Real Time Application of Battery State of Charge and State of Health Estimation

2017-01-1199

03/28/2017

Features
Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
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.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-1199
Pages
9
Citation
Khan, K., Zhou, B., and Rezaei, A., "Real Time Application of Battery State of Charge and State of Health Estimation," SAE Technical Paper 2017-01-1199, 2017, https://doi.org/10.4271/2017-01-1199.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1199
Content Type
Technical Paper
Language
English