Reliability of Extended Kalman Filtering Technic on Vehicle Mass Estimation
In this paper, vehicle mass estimation problem was researched by the Kalman Filtering process to investigate the effectiveness of Extended Kalman Filter technique on mass estimation, which has widely been studied on the related literature with all the successful results. For the purpose, a longit...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Bursa Technical University
2021-06-01
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| Series: | Journal of Innovative Science and Engineering |
| Subjects: | |
| Online Access: | http://jise.btu.edu.tr/en/download/article-file/1488383 |
| Summary: | In this paper, vehicle mass estimation problem was researched by the Kalman Filtering
process to investigate the effectiveness of Extended Kalman Filter technique on mass
estimation, which has widely been studied on the related literature with all the successful
results. For the purpose, a longitudinal vehicle dynamics model was developed, and the
equations were transformed into the well-known state space form. Nonlinear problem in
its nature was discretised and linearized by using Euler method. In addition, road slope
was calculated by a road slope inclinometer logic. IPG CarMaker® was utilized to
overcome the nonlinearities, design the test environment and the conditions, as it was
observed that the simulation results were not met the expectations with the logged
vehicle physical test data. Several test scenarios were run to simulate level and wavy
road with different vehicle speeds. The results showed that the Extended Kalman Filter
could provide a reasonable convergence when the initial values were correctly selected,
no nonlinear issue occurred and certain tuning parameters were defined with stable
boundary conditions for mass estimation. |
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| ISSN: | 2602-4217 2602-4217 |