A Continuous-time LPV model for battery state-of-health estimation using real vehicle data

• One approach for State-of-health estimation onboard electric vehicles is to train a data-driven virtual battery on operational data and use this model, rather than the actual battery, for performance tests. A temperature-dependent continuous-time output-error (OE) model is proposed as virtual battery and identified and validated on real operational data from electric buses. The proposed model is compared to discrete-time and parameter-invariant models and shows better performance on all data sets. In addition, the OE model structure is shown to be superior to a conventional Auto Regressive eXogenous (ARX) model for the purpose of modeling the battery voltage response. Finally, challenges regarding vehicle log data are identified and improvements to the model are suggested in order to capture observed un-modeled phenomena.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering (hsv//eng)

Keyword

Continuous-time

Li-ion battery

LPV

SOH

System identification

Battery management systems

Continuous time systems

Vehicles

Auto-regressive

Battery voltages

Operational data

Output errors

Performance tests

State of health

Temperature dependent

Secondary batteries

Publication and Content Type

ref (subject category)

kon (subject category)