Analysis of Lithium-Ion Battery Management System and Degradation Mechanism
- Type: Conference Presentation
AIChE Member Credits 0.5 AIChE Members $19.00 AIChE Graduate Student Members Free AIChE Undergraduate Student Members Free Computing and Systems Technology Division Members Free Non-Members $29.00
- Conference Type: AIChE Spring Meeting and Global Congress on Process Safety
- Presentation Date: April 11, 2022
- Duration: 30 minutes
- Skill Level: Intermediate
- PDHs: 0.50
Electrochemical models (EM) play a major role in the future BMS. EMâs are based on physiochemical mechanisms, resulting in a more accurate prediction while describing the internal states of the battery at wider operating ranges. However, the governing equations are non-linear and have multiple partial differential equations (PDE) that make them computationally expensive. Moreover, a large number of physical parameters are required which are often dependent on composition and temperature (e.g. thermodynamic potential, ionic conductivity, diffusion coefficient, transference number). Estimating these parameters with achievable accuracy continues to be a challenging job.
This study addresses two pivotal questions â how can we reduce or transform the complex full order EM maintaining the same accuracy at a wider operating window? We explore the suitability of different methods to convert PDEâs (e.g. Finite Element Method, Pade approximation, Orthogonal decomposition, etc.) into simpler equations. Secondly, how to systematically estimate parameters without information loss? Parameter estimation techniques (e.g. Fisher Information Matrix, Particle Swarm Optimization, Genetic Algorithm) are studied to characterize the battery degradation and shed light on the cause-effect mechanisms.
|AIChE Member Credits||0.5|
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|
|Computing and Systems Technology Division Members||Free|