Novel SOC Monitoring Approach for Lithium Batteries
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abstract
The key element in storage based systems remains the ability to monitor, control
and optimise the performance of one or more modules of these batteries, the type of device
performing this task is often referred to as a Battery Management System (BMS). A BMS is a
basical units of electrical energy storage systems, a variety of already developed algorithms can
be applied to define the main states of the battery, among others: state of charge (SOC), state
of health (SOH) and state of functions (SOF) that allow real-time management of the batteries.
All research in the field of Extended Kalman Filter (EKF) based BMS is based on bench-scale
experiments using powerful softwares, such as MATLAB, for data processing and controllers such
as dSPACE. So far, the constraint of computational power limitation is not really addressed in
the majority of scientific papers dealing with this subject. This paper proposes an approach to
implement an extended Kalman filter linked to a Coulomb counting method, this method called
DCC-EKF will allow a better quality monitoring of the battery.
