Electric Vehicle Battery Power Estimation and Remote Monitoring Method Based on Optimization Algorithm. Issue 1 (1st October 2022)

• Record Type: Journal Article
• Authors: Wang, Jiaying; Ye, Shen; Xu, Yongjin; Wang, Lixin; Yuan, Jian; Wang, Jinrong
• Is Part Of: Journal of physics. Volume 2310:Issue 1(2022)
• Publication Date: 2022-10-01
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/2310/1/012011
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: With the leap-forward development of China's economy and society, people have put forward higher demands for travel convenience. As a daily means of transportation, automobiles have gradually approached thousands of households. Therefore, the automobile industry has also developed rapidly in recent years. The construction of digital factories for automobile manufacturing and production has rapidly promoted the progress of the new energy automobile industry. The main purpose of this paper is to study the battery power estimation and remote monitoring program of electric vehicles based on the optimization algorithm. This paper mainly selects the battery model, compares and analyzes different algorithms, and completes the database design and the construction of the relevant development environment according to the functional requirements and combined with the actual situation. Experiments show that low temperature has a great influence on the discharge capacity of the battery. The battery can release 74% of the rated capacity at -5°C, while the battery can release only 56% of the rated capacity at -20°C.