondary batteries-toward a higher energy density. Chemical Society Reviews, 47(17):6505--6602, 2018.

[28]

Naoki Nitta, Feixiang Wu, Jung Tae Lee, and Gleb Yushin. Li-ion battery materials: present and future. Materials today, 18(5):252--264, 2015.

[29]

Qing Xie, Mohammad Javad Dousti, and Massoud Pedram. Therminator: A thermal simulator for smartphones producing accurate chip and skin temperature maps. In Proceedings of the 2014 international symposium on Low power electronics and design, pages 117--122, 2014.

Digital Library

[30]

Yang Daniel and Fontaine Ray. Samsung Galaxy S20 Ultra 5G Teardown Analysis. https://www.techinsights.com/blog/samsung-galaxy-s20-teardown-analysis, 2020. [Online; accessed 19-December-2021].

[31]

Woojoo Lee, Yanzhi Wang, Donghwa Shin, Naehyuck Chang, and Massoud Pedram. Optimizing the power delivery network in a smartphone platform. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 33(1):36--49, 2013.

Digital Library

[32]

Lei Zhang, Xiaosong Hu, Zhenpo Wang, Jiageng Ruan, Chengbin Ma, Ziyou Song, David G Dorrell, and Michael G Pecht. Hybrid electrochemical energy storage systems: An overview for smart grid and electrified vehicle applications. Renewable and Sustainable Energy Reviews, 139:110581, 2021.

[33]

Richard P Brent. Algorithms for minimization without derivatives. Courier Corporation, 2013.

[34]

Lia Kouchachvili, Wahiba Yaïci, and Evgueniy Entchev. Hybrid battery/supercapacitor energy storage system for the electric vehicles. Journal of Power Sources, 374:237--248, 2018.

[35]

Hongwen He, Xiaowei Zhang, Rui Xiong, Yongli Xu, and Hongqiang Guo. Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles. Energy, 39(1):310--318, 2012.

[36]

Donkyu Baek, Yukai Chen, Alberto Bocca, Lorenzo Bottaccioli, Santa Di Cataldo, Valentina Gatteschi, Daniele Jahier Pagliari, Edoardo Patti, Gianvito Urgese, Naehyuck Chang, et al. Battery-aware operation range estimation for terrestrial and aerial electric vehicles. IEEE Transactions on Vehicular Technology, 68(6):5471--5482, 2019.

[37]

Peng Liao, Tie-Qiao Tang, Ronghui Liu, and Hai-Jun Huang. An eco-driving strategy for electric vehicle based on the powertrain. Applied Energy, 302:117583, 2021.

[38]

Rui Xiong, Jiayi Cao, and Quanqing Yu. Reinforcement learning-based real-time power management for hybrid energy storage system in the plug-in hybrid electric vehicle. Applied energy, 211:538--548, 2018.

[39]

Yanzhi Wang, Younghyun Kim, Qing Xie, Naehyuck Chang, and Massoud Pedram. Charge migration efficiency optimization in hybrid electrical energy storage (hees) systems. In IEEE/ACM International Symposium on Low Power Electronics and Design, pages 103--108. IEEE, 2011.

Digital Library

[40]

Yanzhi Wang, Xue Lin, Massoud Pedram, Sangyoung Park, and Naehyuck Chang. Optimal control of a grid-connected hybrid electrical energy storage system for homes. In 2013 Design, Automation & Test in Europe Conference & Exhibition (DATE), pages 881--886. IEEE, 2013.

[41]

Yukai Chen, Alberto Bocca, Alberto Macii, Enrico Macii, and Massimo Poncino. A li-ion battery charge protocol with optimal aging-quality of service trade-off. In Proceedings of the 2016 International Symposium on Low Power Electronics and Design, pages 40--45, 2016.

Digital Library

[42]

Wiggins Gavin. equiv-circ-model. https://github.com/batterysim/equiv-circ-model, 2020.

[43]

Hongwen He, Rui Xiong, and Jinxin Fan. Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach. energies, 4(4):582--598, 2011.

[44]

Micah S Ziegler and Jessika E Trancik. Re-examining rates of lithium-ion battery technology improvement and cost decline. Energy & Environmental Science, 14(4):1635--1651, 2021.

[45]

Micah S. Ziegler and Jessika E. Trancik. Data series for lithium-ion battery technologies, 2021.

[46]

Texas Instruments. TPS61022. https://www.ti.com/product/TPS61022, 2023. [Online; accessed 10-April-2023].

[47]

Liang He, Yu-Chih Tung, and Kang G Shin. icharge: User-interactive charging of mobile devices. In Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services, pages 413--426, 2017.

Digital Library

[48]

Alma Pröbstl, Philipp Kindt, Emanuel Regnath, and Samarjit Chakraborty. Smart2: Smart charging for smart phones. In 2015 IEEE 21st International Conference on Embedded and Real-Time Computing Systems and Applications, pages 41--50. IEEE, 2015.

