Speed tracking of an electric vehicle using a restricted structure NGMV control algorithm

Cebeci, Cagatay and Grimble, Michael; (2022) Speed tracking of an electric vehicle using a restricted structure NGMV control algorithm. In: 2022 European Control Conference, ECC 2022. IEEE, Piscataway, N.J., pp. 790-795. ISBN 9783907144077 (https://doi.org/10.23919/ECC55457.2022.9838220)

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Abstract

A Restricted-Structure Non-linear Generalized Minimum Variance (RS-NGMV) algorithm is applied to a scalar quasi Linear Parameter-Varying (qLPV), or State-Dependent (SD), Electric Vehicle speed tracking control problem. The model represents the longitudinal vehicle dynamics with disturbance factors from the road and the environment such as road inclination, aerodynamic drag and the rolling resistance forces. The control problem is based on the longitudinal speed tracking under the impact of these disturbances with an emphasis on the inclination. The simulation studies consider constant speed, UDDS and HWFET drive cycle scenarios as the reference speed profiles. The Restricted-Structure (RS) controller is of low order and uses NGMV optimization to calculate the feedback gains. The results show that RS-NGMV is efficient in dealing with disturbances and parameter variations, and battery State of Charge (SOC) results are also presented.

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