Standardized Computational Complexity Evaluation for Battery State-of-Charge Estimation Algorithms
To fairly assess the performance of battery state of charge estimation algorithms, a standardized evaluation method is required. This paper expands on a previously proposed evaluation method by including a measurement of computational complexity. Since traditional complexity metrics, such as computation time, may vary across devices and over time, this paper proposes a specialized metric to categorize computational complexity: approximate operational effort (AOE). AOE is determined by running the algorithm and a standard mathematical and memory operation on a device such as a PC and normalizing run time based on these operations. AOE is measured on three different devices for four algorithms, and is shown to decrease the variability between devices from a factor of ten to less than four, which is sufficient to differentiate algorithm performance across devices. The algorithms are also deployed to a microcontroller to compare with the PC based complexity measurement.
Authors
- M.C.F. Donkers (ORCID: https://orcid.org/0000-0003-1465-5529)
- Phillip J. Kollmeyer (ORCID: https://orcid.org/0000-0003-3576-672X)
- Atjen von Liebenstein
Institutions
- Eindhoven University of Technology (NL)
- McMaster University (CA)
Publication Details
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1109/itec63604.2025.11098050
- Primary Topic
- Advanced Battery Technologies Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00