Estimation method of real-time full charge time of battery based on EKF-GPR and daily fragment data
A technology of data and fragments, applied in the field of estimation of battery real-time full charge time, can solve problems such as cumbersome process, difficult measurement and recording, long cycle, etc., and achieve the effect of reducing prediction error
Active Publication Date: 2019-04-16
SHENZHEN ACAD OF METROLOGY & QUALITY INSPECTION +1
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[0005] The present invention aims at the defects of long period, cumbersome process, difficult measurement and recording and poor practicability of the existing battery real-time full charge time estimation method, and provides a battery with short measurement period, simple process, easy measurement and recording, and strong practicability Estimation method of real-time full charge time
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Embodiment 1
[0052] combine figure 1 Describe the present embodiment, in the present embodiment, the method for estimating the real-time full charge time of the battery based on EKF-GPR and daily fragment data involved in the present invention, it includes the following steps:
[0053] Step 1. Initialization: constant current charging current I, constant voltage charging cut-off voltage V, initial cycle loop 0 , full charge data d under initial constant current charge 0 =(t 0 (k), v 0 (k)), k=1,2,...,n 0 , n 0 is the total sampling time points when the battery reaches the constant voltage charging cut-off voltage V under constant current charging current I charging, t 0 (k) is the discrete relative time of equal interval sampling, sampling time interval ΔT=t 0 (k+1)-t 0 (k) is a constant, v 0 (k) represents the voltage of the kth sampling point; the initial state matrix A of the extended Kalman filter 0 ;
[0054] Step 2, Gaussian process regression: use the covariance function o...
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The invention, which belongs to the field of the method for estimating the real-time full charge time of the battery, relates to an estimation method of real-time full charge time of a battery based on EKF-GPR and daily fragment data. In order to overcome defects in the prior art, the invention provides an estimation method of real-time full charge time of a battery, wherein the method has advantages of having a short measurement period, carrying out a simple process, being convenient to measure and record, and having high practicability. According to the invention, initial assignment is performed, Gaussian process regression is performed on the full charge data of constant-current charging, and the an initial hyper-parameter is calculated; secondary fragment data are extracted, a state vector is initialized to be first-time full charge time by using the first-time full charge data as an initial value of the state, extended Kalman filtering-Gaussian process regression is carried out onthe current-times fragment data, and full charge time needed by current-times constant-current charging is estimated; extended Kalman filter cyclic recursion is carried out; full charge time is predicted; full charge time of secondary fragment data is calculated; and updating cycling is carried out; to be specific, assignment is carried out, calculation is carried out, and steps from the step twoto the step five are repeated. The method is mainly used for estimating the real-time full charge time of the battery.
Description
technical field [0001] The invention belongs to a method for estimating the real-time full charging time of a battery. Background technique [0002] In the electric vehicle battery management system, the real-time monitoring of the state-of-health (SOH) of the power lithium battery can accurately reflect the current capacity of the battery, and can make timely preparations for maintenance or replacement, effectively discovering and avoiding battery failure. The unsafe behavior provides guarantee for the stability of the power battery. The state of health of the battery, SOH, is also called the state of life. It is an indicator that characterizes the aging and deterioration of the battery during long-term use. It is usually based on the actual value of some directly measurable or indirectly calculated performance parameters after the battery has been used for a period of time. Estimation of the ratio to the nominal value. SOH is affected by many factors and is related to th...
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Login to View More IPC IPC(8): G01R31/387G01R31/367
Inventor 卢文斌周頔陈锐衡
Owner SHENZHEN ACAD OF METROLOGY & QUALITY INSPECTION