System on chip (SOC) estimation method for lithium ion battery and hardware implementation of estimation method

Abstract

The invention discloses a system on chip (SOC) estimation method for a lithium ion battery. The method comprises the following steps: 1, performing SOC real-time update; 2, introducing a dynamic variable; 3, identifying parameters in a battery circuit model; 4, realizing SOC estimation of the lithium ion battery by using an unscented Kalman filter algorithm according to the identified model parameters; 5, implementing the SOC estimation algorithm of the lithium ion battery based on the unscented Kalman filter. The method disclosed by the invention has the following advantages: (1), an improved second order RC equivalent circuit considers the rate capacity effect and recovery effect of the lithium ion battery compared with other circuit models, and compared with the traditional second order equivalent circuit, the dynamic and static characteristics of the battery are well simulated; (2), compared with the other algorithms, the unscented Kalman filter algorithm is low in initial value dependence, accurate in prediction and capable of well solving the nonlinear problem; (3), by utilizing the characteristics of flexibility and convenience of Xilinx FPGA development, the SOC estimation algorithm of the lithium ion battery is implemented on a hardware platform, so that the algorithm is not only theoretical, but also can be applied to portable equipment.

Description

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AI Technical Summary

Benefits of technology

The technical effect of this patented method compared to existing methods described earlier can be improved accuracy over time by utilizing flexibility or convenience features provided by an xilinx chip design that works well even when used at different times during battery life cycles.

Problems solved by technology

This patents discusses different techniques related to improving Lithium ion cell performance models. One technique involves analyzing how much energy storage occurs during its operation cycle compared to what happens at rest. Another approach focuses on understanding factors like environmental effects and battery's ability to recover their potential function effectively. Overall, both technical problem addressed by the present researchers include developing efficient ways to estimate battery status and determine long term operational times based upon specific parameters.

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