Dissertation > Excellent graduate degree dissertation topics show

SOC Estimation of VRLA for Electric Vehicle Research

Author: JiangKai
Tutor: WangHaiBo
School: Central South University
Course: Control Engineering
Keywords: State of Charge(SOC) Valve regulated Lead-acid battery Suboptimal fading extended Kalman filter(SFEKF)
CLC: TM912
Type: Master's thesis
Year: 2013
Downloads: 30
Quote: 0
Read: Download Dissertation

Abstract


In the recent years, with the lack of petroleum resources and the degradation of air environment, the energy saving and environmental protection of electric vehicle is the development direction of automobile industry. Battery is the main power source of electric vehicles and its price occupies a large proportion in the whole vehicle cost. Thus, it is great significance that battery management system (BMS) for on-board battery under effective control and management, to improve the battery performance and prolong the battery life. The state of charge estimation of battery is the core function of BMS, not only can it reflects the current remaining power of battery, but also provide a reasonable control strategy for vehicle.In this paper, in order to improve the SOC estimation based on the extended kalman filter, the battery model with hysteresis effect adjusted factor and the suboptimal fading factor of extended kalman filtering algorithm are proposed. Firstly, a series of performance testing experiment for VRLA are designed to acquire the static relationship between SOC and its influence factors, and under the analysis of the hysteresis effect of battery, the battery model with hysteresis effect adjusted factor is put forward. Secondly, battery model parameters are identified by the least square recurrence method. Finally, the compare of simulation voltage of model and true voltage of battery validate the model is reasonable.SOC estimation based on extended kalman filter is low precision when the battery model is uncertainty and the statistical noise is inappropriate. Thus, a suboptimal fading factor extended kalman filter (SFEKF) algorithm is proposed, it can remain strong track with the true SOC in the condition of poor compatibility of model and inaccurate noise statistics. Then in the same UDDS conditions, the SFEKF and EKF are adopted to estimate the SOC of VRLA, the simulated result show that the SFEKF algorithm has a higher accuracy and better robustness in SOC estimation.

Related Dissertations

  1. Study of the Valve-Regulated Lead-acid Battery On-Line Monitoring System,TM912
  2. Research on the Monitor and Control Module for Battery Running State,TM910
  3. The Development Research of Battery Management System Based on the PLC on the Small Pure Electric Coach Vehicle,U469.72
  4. Study on SOC Estimation of Power Lithium-ion Battery Based on Support Vector Machine,TM912
  5. Research of VRB and Its Aplication on Doubly-fed Wind Power Generator,TM912
  6. The Research and Design of Equilibrium in Power Batteries,TM912
  7. The Application Research on Estimation of Lithium-ion Battery SOC,TM912
  8. ARM-based Design and Implementation of Battery Management and Monitoring System,TM912
  9. Based of Fuzzy Control Communication Power Battery Testing System Design and Research,TM912
  10. Research on the Power Management IC with High Stability,TN402
  11. The Study and Design of VRLA Battery Intelligent On-Line Monitoring System,TP274
  12. Calculation of Capacitance for Ni-MH Battery Based on Fuzzy Neural Network and Research of Battery Management System,U464.93
  13. Research and Design on Intelligent Charger for 12V Valve-regulated Lead-acid Battery,TM910.6
  14. Research on Battery Management System of Electric Vehicle,TM912
  15. Technology Research of Solar Energy LED Street Lamp Intelligent Control System,TM923
  16. Research on the Super-Capacitor Stacks Management System of the Electric Bus,TM53
  17. The Research of Electric Vehicle Battery Monitoring System Based on ARM,U469.72
  18. Research on the Management and Monitoring System of Lithium Battery for Data Storage Devices,TM912
  19. Energy Management Strategy Based on Neural Network for HEV Lithium Power Batteries,TM912
  20. Research on Strategy of the State of Charge Estimation of Lithium Battery,TM912

CLC: > Industrial Technology > Electrotechnical > Independent power supply technology (direct power) > Battery
© 2012 www.DissertationTopic.Net  Mobile