Accelerated Battery Lifetime Simulations Using Adaptive Inter-Cycle Extrapolation Algorithm
Author(s) -
Valentin Sulzer,
Peyman Mohtat,
Sravan Pannala,
Jason B. Siegel,
Anna G. Stefanopoulou
Publication year - 2021
Publication title -
journal of the electrochemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.258
H-Index - 271
eISSN - 1945-7111
pISSN - 0013-4651
DOI - 10.1149/1945-7111/ac3e48
Subject(s) - extrapolation , battery (electricity) , algorithm , computer science , degradation (telecommunications) , transient (computer programming) , mathematics , physics , statistics , thermodynamics , telecommunications , power (physics) , operating system
We propose algorithms to speed up physics-based battery lifetime simulations by one to two orders of magnitude compared to the state-of-the-art. First, we propose a reformulation of the Single Particle Model with side reactions to remove algebraic equations and hence reduce stiffness, with 3x speed-up in simulation time (intra-cycle reformulation). Second, we introduce an algorithm that makes use of the difference between the “fast” timescale of battery cycling and the “slow” timescale of battery degradation by adaptively selecting and simulating representative cycles, skipping other cycles, and hence requires fewer cycle simulations to simulate the entire lifetime (adaptive inter-cycle extrapolation). This algorithm is demonstrated with a specific degradation mechanism but can be applied to various models of aging phenomena. In the particular case study considered, simulations of the entire lifetime are performed in under 5 s. This opens the possibility for much faster and more accurate model development, testing, and comparison with experimental data.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom