State Of Health (SOH) is one of the most important parameters in order to evaluate battery performances over time and it has profound impact on performances, cost and reliability of the target vehicle. SOH definition requires an accurate estimation of the actual battery energy storage capacity at low frequencies. This paper presents an improved Ampere-Count Method based on Incremental Capacity Analysis in a particular voltage range delivered by battery for SOH estimation. Proposed method is implemented using Matlab Software, and its effectiveness has been verified based on simulated data from thermo-electrical model of LiFePO4 cell with aging phenomena realized on Siemens Amesim software. Model was calibrated with data provided by manufacturer and based on real data acquired from LiFePO4 battery packs installed on a Electric Vehicle (EV).

Online State of Health Estimation of Lithium-Ion Batteries Based on Improved Ampere-Count Method / Locorotondo, Edoardo; Pugi, Luca; Berzi, Lorenzo; Pierini, Marco; Pretto, Alessandro. - ELETTRONICO. - (2018), pp. 1-6. (Intervento presentato al convegno 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)) [10.1109/EEEIC.2018.8493825].

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

Locorotondo, Edoardo
;
Pugi, Luca;Berzi, Lorenzo;Pierini, Marco;
2018

Abstract

State Of Health (SOH) is one of the most important parameters in order to evaluate battery performances over time and it has profound impact on performances, cost and reliability of the target vehicle. SOH definition requires an accurate estimation of the actual battery energy storage capacity at low frequencies. This paper presents an improved Ampere-Count Method based on Incremental Capacity Analysis in a particular voltage range delivered by battery for SOH estimation. Proposed method is implemented using Matlab Software, and its effectiveness has been verified based on simulated data from thermo-electrical model of LiFePO4 cell with aging phenomena realized on Siemens Amesim software. Model was calibrated with data provided by manufacturer and based on real data acquired from LiFePO4 battery packs installed on a Electric Vehicle (EV).
2018
2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Locorotondo, Edoardo; Pugi, Luca; Berzi, Lorenzo; Pierini, Marco; Pretto, Alessandro
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1142803
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