Longitudinal velocity and road slope estimation in hybrid electric vehicles employing early detection of excessive wheel slip
Paper i proceeding, 2014

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.

Kalman filter

best-wheel speed

slope estimation

wheel torque

velocity estimation


Matthijs Klomp

E-AAM Driveline Systems

Y. L. Gao

Tongji University

Fredrik Bruzelius

Chalmers, Tillämpad mekanik, Fordonsteknik och autonoma system

Vehicle System Dynamics

0042-3114 (ISSN)

Vol. 52 SUPPL. 1 172-188

The 23rd IAVSD symposium
Qingdao, China,





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