IDENTIFICATION, ESTIMATION, AND FAULT DIAGNOSTICS OF BATTERY PDE MODELS
Topic: Identification | All
Séance du mercredi 10 janvier 2018, Salle V106B, 14h00-16h00.
15h00 : Scott MOURA, eCAL, University of California, Berkeley
Batteries are ubiquitous. However, today’s batteries are expensive, range-limited, power-restricted, die too quickly, charge too slowly, and susceptible to safety issues. For this reason, model-based battery management systems (BMS) are of extreme interest. In this talk, we discuss eCAL’s recent research electrochemical-based BMS, which are modeled by nonlinear partial differential equations (PDEs). Specifically, we discuss (i) optimal experiment design for parameter identification, (ii) state/parameter estimation, and (iii) fault diagnostics. Finally, we close with exciting new perspectives for next-generation battery systems.
15h00 : Scott MOURA, eCAL, University of California, Berkeley
Batteries are ubiquitous. However, today’s batteries are expensive, range-limited, power-restricted, die too quickly, charge too slowly, and susceptible to safety issues. For this reason, model-based battery management systems (BMS) are of extreme interest. In this talk, we discuss eCAL’s recent research electrochemical-based BMS, which are modeled by nonlinear partial differential equations (PDEs). Specifically, we discuss (i) optimal experiment design for parameter identification, (ii) state/parameter estimation, and (iii) fault diagnostics. Finally, we close with exciting new perspectives for next-generation battery systems.