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Citation |
Klomp M, Gao Y, Bruzelius F. Veh. Syst. Dyn. 2014; 52(Suppl 1): 172-188. |
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Copyright |
(Copyright © 2014, Informa - Taylor and Francis Group) |
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DOI |
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PMID |
unavailable |
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Abstract |
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. |