A linear recursive state of power estimation method based on fusion model of voltage and state of charge limitations

As the main candidate of energy storage system for electric vehicles and hybrid electric vehicles, lithium-ion battery has attracted extensive attention. The working characteristics of the battery under dynamic stress stimulation are complex and changeable. To solve the problem of high-precision state of power estimation, a fusion model based on adaptive forgetting factor recursive least squares identification and voltage and charge state constraints was proposed, and a continuous discharge state of power analysis model for lithium-ion batteries was established. The adaptive forgetting factor recursive least square method based on battery model provides accurate and reliable online parameter identification feedback. The results show that the accuracy error of online parameter identification is less than 0.02V; the combination of the linear recursive algorithm of state of power analysis and the fusion model of voltage and current limit makes the power state estimation more reliable and accurate. The results show that when the battery is t=10s, the peak discharge power error is less than 80W.

Automated summary

The study proposed a fusion model based on adaptive forgetting factor recursive least squares identification and voltage and charge state constraints, established a continuous discharge state of power analysis model for lithium-ion batteries, and provided accurate and reliable online parameter identification feedback, making the power state estimation more reliable and accurate.