Online Identification of Thevenin Equivalent Circuit Model Parameters and Estimation State of Charge of Lithium-Ion Batteries

Abstract

On Electrical and Hybrid Vehicles (EVs, HEVs), energy is stored in accumulators, mainly electro-chemical batteries. A reliable and cost effective management of energy storage system is a key point for the development of such devices, their durability and for vehicle performance optimization. This requires the accurate estimation of the battery state over time and in a wide range of operating conditions. The battery state is usually expressed as State Of Charge (SOC) and State Of Health (SOH). Their estimations requires an accurate model to represent the static and dynamic behaviors of the battery. This paper presents a model adaptive Unscented Kalman Filter (UKF) method to estimate online SOC of Li-ion batteries. The proposed approach uses a Recursive Least Squares method to update the UKF model parameters during a discharge period. The effectiveness of the method has been verified based on real data acquired from five LiFePO4 battery packs installed on a working EV.

Energy Storage System optimization for an Autonomous SailBoat

“…In particular, LiFePO4 technology was chosen for its absolute reliability in terms of thermal and chemical stability. This is a feature confirmed by previous experience in the automotive sector [16] [17] which is fundamental to assure the required reliability respect to variable and probably hard environmental conditions.…”

Online State of Health Estimation of Lithium-Ion Batteries Based on Improved Ampere-Count Method

“…In particular, value of internal resistance depends from actual SOC of cell and the surrounding temperature. In [9] is realized an appropriately surface function R int = Υ(SOC, T ) which returns the value of the internal resistance R int in function of the SOC and the surrounding temperature. Coefficients of this surface function are sized using Curve Fitting Toolbox of Matlab, and are identified based on real data acquired from LiFePO4 battery packs (composed by 30 CALB cells in series) installed on a EV and online estimation algorithms shown in [9].…”

“…Exchanges of heat flows between the surface (T sur ) of the cell and the surrounding environment (T ) are represented by R th,sur , C th,sur parameters. Thermal parameters are sized during phase recharging, analyzing real internal temperature data acquired on battery packs [9]. In particular thermal capacity and resistance are sized using thermodynamics equations:…”

Application of Wireless Power Transfer to Railway Parking Functionality: Preliminary Design Considerations with Series-Series and LCC Topologies

“…(iii) Improved cooling (a better or more sophisticated thermal design of the system). (iv) Advanced power conversion stages for a more flexible control of the whole system; this feature it is very important in order to better adapt recharge functionality to battery SOC [30] (State of Charge) and SOH [31] (State of Health).…”