A novel equivalent modeling method combined with the splice‐electrochemical polarization model and prior generalized inverse least‐square parameter identification for UAV lithium‐ion batteries

Abstract

The accuracy of lithium-ion battery state estimation is critical to the safety of unmanned aerial vehicles (UAVs). In this paper, aiming at the high-fidelity modeling of the UAV lithium-ion battery, a splice-electrochemical polarization model (S-EPM) for UAV lithium-ion battery is constructed by combining the traditional electrochemical model with the equivalent circuit model, which greatly improved the accuracy of the battery modeling. In addition, a novel prior generalized inverse least-squares algorithm is proposed. Also, based on this algorithm, the full-parameter identification and multicondition error analysis of the S-EPM are realized based on this algorithm. Finally, a targeted complex discharge rate test and a full-function charge-discharge test were designed to further verify the applicability of the S-EPM to complex conditions. The experimental results show that the voltage error of the model under each working condition is 5.50 and 3.0 mV, and the maximum percentage error ratio is 0.20% and 0.07%. This experiment can provide a theoretical basis for the combination of the electrochemical model and equivalent circuit model and the accurate estimation of internal state variables of lithium-ion batteries.improve the Nernst model, lithium-ion batteries, parameter identification, prior generalized inverse least square, splice-electrochemical polarization model | INTRODUCTIONThe power battery system is one of the most important components of an unmanned aerial vehicle (UAV), which has a great impact on the performance and safety of the whole aircraft. 1 The lithium-ion battery has become the most widely used power battery for aircraft due to its excellent performance. For UAVs, the highperformance battery management system can not only ensure the timeliness of the drone flight but also extend Energy Sci. Eng.

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“…In recent years, research on new energy batteries has continued to strengthen, the energy density of batteries has continued to increase [14][15][16][17][18] and the production cost has dropped significantly. In particular, the emergence of lithium-ion batteries has become a hot spot for new energy batteries [19][20][21][22]. How to improve the performance of battery packs and reduce the use cost are the research focus of new energy batteries [23][24][25].…”