A power lithium battery model parameter identification and remaining power estimation method

Abstract

The invention discloses a power lithium battery model parameter identification and remaining power estimation method, step 1: establish the state space equation of the second-order impedance-capacitance model of the lithium battery; step 2: establish the relationship between the terminal voltage and the open circuit voltage with respect to the current Regression model; Step 3: Carry out parameter identification based on iterative learning-based recursive least squares method for the regression model; Step 4: Use recursive learning-based recursive least squares method on the experimental data of the discharge current condition by using the parameter identification process satisfying step 3 The identification method obtains the prediction error, and the nonlinear function and parameter set in the parameters of the state space equation are obtained through the convergence of the prediction error; Step 5: Verify the accuracy of the battery model composed of the nonlinear function and parameter set obtained in Step 4; Step 6: Collect the current and voltage data, the remaining power is estimated through the extended Kalman filter; the invention has high accuracy of model parameter identification, small error in the estimated value of the remaining power, and has good application prospects.

Description

technical field [0001] The invention relates to the technical field of new energy vehicle battery management, in particular to a power lithium battery model parameter identification and remaining power estimation method. Background technique [0002] In the State Council's "Thirteenth Five-Year Plan" national science and technology innovation plan, the development of new energy vehicles is the first project to establish and improve the core technology system of transportation. my country mainly promotes pure electric vehicles in the development of new energy vehicles, and power lithium batteries are the core energy source of pure electric vehicles. The remaining power of the lithium battery, that is, the percentage of the available capacity to the rated capacity, is an important parameter to ensure the safe operation of the lithium battery and prolong the available life. The complexity of the electrochemical reaction inside the lithium battery causes the strong nonlinearity...

AI Technical Summary

Problems solved by technology

However, for lithium batteries, due to the internal strong nonlinear characteristics, its model parameters will inevitably not be time-invariant and slowly time-varying. The problem of reduced modeling accuracy has become the main factor causing inaccurate estimation of remaining power

Images