Longitudinal velocity and road slope estimation in hybrid electric vehicles employing early detection of excessive wheel slip
Paper in 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, Applied Mechanics, Vehicle Engineering and Autonomous Systems

Vehicle System Dynamics

0042-3114 (ISSN) 1744-5159 (eISSN)

Vol. 52 SUPPL. 1 172-188

The 23rd IAVSD symposium
Qingdao, China,

Subject Categories

Mechanical Engineering



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