A Wavelet Network based Model for Ni-Cd Batteries

Ni-Cd batteries are nonlinear electrochemical devices with different characteristics at different charge currents. This paper proposes a wavelet network based method for simulation and modeling of Ni-Cd batteries that considers the impact of charge current. It does not have the limitations associated with traditional neural networks or neuro-fuzzy-based algorithms such as convergence to local optimum points, over-fit and/or under-fit problems. Simulations and measurements are performed for the wavelet network and advantages of the model are presented. Inputs of the wavelet network are battery current (Ibat ), no load voltage and time (t) while battery voltage (Vbat) is selected as the output. An experimental setup is used to validate the accuracy of the model at different charge rates. Computed and measured results show good agreements for a 7AH, size F, Ni-Cd battery, manufactured by SANYO. Theoretical and experimental results are compared and analyzed.