Digital Library

[49]

Liang He, Eugene Kim, and Kang G Shin. *-aware charging of lithium-ion battery cells. In 2016 ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS), pages 1--10. IEEE, 2016.

[50]

Guoming Tang, Kui Wu, Yangjing Wu, Huan Wang, and Guangwu Qian. Modelling and alleviating low-battery anxiety for mobile users in video streaming services. IEEE Internet of Things Journal, 2021.

[51]

Younghyun Kim, Jason Koh, Qing Xie, Yanzhi Wang, Naehyuck Chang, and Massoud Pedram. A scalable and flexible hybrid energy storage system design and implementation. Journal of Power Sources, 255:410--422, 2014.

[52]

Thanh Hai Phung, Alexandre Collet, and Jean-Christophe Crebier. An optimized topology for next-to-next balancing of series-connected lithium-ion cells. IEEE transactions on power electronics, 29(9):4603--4613, 2013.

[53]

Ujjal Manandhar, Abhisek Ukil, Hoay Beng Gooi, Narsa Reddy Tummuru, Sathish Kumar Kollimalla, Benfei Wang, and Kalpesh Chaudhari. Energy management and control for grid connected hybrid energy storage system under different operating modes. IEEE Transactions on Smart Grid, 10(2):1626--1636, 2017.

[54]

Caisheng Wang, George Yin, Feng Lin, Michael P Polis, Caiping Zhang, Jiuchun Jiang, et al. Balanced control strategies for interconnected heterogeneous battery systems. IEEE Transactions on Sustainable Energy, 7(1):189--199, 2015.

[55]

Apple. Use Low Power Mode to save battery life on your iPhone. https://support.apple.com/en-gb/HT205234, 2020. [Online; accessed 23-March-2022].

[56]

Google Developers. Power management | Android Developers. https://developer.android.com/about/versions/pie/power, 2021. [Online; accessed 23-March-2022].

[57]

Samsung. What is Power saving mode on my Galaxy phone? https://www.samsung.com/latin_en/support/mobile-devices/what-is-power-saving-mode-on-my-galaxy-phone/, 2022. [Online; accessed 05-April-2023].

[58]

Patrick Schober, Christa Boer, and Lothar A Schwarte. Correlation coefficients: appropriate use and interpretation. Anesthesia & Analgesia, 126(5):1763--1768, 2018.

[59]

BloombergNEF. Battery pack prices fall to an average of $132/kwh, but rising commodity prices start to bite. https://about.bnef.com/blog/battery-pack-prices-fall-to-an-average-of-132-kwh-but-rising-commodity-prices-start-to-bite, 2021. [Online; accessed 05-April-2023].

[60]

Apple. About Optimised Battery Charging on your iPhone. https://support.apple.com/en-au/HT210512, 2023. [Online; accessed 05-April-2023].

Cited By

Lee SJeong DChoi JKwak JSon SSong JShin I(2024)SERENUS: Alleviating Low-Battery Anxiety Through Real-time, Accurate, and User-Friendly Energy Consumption Prediction of Mobile ApplicationsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676437(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676437
Swapnil AMetso LOruganti KHapponen A(2024)Driving the Future: Utilizing Software Foundations to Improve Vehicles Functionalities2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)10.1109/ICECCME62383.2024.10796847(1-7)Online publication date: 4-Nov-2024
https://doi.org/10.1109/ICECCME62383.2024.10796847

Index Terms

MixMax: Leveraging Heterogeneous Batteries to Alleviate Low Battery Experience for Mobile Users

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cover image ACM Conferences

MobiSys '23: Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services

June 2023

651 pages

ISBN:9798400701108

DOI:10.1145/3581791

General Chairs:
Petteri Nurmi,
Pan Hui,
Program Chairs:
Ardalan Amiri Sani,
Yunxin Liu

Copyright © 2023 ACM.

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Published: 18 June 2023

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MobiSys '23: 21st Annual International Conference on Mobile Systems, Applications and Services

June 18 - 22, 2023

Helsinki, Finland

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MobiSys '23 Paper Acceptance Rate 41 of 198 submissions, 21%;

Overall Acceptance Rate 274 of 1,679 submissions, 16%

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Cited By

Lee SJeong DChoi JKwak JSon SSong JShin I(2024)SERENUS: Alleviating Low-Battery Anxiety Through Real-time, Accurate, and User-Friendly Energy Consumption Prediction of Mobile ApplicationsProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676437(1-20)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676437
Swapnil AMetso LOruganti KHapponen A(2024)Driving the Future: Utilizing Software Foundations to Improve Vehicles Functionalities2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)10.1109/ICECCME62383.2024.10796847(1-7)Online publication date: 4-Nov-2024
https://doi.org/10.1109/ICECCME62383.2024.10796847

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