By Zhigang Fang

ISBN-10: 1138028339

ISBN-13: 9781138028333

ISBN-10: 1315680955

ISBN-13: 9781315680958

Energy technological know-how and utilized know-how contains contributions on quite a lot of topics:
- applied sciences in geology, mining, oil and fuel exploration and exploitation of deposits
- power move and conversion, fabrics and chemical technologies
- Environmental engineering and sustainable development
- electric and digital know-how, energy method engineering
- Mechanical, production, strategy engineering
- regulate and automation
- Communications and utilized info technologies
- utilized and computational mathematics
- equipment and algorithms optimization
- community know-how and application
- procedure attempt, prognosis, detection and monitoring
- acceptance, video and photo processing
The ebook will attract teachers and engineers fascinated with strength and utilized sciences.

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Additional info for Energy Science and Applied Technology: Proceedings of the 2nd International Conference on Energy Science and Applied Technology

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2002. Battery performance models in ADVISOR, J Power Sources, 110 (2):321–329. Kaiser R. 2007. Optimized battery-management system to improve storage lifetime in renewable energy systems, Journal of Power Sources, 168(1):58–65. Liu Jiang, Shi Yikai, Yuan Xiaoqing, et al. 2013. SOC Estimation of Lithium Battery Based on RLS and EKF, Measurement & Control Technology, 32(8):123–125. ) © 2016 Taylor & Francis Group, London, ISBN 978-1-138-02833-3 SOC estimation strategy based on online feed-forward compensation for lithium-ion battery Xuanju Dang, Yan Mo, Hui Jiang, Xiru Wu & Xiangwen Zhang School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guangxi, China ABSTRACT: Accurately estimating the internal parameters is very important for electric vehicles, which can not only guarantee that the State Of Charge (SOC) of the power battery is maintained within a reasonable range of the operation to avoid the risk of the overcharge or the deep discharge of the power battery, but also both improve the efficiency and extend the life of the battery.

Compared with the conventional lead-acid battery or the nickel metal hydride battery, the lithium-ion battery has the advantages of high energy density, no memory effect, long cycle life and environment friendly. The SOC estimation of the battery includes two main components: parameter identification and SOC estimation. (1) The methods for parameter identification usually include the genetic algorithm, the least squares algorithm, the dual extended Kalman filter. (2) The SOC estimation methods usually include the open-circuit voltage method, the current integral method, the Kalman filter method, the extended Kalman filter method, the unscented Kalman filter method and the adaptive extended Kalman filter method.

In the BP neural network, M is the implied node (let M = 10), losing is defined as the S-type function of the hidden layer, and purelin is the output linear function. 08e−04. The modeling and testing of the OCV-SOC neural network is shown in Figure 6. The OCV-SOC model is established by the BP neural network, and then tested as shown in Figure 6. 9. 9. Therefore, the proposed OCV-SOC model can meet the practical requirement. 1996). Under the FUDS operation, the experiment with the initial condition of SOC = 1 is executed for 27 cycles until the battery is emptied.

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Energy Science and Applied Technology: Proceedings of the 2nd International Conference on Energy Science and Applied Technology by Zhigang Fang


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