Nelder-Mead Simplex Algorithm for Age-dependent Parameter Estimation of a Lithium-ion Electrochemical Battery Model

The proliferation and prevalence of lithium ion batteries has produced a surge in research into electrochemical cell models and the identification of specific unknown cell parameters. Accordingly, optimization methods have become an area of intense investigation for their inherent ability to search problem spaces for model parameters. With the ability to calculate lithium ion cell properties in real time, Battery Management Systems (BMS) would exhibit vast improvements in decision making for prolonging batteries' life span and increasing efficient charging/discharging. The paper analyses the use of Nelder-Mead Simplex algorithm for identifying three age-dependent parameters of a electrochemical cell model. Results indicate accurate parameter identification for simulation and ex-perimental environments. With real time voltage measurements, the applications such as electric vehicles and large power grid batteries would greatly benefit from the use of Nelder- Mead Simplex mentioned throughout this paper.