Title: A hardware-in-the-loop test rig for development of electric vehicle battery identification and state estimation algorithms

Authors: Abbas Fotouhi; Karsten Propp; Lilantha Samaranayake; Daniel Auger; Stefano Longo

Addresses: Advanced Vehicle Engineering Centre, School of Aerospace, Transport and Manufacturing (SATM), Canfield University, Canfield, MK43 0AL, UK ' Advanced Vehicle Engineering Centre, School of Aerospace, Transport and Manufacturing (SATM), Canfield University, Canfield, MK43 0AL, UK ' Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Peradeniya, Sri Lanka ' Advanced Vehicle Engineering Centre, School of Aerospace, Transport and Manufacturing (SATM), Canfield University, Canfield, MK43 0AL, UK ' Advanced Vehicle Engineering Centre, School of Aerospace, Transport and Manufacturing (SATM), Canfield University, Canfield, MK43 0AL, UK

Abstract: This paper describes a hardware-in-the-loop (HIL) test rig for the test and development of electric vehicle battery parameterisation and state-estimation algorithms in the presence of realistic real-world duty cycles. The rig includes two electric machines, a battery pack, a real-time simulator, a thermal chamber and a PC for human-machine interface. Other parts of a vehicle powertrain system are modelled and used in the real-time simulator. A generic framework has been developed for real-time battery measurement, model identification and state estimation. Measurements are used to extract parameters of an equivalent circuit network model. Outputs of the identification unit are then used by an estimation unit trained to find the relationship between the battery parameters and state-of-charge. The results demonstrate that even with a high noise level in measured data, the proposed identification and estimation algorithms are able to work well in real-time.

Keywords: battery modelling; electric powertrain; hardware-in-the-loop test; state-of-charge estimation; identification.

DOI: 10.1504/IJPT.2018.090391

International Journal of Powertrains, 2018 Vol.7 No.1/2/3, pp.227 - 248

Received: 15 Jan 2017
Accepted: 24 Nov 2017
Published online: 13 Mar 2018 *

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