Real Time Application of Battery State of Charge and State of Health Estimation
Document Type
Conference Proceeding
Publication Date
3-28-2017
Department
Department of Electrical and Computer Engineering
Abstract
A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model. This method allows the user to monitor battery operating conditions instantaneously. The proposed method is implemented and verified by series of comprehensive hardware-in-loop (HIL) testing with high voltage HEV battery pack having a capacity of the 29Ah lithium-cobalt-oxide cell through multiple drive cycles. This technology was designed by Energy Storage Systems and Sustainability Lab at Michigan Technological University to be used in the hybrid electric vehicle based on a 1950 Chevy Truck developed at Michigan Technological University, Hybrid Electric Vehicle Enterprise.
Publication Title
SAE Technical Papers
Recommended Citation
Khan, K.,
Zhou, B.,
&
Rezaei, A.
(2017).
Real Time Application of Battery State of Charge and State of Health Estimation.
SAE Technical Papers,
2017-March(March).
http://doi.org/10.4271/2017-01-1199
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/2992
Publisher's Statement
© 2017 SAE International. Publisher’s version of record: https://doi.org/10.4271/2017-01-1199