Integration of sampling based battery state of health estimation method in electric vehicles. (1st August 2016)

• Record Type: Journal Article
• Authors: Ozkurt, Celil; Camci, Fatih; Atamuradov, Vepa; Odorry, Christopher
• Is Part Of: Applied energy. Volume 175(2016)
• Page Start: 356
• Page End: 367
• Publication Date: 2016-08-01
• Subjects: State of health estimation -- Electric vehicles -- Li-ion batteries -- System level diagnostics; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.05.037
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Presentation of a prototype system with full charge discharge cycling capability. Presentation of SoH estimation results for systems degraded in the lab. Discussion of integration alternatives of the presented method in EVs. Simulation model based on presented SoH estimation for a real EV battery system. Optimization of number of battery cells to be selected for SoH test. Abstract: Battery cost is one of the crucial parameters affecting high deployment of Electric Vehicles (EVs) negatively. Accurate State of Health (SoH) estimation plays an important role in reducing the total ownership cost, availability, and safety of the battery avoiding early disposal of the batteries and decreasing unexpected failures. A circuit design for SoH estimation in a battery system that bases on selected battery cells and its integration to EVs are presented in this paper. A prototype microcontroller has been developed and used for accelerated aging tests for a battery system. The data collected in the lab tests have been utilized to simulate a real EV battery system. Results of accelerated aging tests and simulation have been presented in the paper. The paper also discusses identification of the best number of battery cells to be selected for SoH estimation test. In addition, different application options of the presented approach for EV batteries have been discussed in the paper.