Abstract
The working life of power system mainly depends on the life of the battery. The health state evaluation method is one of the key technologies of Prognostic and Health Management (PHM). According to the health evaluation result of the satellite battery, the potential trend of health degradation and hidden danger of influence of health level can timely be found, thus improving the level of effectiveness, precision and autonomation of the power system management. In this paper, a satellite battery health evaluation method based-on Bayesian network is proposed. Firstly, the Bayesian network topology structure for the satellite battery health evaluation is designed by means of satellite ground phase design principle knowledge and ground test engineering experience. Secondly, the historical ground test data is analyzed and processed, and the Bayesian network training samples are built based on the expert knowledge and historical data. Thirdly, the prior probability and conditional probability of each node of the Bayesian network are calculated according to the training samples, finally, the health status of the batteries is calculated using the current test data. The experimental results verified the effectiveness of the proposed health state evaluation method.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
