Title :
Model-Based Dynamic Power Assessment of Lithium-Ion Batteries Considering Different Operating Conditions
Author :
Xiaosong Hu ; Rui Xiong ; Egardt, Bo
Author_Institution :
Dept. of Signals & Syst., Chalmers Univ. of Technol., Gothenburg, Sweden
Abstract :
This paper is concerned with model-based dynamic peak-power evaluation for LiNMC and LiFePO4 batteries under different operating conditions. The battery test and our prior study on linear-parameter-varying (LPV) battery modeling are briefly introduced. The peak-power estimation method that incorporates an explicit prediction horizon and design constraints on the battery current, voltage, and SOC are elaborated, and its computational load is analyzed. The discharge and charge peak powers are quantitatively assessed under different dynamic characterization tests, in which a comparison with the conventional PNGV-HPPC method and approaches using the less accurate models is conducted. The robustness of the peak-power estimation approach against varying battery temperatures and aging levels is investigated. The methods to improve the credibility of the peak-power assessment in the context of battery degradation are explored.
Keywords :
battery management systems; iron compounds; lithium compounds; secondary cells; LPV battery modeling; LiFePO4; SOC; battery current; battery test; battery voltage; design constraints; explicit prediction horizon; linear parameter-varying battery modeling; lithium-ion battery; model-based dynamic power assessment; peak power estimation method; Battery management systems; Electric vehicles; Lithium batteries; Load modeling; Vehicle dynamics; Battery management system; Li-ion battery; battery modeling; electrified vehicle; peak-power assessment;
Journal_Title :
Industrial Informatics, IEEE Transactions on
DOI :
10.1109/TII.2013.2284713