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Longitudinal velocity and road slope estimation in hybrid electric vehicles employing early detection of excessive wheel slip

M. Klomp ; Y. L. Gao ; Fredrik Bruzelius (Institutionen för tillämpad mekanik, Fordonsteknik och autonoma system)
Vehicle System Dynamics (0042-3114). Vol. 52 (2014), p. 172-188.
[Artikel, refereegranskad vetenskaplig]

Vehicle speed is one of the important quantities in vehicle dynamics control. Estimation of the slope angle is in turn a necessity for correct dead reckoning from vehicle acceleration. In the present work, estimation of vehicle speed is applied to a hybrid vehicle with an electric motor on the rear axle and a combustion engine on the front axle. The wheel torque information, provided by electric motor, is used to early detect excessive wheel slip and improve the accuracy of the estimate. A best-wheel selection approach is applied as the observation variable of a Kalman filter which reduces the influence of slipping wheels as well as reducing the computational effort. The performance of the proposed algorithm is illustrated on a test data recorded at a winter test ground with excellent results, even for extreme conditions such as when all four wheels are spinning.

Nyckelord: velocity estimation, Kalman filter, wheel torque, best-wheel speed, slope estimation



Denna post skapades 2014-07-22.
CPL Pubid: 200644

 

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Institutioner (Chalmers)

Institutionen för tillämpad mekanik, Fordonsteknik och autonoma system

Ämnesområden

Maskinteknik

Chalmers infrastruktur