arrow
Return

Optimal Scheduling for Active Cell Balancing

delete2019-12-01
delete3
PRE
AI
D
Debayan Roy *
S
Swaminathan Narayanaswamy
A
Alma Proebstl
S
Samarjit Chakraborty
DOI:10.1109/RTSS46320.2019.00021delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Active cell balancing is performed to minimize the variation in the charge levels of the individual cells in a high-power battery pack, to improve its usable capacity. The process of charge equalization is carried out by scheduling pairs of cells to transfer charge over a hardware circuit. Improving the time for charge equalization has been studied in the power electronics and the electronic design automation domains. However, these approaches have focused on the electronics issues and used heuristics to determine the charge transfer schedule. Hence, no optimality results on charge equalization times are known. We, for the first time, take a real-time systems approach and propose an optimal scheduling framework for active cell balancing. The proposed framework employs a hybrid optimization technique consisting of two sequential stages. In the first stage, we solve a mixed-integer linear programming problem to identify the time-optimal set of charge transfers required to achieve charge equalization. In the second stage, we construct a conflict graph based on the obtained charge transfers, to which we apply the minimum vertex coloring algorithm to synthesize the minimum length schedule. Results show that our proposed framework can reduce the charge equalization time by more than 50% (e.g., from 11 h to 5h). Hence, this has real benefits, e.g., in the context of charging electric vehicles. While task and message scheduling problems have been extensively studied in the real-time systems literature, the scheduling problem we study here, has not been addressed before.
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

I
IEEE Real-Time Systems Symposium
IF:
0
Papers:
10
Citations:
0

Organization

T
Technical University of Munich
Scholars:
5.2W
Papers: 3.9W
Citations: 6.2W
Cited Papers

Cited Papers

Performance comparison of active balancing techniques for lithium-ion batteries
err2014-12-01
err151
errOAAI
errBaronti, Federico; Roncella, Roberto; Saletti, Roberto
errShare
errSave
An Optimized Topology for Next-to-Next Balancing of Series-Connected Lithium-ion Cells
err2014-09-01
err183
PREAI
errThanh Hai Phung; Collet, Alexandre; Crebier, Jean-Christophe
errShare
errSave
Decentralized Non-Neighbor Active Charge Balancing in Large Battery Packs
err2019-03-01
err2
PREAI
errLamprecht, Alexander; Baumann, Martin; Massier, Tobias; Steinhorst, Sebastian
errShare
errSave
Smart backpack for visually impaired person
err2013-06-01
err0
PREAI
errJin-hee Lee; Kyeongyul Kim; Sang-Chul Lee; Byeong-Seok Shin
errShare
errSave
Cardiovascular disease risk factor variables at the preschool age. The Bogalusa heart study.
err1978-03-01
err0
errOAAI
errG S Berenson; T A Foster; G C Frank; R R Frerichs; S R Srinivasan; A W Voors; L S Webber
errShare
errSave
Battery- and Aging-Aware Embedded Control Systems for Electric Vehicles
err2014-12-01
err14
PREAI
errChang, Wanli; Proebstl, Alma; Goswami, Dip; Zamani, Majid; Chakraborty, Samarjit
errShare
errSave
researcher View more