SOC (State of Charge) and SOH (State of Health) prediction method of electric vehicle-mounted lithium iron phosphate battery

Abstract

The invention discloses an SOC (State of Charge) and SOH (State of Health) prediction method of an electric vehicle-mounted lithium iron phosphate battery, which comprises the following steps of: (a) improving a Thevenin cell equivalent model; (b) determining the state equation and the output equation of a system; (c) identifying battery model parameters; (d) using a Kalman filter algorithm to iterate the state variables of the system, so that the predictive value of SOC is closer to the actual value; and (e) using a dual-channel Kalman filter algorithm to carry out the online predication of an internal resistance and capacity of the lithium iron phosphate battery, and simultaneously predicating the SOH of the battery according to the changes in the internal resistance and the capacity value of the battery in the current state and the initial state. With the method, the predication precision of SOH of the battery is effectively improved, the decline in battery performance can be determined more accurately, and the internal resistance and capacity information of the battery is combined to provide a basis for making the battery management strategy and maintaining and replacing the battery.

Description

technical field [0001] The invention relates to the field of battery management systems, in particular to a method for predicting SOC and SOH of a lithium iron phosphate battery mounted on an electric vehicle. Background technique [0002] state of charge SOC Refers to the remaining capacity of the battery when it has been used for a period of time or left unused for a long period of time. Charge When the ratio of the rated capacity, usually expressed as a percentage, SOC =100% means the battery is fully charged, SOC =0% means the battery is empty. Whether the SOC of the battery can be accurately estimated is one of the key points and difficulties in the study of battery management systems. The reason why SOC is difficult to estimate is: (1) The working state of the battery is complex, it is often on, often off, often off and then on, and the time between them is difficult to determine, all of which can affect SOC Prediction. (2) The capacity of the battery itself is...

AI Technical Summary

Problems solved by technology

[0057] The invention provides a method for predicting SOC and SOH of a lithium iron phosphate battery on-board an electric vehicle, which solves the problem that in the previous SOC prediction process, the obtained SOC prediction value is inaccurate and cannot provide a reliable basis for the formulation of active balancing technology and battery management strategy. Based on the question

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