The Implementation Of Monitoring Platform Of Battery Management System With Model Parameter Extraction

With the rapid development of automobile industry, energy and environmental issues become much more serious. Stringent emissions and fuel efficiency standards promote the development of new energy vehicles, which is safe, clean, and efficient. As an important part of electric car in“three vertical and three horizontal”layout during the 10th Five-year Plan, technology of battery management systems in electric vehicles has become a hot topic. This work focuses on the battery management system technology. This paper proceeds as follow.Advantages and disadvantages of the ampere hour counting method and the electromotive force (EMF) method were discussed. Based on a parallel feedback weighting structure designed in previous research which combines ampere hour counting method and EMF method, this paper presented a novel parallel feedback weighting algorithm based on two-dimensional dynamic parameters model.The management system and monitoring platform were designed to realize the proposed algorithm. The management system consisted of SOC calculation module, communication module, EEPROM module and security module. It used to calculate the SOC of the batteries, send status information of batteries to the monitoring platform and receive parameters from the monitoring platform. The monitoring platform included display module, drawing module, database module and communication module. The parameter extraction module was designed and the implement was presented in detail, which used to extract parameters of two-dimensional dynamic model in the battery management system.The standard charge and discharge experiments were done under monitoring platform. The dynamic parameters were acquired through experimental results. The SOC of batteries were estimated via parallel feedback weighting algorithm based on two-dimensional dynamic parameters model. Compare to the traditional parallel feedback weighting algorithm, the results show that the novel algorithm proposed in this paper improved the estimation accuracy of SOC. It is a practical innovative SOC estimation algorithm.