A fast capacity estimation method based on open circuit voltage estimation for LiNixCoyMn1-x-y battery assessing in electric vehicles

2020 ◽  
Vol 32 ◽  
pp. 101830
Author(s):  
Zheng Zhou ◽  
Yifan Cui ◽  
Xiangdong Kong ◽  
Jiaqi Li ◽  
Yuejiu Zheng
Keyword(s):  
Electric Vehicles ◽  
Open Circuit Voltage ◽  
Estimation Method ◽  
Open Circuit ◽  
Capacity Estimation

A Novel Design of SOC Prediction for an Electrical Vehicle Based on the Intelligent Algorithm

2012 ◽  
Vol 468-471 ◽  
pp. 601-606 ◽  
Author(s):  
Hao Qiu ◽  
Zheng Bao Lei ◽  
Tom Zi Ming Qi
Keyword(s):  
Neural Network ◽  
Electric Vehicles ◽  
Open Circuit Voltage ◽  
Open Circuit ◽  
Intelligent Algorithm ◽  
Electrical Vehicle ◽  
Fuzzy Neural ◽  
Intelligent Methods ◽  
Novel Design

This paper is to present a novel design to predict the State of charge (SOC) of the batteries for the Electric Vehicles (EV) using a voltage descent model which has been built based on the analysis of adaptive fuzzy neural intelligent algorithm (AFNIA) and the charge/discharge experimental data of Electric Vehicle. In this design, an improved BP neural network has also been proposed to indicate the correlation between open circuit voltage and SOC. An experiment employed a Lateral Moving and In Situ Steering EV built by Shenzhen Polytechnic. The test and simulation results showed that the intelligent methods can accurately predict the SOC of lithium batteries. The combination of fuzzy control and neural network can achieve an effective way of predicting the SOC of batteries.

Study on Zn-PANi Battery Characteristics Used for Electric Vehicles

2013 ◽  
Vol 724-725 ◽  
pp. 1374-1378
Author(s):  
Sheng Min Cui ◽  
Yuan Lu ◽  
Jin Ping Song ◽  
Jian Feng Wang ◽  
Wen Feng Ding
Keyword(s):  
Electric Vehicles ◽  
Open Circuit Voltage ◽  
Discharge Rate ◽  
Short Circuit ◽  
Dynamic Test ◽  
Open Circuit ◽  
Test Cycle ◽  
Advantages And Disadvantages ◽  
Power Battery ◽  
The Relationship

To study Zn-PANi (polyaniline) battery dynamic characteristics a vehicle power supply based on miniature electric vehicles was designed. And the power battery dynamic test cycle was determined according to the vehicle test cycle prescribed under GB using Land battery testing system. The power battery steady characteristics tests include battery voltage test, per gram capacity test, self-discharge rate test, open circuit voltage and impedance test, cycle life test and short circuit test. Battery discharge characteristics include the relationship between discharge voltage and time, DOD(depth of discharge), the relationship between open circuit voltage, impedance and SOC in different discharge currents. Rationalization proposals in using Zn-PANi batteries efficiently by analyzing battery characteristics, advantages and disadvantages as power batteries are put forward.

scholarly journals Application Error Analysis of SOC Estimation of Pure Electric Vehicles Based on Kalman Signal Big Data Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhaona Lu ◽  
Junlong Wang ◽  
Chuanxing Wang ◽  
Guoqing Li
Keyword(s):  
Electric Vehicles ◽  
Time Integration ◽  
Estimation Method ◽  
Open Circuit ◽  
Battery Pack ◽  
Estimation Accuracy ◽  
Battery Management System ◽  
Battery Management ◽  
Current Time ◽  
Power Battery

The state of charge estimation of a pure electric vehicle power battery pack is one of the important contents of the battery management system. Improving the estimation accuracy of the battery pack’s SOC is conducive to giving full play to its performance and preventing overcharge and discharge of a single battery. At present, the open-circuit voltage ampere-hour integral method is traditionally used to estimate the SOC value of the battery pack; however, this estimation method is not accurate enough to correct the initial value of SOC and cannot solve the problem of current time integration error between this correction and the next correction. As for the battery performance and characteristics of electric vehicles, it is pointed out that the size of the model value will affect the estimation accuracy of the Kalman signal value. Based on the analysis of the factors to be referred to in the calculation and estimation of SOC by Kalman for pure electric vehicles, the scheme is improved considering the change of battery model value, and the Kalman scheme is proposed. The feasibility and accuracy of the scheme are proved by several battery simulation experiments.

scholarly journals A Time-Efficient and Accurate Open Circuit Voltage Estimation Method for Lithium-Ion Batteries

Energies ◽  
2019 ◽  
Vol 12 (9) ◽  
pp. 1803 ◽  
Author(s):  
Yingjie Chen ◽  
Geng Yang ◽  
Xu Liu ◽  
Zhichao He
Keyword(s):  
Lithium Ion Batteries ◽  
Open Circuit Voltage ◽  
Estimation Method ◽  
Nonlinear Function ◽  
Lithium Ion ◽  
Open Circuit ◽  
Constant Current ◽  
Estimation Accuracy ◽  
Battery Modeling ◽  
The Difference

The open circuit voltage (OCV) of lithium-ion batteries is widely used in battery modeling, state estimation, and management. However, OCV is a function of state of charge (SOC) and battery temperature (Tbat) and is very hard to estimate in terms of time efficiency and accuracy. This is because two problems arise in normal operations: (1) Tbat changes with the current (I), which makes it very hard to obtain the data required to estimate OCV—terminal voltage (U) data of different I under the same Tbat; (2) the difference between U and OCV is a complex nonlinear function of I and is very difficult to accurately calculate. Therefore, existing methods have to design special experiments to avoid these problems, which are very time consuming. The proposed method consists of a designed test and a data processing algorithm. The test is mainly constant current tests (CCTs) of large I, which is time-efficient in obtaining data. The algorithm solves the two problems and estimates OCV accurately using the test data. Experimental results and analyses showed that experimental time was reduced and estimation accuracy was adequate.

Sign in / Sign up

Export Citation Format

Share Document