Experimental Analysis of Open-Circuit Voltage Hysteresis in Lithium-Iron-Phosphate Batteries

This paper aims at investigating and modelling the hysteresis in the relationship between state-of-charge and open-circuit voltage of lithium-iron-phosphate batteries. A first-order charge relaxation equation was used to describe the hysteresis dynamics. This equation was translated into a voltage-controlled voltage source and included within an equivalent electric circuit of the battery used in online state-of-charge estimators. The effectiveness of the obtained battery model was verified comparing simulated and experimental data

Smart LiFePO4 battery modules in a fast charge application for local public transportation

This paper describes the research effort jointly carried out by the University of Pisa and ENEA on electrochemical energy storage systems based on Lithium-ion batteries, particularly the Lithium-Iron-Phosphate cells. In more detail, the paper first illustrates the design and experimental characterization of a family of 12 V modules, each of them provided with an electronic management system, to be used for electric traction. Then, the sizing of the energy storage system for an electric bus providing a service with 'fast and frequent' charge phases is described

Estimation of state of charge of lithium-ion battery based on photovoltaic generation energy storage system

Brza i točna procjena stanja naboja - state of charge (SOC) litij-ion baterije jedna je od ključnih tehnologija sustava za praćenje stanja baterije. Imajući u vidu nelinearni dinamički sustav litij baterije, u ovom je radu postavljen RC model histereze drugog reda ispitivanjem i analizom karakteristika histereze litij-ion baterije, a kubatura algoritma Kalmanovog filtra primijenjena je za procjenu stanja naboja baterije. Rezultati eksperimenta pokazuju da se modelom baterije može predvidjeti dinamičko ponašanje naboja histereze litij-ion baterije, a algoritmom kubature Kalmanovog filtriranja održati visoka točnost u postupku procjene.The fast and accurate estimation of state of charge (SOC) of lithium-ion battery is one of the key technologies of battery management system. In view of this nonlinear dynamic system of lithium battery, through the test and analysis of lithium-ion battery hysteresis characteristics, the second-order RC hysteresis model is established, and the cubature Kalman filter algorithm is used to estimate the battery state of charge in this report. The experiment results show that the battery model can essentially predict the dynamic hysteresis voltage behavior of the lithium-ion battery and cubature Kalman Filtering algorithm can maintain high accuracy in the estimation process

A Lithium Battery Current Estimation Technique Using an Unknown Input Observer

Current consumption measurements are useful in a wide variety of applications, including power monitoring and fault detection within a lithium battery management system (BMS). This measurement is typically taken using either a shunt resistor or a Hall-effect current transducer. Although both methods have achieved accurate current measurements, shunt resistors have inherent power loss and often require isolation circuitry, and Hall-effect sensors are generally expensive. This work explores a novel alternative to sensing battery current by measuring terminal voltages and cell temperatures and using an unknown input observer (UIO) to estimate the battery current. An accurate model of a LiFePO4 cell is created and is then used to characterize a model of the proposed current estimation technique. Finally, the current estimation technique is implemented in hardware and tested in an online BMS environment. Results show that the current estimation technique is sufficiently accurate for a variety of applications including fault detection and power profiling