声明
1 Introduction
1.1Background and significance of study
1.1.1Study background
1.1.2Study significance
1.2Topic research status in China and other contries
1.2.1Battery modeling research status
1.2.2SOC prediction research status
1.2.3SOH prediction research status
1.3The main contents of research
2 Battery modeling and parameter estimation
2.1Principles and characteristics of lithium batteries
2.1.1Battery technology comparison
2.1.2Battery structure and working principle
2.1.3Main technical parameters of battery
2.2Brief introduction to battery models
2.2.1Existing equivalent circuit models analysis
2.2.2Battery model selection
2.3Model parameters estimation and validation
2.3.1Levenberg-Marquardt parameter estimation method
2.3.2Parameter estimation results
2.4Chapter short summary
3Battery SOC prediction based on AEKF
3.1The basic principles of Kalman filter
3.2 SOC estimation algorithm based on EKF
3.3SOC estimation algorithm based on AEKF
3.3.1Application of AEKF
3.3.2Introduction of battery SOC testing
3.4 Simulation analysis
3.5 Chapter short summary
4SOH prediction
4.1Battery State of Health definition and influencing factors
4.2 SOH estimation based on Kalman filtering algorithm
4.2.1Ampere-hour integration method
4.2.2The Kalman filter design
4.3 Simulation analysis
4.4 Chapter shortsummary
Conclusion
致谢
参考文献
The results of research during the obtaining degree
兰州交通大学;
