Unscented particle filtering method for SOC estimation of lithium ion battery pack of large unmanned aerial vehicle
A lithium-ion battery pack, traceless particle filtering technology, applied in computer-aided design, computing, electrical digital data processing and other directions, can solve problems such as reducing use efficiency, intensifying inconsistency, and shortening battery life.
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[0049] An unscented particle filter method for SOC estimation of lithium-ion battery packs for large unmanned aerial vehicles, comprising the following steps:
[0050] S01. Construct a battery model according to the relationship between the influencing factors of the SOC of the lithium-ion battery pack and the internal nonlinear operating characteristics due to parameter coupling, wherein the specific circuit of the electromagnetic model is as follows Figure 1-Figure 4 shown;
[0051] S02. Collect and integrate various data of the battery pack;
[0052] S03, the integrated data uses the mean value and variance obtained by the unscented Kalman filter algorithm to update the particle set in the particle filter algorithm sampling;
[0053] S04. Predict the working characteristics of the lithium-ion battery pack according to the calculation in step S03.
[0054] In another embodiment, the particle filter algorithm in step S03 includes the following steps:
[0055] S31. Initial...
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