A Method for Estimating the Remaining Battery Power of an Electric Vehicle Battery Management System

Abstract

The invention discloses a battery remaining capacity estimation method for an electric car battery management system. The method comprises the following steps of initializing the initial battery remaining capacity of a battery; predicting the remaining battery capacity of the battery at a next moment by adopting an ampere-hour current integral method so as to obtain a current polarization state through a current polarization model; estimating an open-circuit voltage according to an open-circuit voltage model; estimating the battery voltage; comparing the real sampled voltage and the estimated battery voltage, and calculating a voltage error; acquiring the corrected remaining battery capacity by adopting a kalman filter model; and introducing a temperature and battery service life compensation strategy, and estimating the remaining battery capacity according to the corrected remaining battery capacity. By adopting the method, the calculation complexity and the requirement on the battery model precision can be alleviated, and the method is particularly suitable for estimating the remaining battery capacity of the electric car power battery under relatively wicked environmental factors such as severe discharging current variation and the temperature.

Description

technical field [0001] The invention relates to the field of vehicle energy and vehicle state monitoring, in particular to a method for estimating remaining battery power used in a battery management system (BMS) of an electric vehicle. Background technique [0002] Accurately estimating the battery's state of charge (SOC) helps avoid battery overcharging and overdischarging, preventing battery damage or rapid aging. The traditional method of estimating the remaining battery capacity using the ampere-hour current integration method (AH) will cause the problem of error accumulation, resulting in inaccurate estimation. In addition, chemical reactions inside the battery under charging and discharging conditions can cause temperature increases, which can affect the estimation of the battery's remaining capacity. Therefore, an accurate battery remaining capacity estimation algorithm depends on a complete battery model. For electric vehicles or hybrid vehicles, a large number of...

AI Technical Summary

Problems solved by technology

[0004] The output error of existing estimation methods based on open-loop models can hardly be suppressed or eliminated

As time goes by, the error will continue to accumulate and lead to the generation of error information. Although the commonly used closed-loop algorithms based on the Kalman filter method will not accumulate errors, the relative accuracy is relatively high, which can effectively reflect the working status of the battery pack and reduce overcharging. And the chance of over-discharge, and can automatically estimate the dynamic error range, but the calculation complexity of the algorithm is high and the accuracy of the battery model of the system is very high

Images