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.
Original language | English |
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Title of host publication | 2022 European Control Conference, ECC 2022 |
Place of Publication | Piscataway, N.J. |
Publisher | IEEE |
Pages | 790-795 |
Number of pages | 6 |
ISBN (Electronic) | 9783907144077 |
DOIs | |
Publication status | Published - 5 Aug 2022 |
Event | European Control Conference - Duration: 12 Jul 2022 → 15 Jul 2022 |
Conference
Conference | European Control Conference |
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Period | 12/07/22 → 15/07/22 |
Keywords
- resistance
- roads
- heuristic algorithms
- electric vehicles
- batteries