This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Application of an Adaptive Digital Filter for Estimation of Internal Battery Conditions
Technical Paper
2005-01-0807
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
This paper proposes an innovative and accurate method of estimating the internal conditions of rechargeable batteries for vehicles powered by electric motors, such as electric vehicles (EVs) and hybrid electric vehicles (HEVs). The proposed method is necessary to utilize battery power fully on vehicles powered by electric motors (especially HEVs) and thereby improve fuel economy or reduce the battery size.
As the first step in this study, the relationship between the current and terminal voltage of a rechargeable lithium-ion battery was described using a linear parameter varying (LPV) model. That made it possible to reduce the problem of estimating the internal battery conditions (internal resistance, time constant, and so on) to a problem of recursively estimating the model parameters with an adaptive digital filter. An up-to-date parameter identification algorithm has been applied in order to estimate the model parameters recursively with good accuracy at all times, since they vary greatly depending on the operating conditions (state of charge (SOC), temperature, degree of battery degradation, etc.). As the second step, the calculated model parameters (internal resistance, time constant) and another type of LPV battery model were used to derive the open voltage (one of the internal states). The calculated model parameters and open voltage facilitated accurate estimations of the SOC, available output power and acceptable input power using an inherent battery characteristic (the steady-state correlation between open voltage and SOC) and maximum power definitions regardless of the operating conditions.
This paper describes an example of the application of this method to a lithium-ion battery and presents the simulation and experimental results. Bench test results verified that SOC estimation accuracy was within ±4% and that of the available output power and acceptable input power was within ±10%.
Recommended Content
Authors
Topic
Citation
Asai, H., Ashizawa, H., Yumoto, D., Nakamura, H. et al., "Application of an Adaptive Digital Filter for Estimation of Internal Battery Conditions," SAE Technical Paper 2005-01-0807, 2005, https://doi.org/10.4271/2005-01-0807.Also In
SAE 2005 Transactions Journal of Passenger Cars: Electronic and Electrical Systems
Number: V114-7; Published: 2006-02-01
Number: V114-7; Published: 2006-02-01
References
- Matsumura S. Ishikawa F. et al. “Estimation of Open Voltage and Residual Values for Pb Battery By Adaptive Digital Filter” T.IEE Japan 112-C 4 259 267 1992
- Shinnaka S. “Adaptive Algorithm” Sangyou Tosho 1990
- Adachi K. Ito K. Fujishiro T. Kanai K. “Parameter Identification of a Vehicle's Yaw Rate Transfer Function” JSAE Scientific Lecture Series 901, 901041 1990