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Active Excitation for Battery Model Parameter Identification

[+] Author Affiliations
Yonghua Li, Hai Yu

Ford Motor Company, Dearborn, MI

Paper No. DSCC2014-6059, pp. V002T23A002; 8 pages
doi:10.1115/DSCC2014-6059
From:
  • ASME 2014 Dynamic Systems and Control Conference
  • Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy Management Optimization; Energy Storage, Optimization; Transportation and Grid Applications; Estimation and Identification Methods, Tracking, Detection, Alternative Propulsion Systems; Ground and Space Vehicle Dynamics; Intelligent Transportation Systems and Control; Energy Harvesting; Modeling and Control for Thermo-Fluid Applications, IC Engines, Manufacturing
  • San Antonio, Texas, USA, October 22–24, 2014
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4619-3
  • Copyright © 2014 by ASME

abstract

In this paper an active excitation approach to battery model parameter identification is discussed. Based on begin-of-life battery model, it is possible to establish a reference parameter table (either fixed, or adaptively learned), and based on such reference parameter table, as well as by analysing battery input signal, active excitation request may be generated. Active excitation is achieved based on maintaining overall torque level with regard to drive input, while adjusting both engine and battery power output (and input). Both conditions for active excitation request, as well as active excitation generation approaches, are presented in detail. Simulation examples using production electrified vehicle battery model parameters and real world drive cycles demonstrate that the proposed approach indeed improves battery model parameter identification accuracy.

Copyright © 2014 by ASME
Topics: Batteries

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